Bill Gurley was one of Silicon Valley’s smartest and most successful VCs. He recently gave a talk at the All-In Summit that was really two talks in one. The first part was railing against the consequences of regulatory capture on innovation and a second part, about the consequences of premature government regulation of AI and why the incumbents are all for it. He illustrated his talk with regulatory horror stories in the telecom market, electronic health records, and Covid antigen tests.

Bill’s closing line, “The reason why Silicon Valley is so successful is that it’s so fxxxng far away from Washington” received great applause. Unfortunately, for startups entering a regulated market following this advice this might not be the optimum path.

(You can watch Bill’s entire 24-minute talk here or his thesis summarized in this 7 second clip here. https://youtu.be/HMIyDf3gBoY?feature=shared )

Let’s be clear, rent seekers and regulatory capture strangle innovation in its crib. It’s the antithesis of how founders want to build a business. (And to be fair that was the point of the last part of Bill’s presentation.) But entrepreneurs entering regulated markets need to understand how the game is played, how they can play it, what their VC’s should be doing to help them, and how to win.

Regulation
What’s regulatory capture? Why is it bad? And why was Bill’s advice of staying away from Washington flawed for startups?

All businesses have regulations to follow — paying taxes, incorporating the company, complying with financial reporting. And some have to ensure that there are no patents or blocking patents. But regulated markets are different. Regulated marketplaces have significant government regulation to promote and protect (ostensibly) the public interest for the benefit of all citizens. A good example is the regulations the FDA (Food and Drug Administration) have in place for approving new drugs and medical devices.

In a regulated market, the government controls how products and services are allowed to enter the market, what prices may be charged, what features the product/service must have, safety of the product, environmental regulations, labor laws, domestic/foreign content, etc. In the U.S. regulation happens on three levels:

• federal laws that are applicable across the country developed by Federal government in Washington, D.C.
• state laws that are applicable in one state imposed by state government
• local city and county laws come from local government

Federal Regulation
In the U.S. the government has regulatory authority over commerce between the states, foreign trade, and other business activities of national scope. Congress decides what things need to be regulated and passes laws that determine those regulations. Congress often does not include all the details needed to explain how an individual, business, state or local government, or others might follow the law. To make the laws work day-to-day, Congress authorizes government agencies to write the regulations which set the specific requirements about what is legal and what isn’t. The regulatory agencies then oversee these requirements.

In the U.S. startups might run into an alphabet soup of federal regulatory agencies, for example: ATF, CFPB,DEA, DoD, EPA, FAA, FCC, FDA, FDIC, FERC, FTC, OCC, OSHA, SEC. These agencies exist because Congress passed laws.

State Regulation
In addition to federal laws, each State has its own regulatory environment that applies to businesses operating within the state in areas such as land-use, zoning, motor vehicles, state banking, building codes, public utilities, drug laws, etc.

Cities/County Regulation
Finally, local cities and counties may have local laws and regulatory agencies or departments like taxi commissions, zoning laws, public safety, permitting, building codes, sanitation, drug laws, etc.

Incumbents Advantage — Rent Seekers and Regulatory Capture
If you’re a startup entering a regulated market (Telecom, Pharma, Education, Energy, Department of Defense, Intelligence, Health, Fintech, Insurance, Transportation, Agriculture, Gaming, Cannabis, Petrochemicals, Automotive, Air Transportation, Fishing, et al.) you need to know that the game is rigged. And it’s not in your favor.

Incumbents in a regulated a market keep out new, innovative, and disruptive competitors by “gaming the system” in their favor. They do this by either being Rent Seekers and/or by Regulatory Capture. (Bill Gurley’s point.)

Rent seekers are individuals or organizations with successful existing business models who use government regulation and lawsuits to keep out new entrants that might threaten their business models. They use every argument — from public safety to lack of quality or loss of jobs — to lobby against the new entrants. Rent seekers spend money lobbying to increase their share of an existing market instead of creating new products or markets but create nothing of value.

These barriers to new innovative startups are called economic rent. Examples of economic rent include state automobile franchise laws, taxi medallion laws, limits on charter schools, cable company monopolies, patent trolls, bribery of government officials, corruption, and regulatory capture.

Rent-seeking lobbyists go directly to legislative bodies (Congress, State Legislatures, City Councils) to persuade government officials and their staff to enact laws and regulations in exchange for campaign contributions, appeasing influential voting blocks, or the “revolving door” — offering officials future jobs in the industry they regulated. They use the courts to tie up and exhaust a startup’s limited financial resources. Their lobbyists also work through regulatory bodies like the FCC, SEC, FTC, Public Utility, Taxi, or Insurance Commissions, School Boards, etc.

Regulatory capture is what happens when the very organizations set up to protect the public’s health and safety, or to provide an equal playing field, are taken over by the very people they’re supposed to regulate. These are the examples Bill Gurley were talking about.

Tech Companies Use Regulatory Capture
In my first two decades inside the Silicon Valley bubble we built products people wanted and needed. We competed with other technology companies, and, like Bill Gurley, largely ignored whatever was going on in Washington. We were content Washington didn’t know we existed. Unless you were in life sciences (therapeutics, medical devices, or diagnostics), very little government regulation applied. We ignored Washington and Washington mostly ignored us (defense contractors excepted.)

The tech ecosystem got a rude awakening in May 1998 when the U.S. Justice Department and 20 state Attorneys General brought suit again Microsoft for anticompetitive practices designed to maintain its monopoly in PC operating systems and internet browsers. While tech hadn’t come to Washington, Washington came for the tech industry. Until then no tech company had an organized lobbying organization of significance in DC.

Fast forward 25 years. The tech industry grew up and realized rather than running away from Washington they needed to play the game. Companies like Intuit mastered regulatory capture as a massive advantage while Big Tech (Microsoft, Amazon, Google, Facebook, Oracle, Intuit, Uber et al.) spent $124 million in lobbying and campaign contributions in the 2020 election with 333 registered lobbyists.

Startups have successfully disrupted regulated markets and rent seekers — Uber with local taxi licensing laws (a board Bill Gurley sat on with a ShowTime series highlighting his role), AirBnB with local zoning laws, Tesla with state dealership licensing, SpaceX competing with the Air Force and United Launch Alliance — and in doing so they have built impenetrable moats for their business.

What Do Startups Need to Know?
There’s nothing magical about dealing with regulated markets. However, every regulated market has its own rules, dynamics, language, players, politics, etc. And they are all very different from the business-to-consumer or business-to-business markets most founders and their investors are familiar with.

How do you know you’re in a regulated market? It’s simple– ask yourself three questions:

• Can I do anything I want or are there laws and regulations that might stop me or slow me down?
• Are there incumbents who will view us as a threat to the status quo? Can they use laws and regulations to impede our growth?
• Do you understand how the regulatory process works? For example, do you just fill out an online form and pay a $50 fee with your credit card and get a permit? Or do you need to spend millions of dollars and years running clinical trials to get FDA clearance and approval? And are these approvals good in every state? In every country? What do you need to do to sell worldwide?

What Do I Need to Do?
The first step is to understand what you’re up against. Who are the incumbents, who do they influence, how much are they spending on influence, who are their lobbyists, and what are their messages? And most importantly, how are they going to stop you from scaling?

Next, figure who are the other stakeholders, saboteurs, rent seekers, influencers, bureaucrats, politicians, and regulators. As you get out of the building and start talking to people you’ll discover more and more players. You’ll discover that the interests of your product’s end user versus a regulator versus an advocacy group, key opinion leaders or a politician, are radically different. For you to succeed you need to understand all of them.

Start diagraming out the relationships of all the customer segments. Who influences who? How do they interconnect? What laws and regulations are in your way for deployment and scale? How powerful are each of the players? For the politicians, what are their public positions versus actual votes and performance. Follow the money by using opensecrets.org. If an elected official’s major donor is organization x, you’re not going to be able to convince them with a cogent argument. And most importantly, start asking “who are the best lobbyists/advisors in this market?”

The book Regulatory Hacking calls this diagram the Power Map. As an example, this is a diagram of the multiple beneficiaries and stakeholders that a software company developing math software for middle school students has to navigate. Your diagram may be more complex. There is no possible way you can draw this on day one of your startup. You’ll discover these players as you get out of the building and start filling out your value proposition canvases.

While this sounds complicated, entering a regulated market should be a strategy not a disconnected set of tactics. (Or worse obliviousness.) You need a lobbying/government relations strategy from day one.

Draw your strategy diagram (see figure below) and share it with your board. What regulatory issues need to be solved? In what order? For example, do you beg for forgiveness or ask for permission? How do you get regulators who don’t see a need to change to move? How do you get your early customers to advocate on your behalf? (The books The Fixer and Regulatory Hacking give examples of regulatory pitfalls, problems and suggested solutions.)

Most early stage startups don’t have the regulatory domain expertise in-house. Get outside advice at each step. Hire/advisors from the inside industry but use them to make you smarter not just to outsource the work. Having a meeting or two with a congressman or contributing to their campaign might get you a return call, but only sustained engagement (via money, influence, and an on-the-ground presence in D.C.) will move the needle. Eventually you’ll need to build an in-house team to manage regulatory affairs.

Choose VCs who have experience in operating in regulated markets — not those who hope it stays away. Have them tell you how they helped other companies in their portfolio succeed, pitfalls to avoid, and the lobbying resources they can bring to bear. You and your board need to be in sync about the costs and risks of getting into a street fight entering these markets. (Strategic choices include asking for permission versus forgiveness, public versus private battles. Tactical activities can include influencing key opinion leaders, political donations, advocacy groups, and grassroots and grasstops campaigns, etc.)

Finally, as an innovation ecosystem (VCs, their limited partners, and startups) we need to do a better job in insisting in transparency in government, calling out rent seekers and regulators who no longer regulate, and try to keep government from premature regulation of new innovation. For the majority of regulators and policymakers who want to make the system better, we can help shape policy by educating them on why the products/changes we are proposing make the world a better place.

But startups? They need to understand the game and work the system.

Post note. Ironically the best example of premature government regulation was AT&T and U.S. telephone service. In 1921 AT&T argued that telephone service was a natural monopoly, and that competition was inefficient. The government agreed and land line communications became a government sanctioned monopoly for the next 63 years. Innovation in telecom outside of AT&T died and the industry could only innovate as fast as AT&T approved. A possible proxy for why the incumbent AI providers went to Congress. They want to lock-in their lead.

Lessons Learned

— If you’re in regulated market, often the game is rigged by incumbents

• Understand Rent Seeking and Regulatory Capture
• You need a lobbying/government relations strategy from day one

— Choose VCs who understand how to play the game not those who hope it stays away

— The CEO needs to get out of the building to understand the regulatory ecosystem

• CEO and board need to be in sync about the learning and strategy

— Hire initial lobbyists (but learn from them, not just outsource to them)

• As the company gets larger staff an internal public affairs group to manage the lobbying effort

— If you figure out the regulatory game, it can be your defensible moat

Steve Blank writes how to build successful companies at www.steveblank.com.

But the Atomic Bomb story that starts at Los Alamos with Oppenheimer and General Grove misses the fact that from mid-1940 to mid-1942 it was Vannevar Bush (and his number 2, James Conant, the president of Harvard) who ran the U.S. atomic bomb program and laid the groundwork that made the Manhattan Project possible.

Here’s the story.

During World War II, the combatants (Germany, Britain, U.S. Japan, Italy, and the Soviet Union) made strategic decisions about what types of weapons to build (tanks, airplanes, ships, submarines, artillery, rockets), what was the right mix (aircraft carriers, fighter planes, bombers, light/ medium/ heavy tanks, etc.) and how many to build.

But only one country — the U.S. — succeeded in building nuclear reactors and nuclear weapons during the war, moving from atomic theory and lab experiments to actually deploying nuclear weapons in a remarkable 3 years.

Three reasons unique to the U.S. made this possible:

1. Émigré and U.S. physicists who feared that the Nazis would have an atomic bomb led to passionate advocacy before the government became involved.
2. A Presidential Science Advisor who created a civilian organization for building advanced weapons systems, funded and coordinated atomic research, then convinced the president to authorize an atomic bomb program and order the Army build it.
3. The commitment of U.S. industrial capacity and manpower to the atomic bomb program as the №1 national priority.

The Atom Splits
In December 1938 scientists in Nazi Germany reported a new discovery — that the Uranium atom split (fissioned) when it hit with neutrons. Other scientists calculated that splitting the uranium atom released an enormous amount of energy.

Fear and Einstein
Once it became clear that in theory a single bomb with enormous destructive potential was possible, it’s hard to understate the existential dread, fear, and outright panic of U.S. and British emigre physicists — many of them Jewish refugees who had fled Germany and occupied Europe. In the 1920s and ’30s, Germany was the world center of advanced physics and the home of many first-class scientists. After seeing firsthand the terror of Nazi conquest, the U.S. and British understood all too well what an atomic bomb in the hands of the Nazis would mean. They assumed that German scientists had the know-how and capacity to build an atomic bomb. This was so concerning that physicists convinced Albert Einstein in August 1939 to write to President Roosevelt pointing out the potential of an atomic weapon and the risk of the bomb in German hands.

Motivated by fear of a Nazi atomic bomb, for the next two years scientists in the U.S. lobbied, pushed and worked at a frantic speed to get the government engaged, believing they were in a race with Nazi Germany to build a bomb.

After Einstein’s letter, Roosevelt appointed an Advisory Committee on Uranium. In early 1940 the Committee recommended that the government fund limited research on Uranium isotope separation. It spent $6,000.

Vannevar Bush Takes Over — National Defense Research Committee (NRDC)
European émigré physicists (Einstein, Fermi, Szilard, and Teller) and Ernest Lawrence at Berkeley were frustrated at the pace the Advisory Committee on Uranium was moving. As theorists, they thought it was clear an atomic bomb could be built. They wanted the U.S. government to aggressively fund atomic research, so that the U.S. could build an atomic bomb before the Germans had one.

They weren’t alone in feeling frustrated about the U.S. approach to advanced weapons, not just atomic bombs.

In June 1940 Vannevar Bush, ex-MIT dean of engineering; and a group of the country’s top science and research administrators (Harvard President James Conant, Bell Labs President and head of the National Academy of Sciences Frank Jewett, and Richard Tolman Caltech Dean) all felt that there was a huge disconnect. The U.S. military had little idea of what science could provide in the event of war, and scientists were wholly in the dark as to what the military needed. As a result, they believed the U.S. was woefully unprepared and ill-equipped for a war driven by technology.

This group engineered a massive end run around the existing Army and Navy Research and Development labs. Bush and others believed that advanced weapons could be created better and faster if they could be designed by civilian scientists and engineers in universities and companies.

The scientists drafted a one-page plan for a National Defense Research Committee (NDRC). The NDRC would look for new technologies that the military labs weren’t working on (radar, proximity fuses, and anti-submarine warfare. (At first, atomic weapons weren’t even on their list.)

in June 1940 Bush got Roosevelt’s approval for the NDRC. In a masterful bureaucratic sleight of hand the NDRC sat in the newly created Executive Office of the President (EOP), where it got its funding and reported directly to the president. This meant that the NDRC didn’t need legislation or a presidential executive order. More importantly it could operate without congressional or military oversight.

Roosevelt’s decision gave the United States an 18-month head start for employing science in the war effort.

The NRDC was divided into five divisions and one committee, each run by a civilian director and each having a number of sections. (see diagram below.)

Bush became chairman of the NDRC and the first U.S. Presidential Science Advisor systematically applying science to develop advanced weapons. The U.S., alone among all the Axis powers and Allied nations, now had a science advisor who reported directly to the president and had the charter and budget to fund advanced weapon systems research — outside the confines of the Army or Navy.

NRDC was run by science administrators, who had managed university researchers as well as complex research and applied engineering projects science before. They took input from theorists, experimental physicists, and industrial contractors, and were able to weigh the advice they were receiving. They understood the risks, scale and resources needed to turn blackboard theory to deployed weapons. Equally important, they weren’t afraid to make multiple bets on a promising technology nor were they afraid to kill projects that seemed like dead ends for the war effort.

200+ contracts
Prior to mid 1940 research in U.S. universities was funded by private foundations or companies. There was no government funding. The NRDC changed that. With a budget of $10,000,000 to fund research proposed by the five section chairmen, the NDRC funded 200+ contracts for research in radar, physics, optics, chemical engineering, and atomic fission.

For the first time ever, U.S. university researchers were receiving funding from the U.S. government. (It would never stop.)

The Uranium Committee
In addition to the five NRDC divisions working on conventional weapons, the NRDC took over the moribund standalone Uranium Committee and made it a scientific advisory board reporting directly to Bush. The goal was to understand whether the theory of an atomic weapon could be turned into a practical weapon. Now the NRDC could directly fund research scientists to investigate ways to separate for U-235 to make a bomb.

What Didn’t Work at the NRDC?
After a year, it was clear to Bush that while the NDRC was funding advanced research, the military wasn’t integrating those inventions into weapons. The NRDC had no authority to build and acquire weapons. Bush decided what he needed was a way to bypass traditional Army and Navy procurement processes and get those advanced weapons built.

Read the sidebars for background.

The Office of Scientific Research and Development Stands Up
In May 1941 Bush went back to President Roosevelt, this time with a more audacious request: Turn NRDC into an organization that not only funded research but built prototypes of new advanced weapons and had the budget and authority to write contracts to industry to build these weapons at scale. In June 1941 Roosevelt agreed and signed the Executive Order creating the Office of Scientific Research and Development (OSRD). (It’s worth reading the Executive Order here to see the extraordinary authority he gave OSRD.)

OSRD expanded the National Defense Research Committee’s (NDRC) original five divisions into 19 weapons divisions, five research committees and a medical portfolio. Each division managed a broad portfolio of projects from research to production, and deployment. Its organization chart is shown below.

These divisions spearheaded the development of an impressive array of advanced weapons including radar, rockets, sonar, the proximity fuse, Napalm, the Bazooka and new drugs such as penicillin and cures for malaria.

The OSRD was a radical experiment. Instead of the military controlling weapons development Bush was now running an organization where civilian scientists designed and built advanced weapons systems. Nearly 10,000 scientists and engineers received draft deferments to work in these labs.

As a harbinger of much bigger things, the NRDC uranium committee was enlarged and renamed the S-1 Section on Uranium.

Throughout the next year the pace of atomic research picked up. And Bush’s involvement in launching the U.S. nuclear weapons program would grow larger.

By the middle of 1941 Bush was beginning to believe that building an atomic bomb was possible. But he felt he did not have enough evidence to suggest to the president that the country commit to the massive engineering effort to build the bomb.

Then the MAUD report from the British arrived.

Bush is Convinced by the MAUD Report
The MAUD Report finally pushed Bush over the edge. The British report showed how it was possible to build an atomic bomb. The fact that the British were independently saying what passionate advocates like Lawrence, Fermi, et al were saying convinced Bush that an atomic bomb program was worth investing in at the scale needed.

Bush Tells Roosevelt — We Can Build an Atomic Bomb
In October 1941, Bush told the President about the British MAUD report conclusions: the bomb’s uranium core might weigh twenty-five pounds, its explosive power might equal eighteen hundred tons of TNT, but to separate the U-235 they would need to build a massive industrial facility. The President asked Bush to work with the Army Corps of Engineers to figure out what type of plant to build, how to build it and how much would it cost.

A month later, in November 1941 the U.S. National Academy of Sciences confirmed to Bush that the British MAUD report conclusions were correct.

Bush now had all the pieces lined up to support an all-out effort to develop an atomic bomb.

December 1941 — Let’s Build an Atomic Bomb
In December 1941, the day before the Japanese attack on Pearl Harbor, the atomic bomb program was placed under Vannevar Bush. He renamed the Uranium program as the S-1 Committee of OSRD.

In addition to overseeing the 19 Divisions of OSRD, Bush’s new responsibility was to coordinate all the moving parts of the atomic bomb program — the research, the lab experiments, and now the beginning of construction contracts.

With the Presidents support, Bush reorganized the program to take it from research to a weapons program. The goal now was to find the best ways to produce uranium-235 and Plutonium in large quantities. He appointed Harold Urey at Columbia to lead the gaseous diffusion and centrifuge methods and heavy-water studies. Ernest Lawrence at Berkeley took electromagnetic and plutonium responsibilities, and Arthur Compton at Chicago ran chain reaction and weapons theory programs. This team proposed to begin building pilot plants for all five methods of separating U-235 before they were proven. Bush and Conant agreed and sent the plan to the President, Vice President, and Secretary of War, suggesting the Army Corps of Engineers build these plants.

With U.S. now at war with Germany and Japan, the race to build the bomb was on.

In January 1942, Compton made Oppenheimer responsible for fast neutron research at Berkeley. This very small part of the atomic bomb program is the first time Oppenheimer was formally engaged in atomic bomb work.

Enter the Army
The Army began attending OSRD S-1 (the Atomic Bomb group) meetings in March 1942. Bush told the President that by the summer of 1942 the Army should be authorized to build full-scale plants.

Build the U-235 Separation and Plutonium Plants
By May 1942 it was still unclear which U-235 separation method would work and what was the right way to build a nuclear reactor to make Plutonium, so the S-1 committee recommended — build all of them. Build centrifuge, electromagnetic separation, and gaseous diffusion plants as fast as possible; build a heavy water plant for the nuclear reactors as an alternative to graphite; build reactors to produce plutonium; and start planning for large-scale production and select the site(s). The S-1 Committee also recommended the Army be in charge of building the plants.

Meanwhile that same month, Oppenheimer was made the “Coordinator of Rapid Rupture.” He headed up a group of theorists working with experimentalists to calculate how many pounds of U-235 and Plutonium were needed for a bomb.

The Manhattan Engineering District — The Atomic Program Moves to the Army
In June 1942, the president approved Bush’s plan to hand building the bomb over to the Army. The Manhattan Engineering District became the new name for the U.S. atomic bomb program. General Groves was appointed its head in September 1942.

To everyone’s surprise Groves selected Oppenheimer to administer the program. It was a surprise because up until then Oppenheimer was a theoretical physicist, not an experimentalist nor had he ever run or managed any programs.

Grove and Oppenheimer decided that in addition to the massive production facilities — U-235 in Oak Ridge, TN, and Plutonium in Hanford, WA — they would need a central laboratory to design the bomb itself. This would become Los Alamos. And Oppenheimer would head that lab bringing together a diverse set of theorists, experimental physicists, explosive experts, chemistry, and metallurgists.

At its peak in mid-1944 130,000 people were working on the Manhattan Project; 5,000 of them worked at Los Alamos.

Vannevar Bush would be present at the test of the Plutonium weapon at the Trinity test site in July 1945.

The OSRD would be the organization that made the U.S. the leader in 20th century research. At the end of World War II, Bush laid out his vision for future U.S. support of research in an article called “Science the Endless Frontier.” OSRD was disbanded in 1947, but after a long debate it was resurrected in pieces. Out of it came the National Science Foundation, the National Institute of Health, the Atomic Energy Commission and ultimately NASA and DARPA — all would all spring from its roots.

50 years before it happened Bush would describe what would become the internet in a 1945 article called As We May Think.

Summary

• By the time Oppenheimer and Grove took over the Atomic Bomb program, Vannevar Bush had been running it for two years
• The U.S. atomic bomb program was the sum of multiple small decisions guided by OSRD and a Presidential science advisor — Vannevar Bush
• Bush’s organizations kick-started the program. The NDRC invested (in 2023 dollars) $10M in nuclear research, OSRD put in another $250M for nuclear experiments
• The Manhattan project would ultimately cost ~$40 billion to build the two bombs.
• As the country was in a crisis — decisions were made in days/weeks by small groups with the authority to move with speed and urgency.
• Large-scale federal funding for science research in U.S. universities started with the Office of Scientific Research and Development (OSRD) — more to come in subsequent posts

Steve Blank writes about The Secret History of Silicon Valley at www.steveblank.com.

A journey of a thousand miles begins with a single step

Lǎozi 老子

I just had lunch with Shenwei, one of my ex-students who had just taken a job in a mid-sized consulting firm. After a bit of catching up I offered he was looking a bit lost. “I just got handed a project to help our firm enter a new industry — semiconductors. They want me to map out the space so we can figure out where we can add value.

When I asked what they already knew about it, they tossed me a tall stack of industry and stock analyst reports, company names, web sites, blogs. I started reading through a bunch of it and I’m drowning in data but don’t know where to start. I feel like I don’t know a thing.”

I told Shenwei I was happy for him because he had just been handed an awesome learning opportunity — how to rapidly understand and then map any new market. He gave me a “easy for you to say” look, but before he could object I handed him a pen and a napkin and asked him to write down the names of companies and concepts he read about that have anything to do with the semiconductor business — in 30 seconds. He quickly came up with a list with 9 names/terms. (See Mapping — First Pass)

“Great, now we have a start. Now give me a few words that describe what they do, or mean, or what you don’t know about them.”

Don’t let the enormity of unknowns frighten you. Start with what you do know.

After a few minutes he came up with a napkin sketch that looked like the picture in Mapping — Second Pass.

Now we had some progress.

I pointed out he now had a starter list that not only contained companies but the beginning of a map of the relationships between those companies. And while he had a few facts, others were hypotheses and concepts. And he had a ton of unanswered questions.

We spent the next 20 minutes deconstructing that sketch and mapping out the Second Pass list as a diagram (see Mapping — Third Pass.)

As you keep reading more materials, you’ll have more questions than facts. Your goal is to first turn the questions into testable hypotheses (guesses). Then see if you can find data that turns the hypotheses into facts. For a while the questions will start accumulating faster than the facts. That’s OK.

Note that even with just the sparse set of information Shenwei had, in the bottom right-hand corner of his third mapping pass, a relationship diagram of the semiconductor industry was beginning to emerge.

Drawing a diagram of the relationships of companies in an industry can help you deeply understand how the industry works and who the key players are. Start building one immediately. As you find you can’t fill in all the relationships, the gaps outlining what you need to learn will become immediately visible.

As the information fog was beginning to lift, I could see Shenwei’s confidence returning. I pointed out that he had a real advantage that his assignment was in a known industry with lots of available information. He quickly realized that he could keep adding information to the columns in the third mapping pass as he read through the reports and web sites.

Google and Google Scholar are your best friends. As you discover new information increase your search terms.

My suggestion was to use the diagram in the third mapping pass as the beginning of a wall chart — either physically (or virtually if he could keep it in all in his head). And every time he learned more about the industry to update the relationship diagram of the industry and its segments. (When he pointed out that there were existing diagrams of the semiconductor industry he could copy, I suggested that he ignore them. The goal was for him to understand the industry well enough that he could draw his own map ab initio — from the beginning. And if he did so, he might create a much better one.)

When lunch was over Shenwei asked if it was OK if he checked in with me as he learned new things and I agreed. What he didn’t know was that this was only the first step in a ten-step industry mapping process.

Epilog

Over the next few weeks Shenwei shared what he had learned and sent me his increasingly refined and updated industry relationship map. (The 4th mapping pass showed up 48 hours later.)

In exchange I shared with him the news that he was on step one of a ten step industry mapping program. Other the next few weeks he quickly built on the industry map to answer questions 2 through 10 below.

Two weeks later he handed his leadership an industry report that covered the ten steps below and contained a sophisticated industry diagram he created from scratch. A far cry from his original napkin sketch!

Six months later his work on this project convinced his company that there was a large opportunity in the semiconductor space, and they started a new practice with him in it. His work won him the “best new employee” award.

The Ten Steps to Map any Industry

Start by continuously refining your understanding of the industry by diagramming it. List all the new words you encounter and create a glossary in your own words. Start collecting the best sources of information you’ve read.

Basic Industry Understanding

1. Diagram the industry and its segments

• Start with anything
• Build your learning by successive iteration
• Who are the key suppliers to each segment?
• How does this industry feed into the larger economy?

2. Create a glossary of industry unique terms

• Can you explain them to others? Are there analogies to other markets?

3. Who are the industry experts in each segment? For the entire industry?

• Economic experts? E.g. industry analysts, universities, think tanks
• Technology experts? E.g. universities, think tanks
• Geographic experts?

4. Key Conferences, blogs, web sites, etc.

• What are the best open source data feeds?
• What are the best paid resources?

Overlay numbers, dollars, market share, Compound Annual Growth Rate (CAGR) on all parts of the industry diagram. That will inform velocity and direction of the market.

Detailed Industry Understanding

5. Who are the market leaders? New entrants? In revenue, market share and growth rate

• In the U.S.
• Western countries
• China

6. Understand the technology flows

• Who builds on top of who
• Who is critical versus who can be substituted

7. Understand the economic flows

• Who buys from who in this industry
• Who buys the output from this industry.
• How cyclical is demand?
• What are the demand drivers?
• How do companies inside each segment get funded? Any differences in capital requirements? Ease of starting, etc.

8. If applicable, understand the personnel flow for each segment

• Do people move just between their segments or up and down through the entire industry?
• Where do they get trained?

The beginner’s forecasting method is to simply extrapolate current growth rates forward. But in today’s technology markets, discontinuities are coming fast and furious. Are there other technologies from adjacent markets will impact this one? (e.g. AI, Quantum, High performance computing,…?). Are there other global or national economic initiatives that could change the shape of the market?

Forecasting

9. What’s changed in the last 10 years? 5 years?

• Diagram the past incarnations of the industry

10. What’s going to change in the next 5 years?

• Any big insight on disruption?
• New entrants?
• New technology?
• New foreign suppliers?
• Diagram your model of the industry in 5 years

Steve Blank writes about how to build a successful company at www.steveblank.com.

This article previously appeared in The National Interest.

Last month the U.S. passed the CHIPS and Science Act, one of the first pieces of national industrial policy — government planning and intervention in a specific industry — in the last 50 years, in this case for semiconductors. After the celebratory champagne has been drunk and the confetti floats to the ground it’s helpful to put the CHIPS Act in context and understand the work that government and private capital have left to do.

Today the United States is in great power competition with China. It’s a contest over which nation’s diplomatic, information, military and economic system will lead the world in the 21st century. And the result is whether we face a Chinese dystopian future or a democratic one, where individuals and nations get to make their own choices. At the heart of this contest is leadership in emerging and disruptive technologies — running the gamut from semiconductors and supercomputers to biotech and blockchain and everything in between.

National Industrial Policy — U.S. versus China
Unlike the U.S., China manages its industrial policy via top-down 5-year plans. Their overall goal is to turn China into a technologically advanced and militarily powerful state that can challenge U.S. commercial and military leadership. Unlike the U.S., China has embraced the idea that national security is inexorably intertwined with commercial technology (semiconductors, drones, AI, machine learning, autonomy, biotech, cyber, semiconductors, quantum, high-performance computing, commercial access to space, et al.) They’ve made what they call military/civil fusion — building a dual-use ecosystem by tightly coupling their commercial technology companies with their defense ecosystem.

China has used its last three 5-year plans to invest in critical technologies (semiconductors, supercomputers, Al/ML, quantum, access to space, biotech) as a national priority. They have built a sophisticated public/private financing ecosystem to support these plans. The Chinese technology funding ecosystem includes regional investment funds that exceed 700 billion dollars (what they call their Civil/Military Guidance Funds). These are investment vehicles in which central and local government agencies make investments that are combined with private venture capital and State-Owned Enterprises in areas of strategic importance. They are tightly coupling critical civilian companies to their defense ecosystem to help them develop military weapons and strategic surprises. (Tai Ming Cheung’s book is the best description of the system.)

The U.S. has nothing comparable.

In contrast, for the last several decades, planning in the U.S. economy was left to “the market.” Driven by economic theory from the Chicago School of Economics, its premise is that free markets best allocate resources in an economy and that minimal, or even no, government intervention is best for economic prosperity. We ran our economy on this theory as a bipartisan experiment in the U.S. for the last several decades. Optimizing profit above else led to wholesale offshoring of manufacturing and entire industries in order to lower costs. Investors shifted to making massive investments in industries with the quickest and greatest returns without long-term capital investments (e.g. social media, ecommerce, gaming) instead of in hardware, semiconductors, advanced manufacturing, transportation infrastructure, etc. The result was that by default, private equity and venture capital were the de facto decision makers of U.S. industrial policy.

With the demise of the Soviet Union and the U.S. as the sole superpower, this “profits first” strategy was “good enough” as there was no other nation that could match our technical superiority. That changed when we weren’t paying attention.

China’s Ambition and Strategic Surprises
In the first two decades of the 21st century, while the U.S. was focused on combating non-nation states (ISIS, Al-Qaeda…) U.S. policymakers failed to understand China’s size, scale, ambition, and national commitment to surpass the U.S. as the global leader in technology. Not just in “a” technology but in all of those that are critical to both our national and economic security in this century.

China’s top-down national industrial policy means we are being out-planned, outmanned, and outspent. By some estimates, China could be the leader in a number of critical technology areas sooner than we think. While Chinese investment in technology at times has been redundant and wasteful, the sum of these tech investments has resulted in a series of strategic surprises to the U.S.– hypersonics, ballistic missiles with maneuverable warheads as aircraft carrier killers, fractional orbital bombardment systems, rapid advances in space, semiconductors, supercomputers, and biotech …with more surprises likely — all with the goal to gain superiority over the U.S. both commercially and militarily.

Limits and Obstacles to China’s Dominance
However, America has advantages that China lacks: capital markets that can be incented not coerced, untapped innovation talent willing to help, labor markets that can be upskilled, university and corporate research that still excels, etc. At the same time, a few cracks are showing in China’s march to technology supremacy; their detention of some of their most successful entrepreneurs and investors, a crackdown on “superfluous” tech (gaming, online tutoring) and a slowdown of listings on the China’s version of NASDAQ, the Shanghai Stock Exchange’s STAR Market — may signal that the party is reining in its “anything goes” approach to pass the U.S. Simultaneously the U.S. Commerce department has begun to prohibit export of critical equipment and components that China has needed to build their tech ecosystem.

Billionaires and Venture Capital Funding Defense Innovation
In the U.S. DoD’s traditional suppliers of defense tools, technologies, and weapons — the prime contractors and federal labs — are no longer the leaders in many of these emerging and disruptive technologies. And while the Department of Defense has world-class people and organizations it’s for a world that no longer exists. (Its inability to rapidly acquire and deploy commercial systems requires an organizational redesign on the scale of Goldwater/Nichols Act, not a reform.)

Technology innovation in many areas now falls to commercial companies. In lieu of a coherent U.S. national investment strategy across emerging and disruptive technologies (think of the CHIPS Act times ten), billionaires in the U.S. have started their own initiatives — Elon Musk — SpaceX and Starlink (reusable rockets and space-based broadband internet), Palmer Lucky — Anduril (AI and Machine Learning for defense), Peter Theil — Palantir (data analytics). And in the last few years a series of defense-focused venture funds — Shield Capital, Lux Capital, and others — have emerged.

However, depending on billionaires interested in defense is not a sustainable strategy, and venture capital invests in businesses that can become profitable in 10 years or less. This means that technologies that might take decades to mature (fusion, activities in space, new industrial processes, …) get caught up and die in a “Valley of Death.” Attempts to bridge this Valley of Death often find technology companies relying on Government capital. These programs (DIU, In-Q-Tel, AFWERX, et al), are limited in scope, time and success at scale. These government investment programs have largely failed to scale these emerging and disruptive technologies for four reasons:

• Government agencies have limited access to top investment talent to help them make sophisticated technical investment decisions
• Government agencies lack the commercialization skills to help founders turn technical ideas into commercial ventures.
• While the Dept of Defense has encouraged starting new ventures, it has failed to match it with the acquisition dollars to scale them. There’s no DoD coherent/committed strategy to create a new generation of prime contractors around these emerging and disruptive technologies.
• No private or government funds operates as “patient capital” — investing in critical deep technologies that may take more than a decade to mature and scale

America’s Frontier Fund

Today one private capital fund is attempting to solve this problem. Gilman Louie, the founder of In-Q-Tel, has started America’s Frontier Fund(AFF.) This new fund will invest in key critical deep technologies to help the U.S. keep pace with the Chinese onslaught of capital focused on this area. AFF plans to raise one billion dollars in “patient private capital” from both public and private sources and to be entirely focused on identifying critical technologies and strategic investing. Setting up their fund as a non-profit allows them to focus on long-term investments for the country, not just what’s expedient to maximize profits. It will ensure these investments grow into large commercial and dual-use companies focused on the national interest.

They’ve built an extraordinary team of experienced venture capitalists (I’ve known Gilman Louie and Steve Weinstein for decades), a world-class chief scientist, a startup incubation team, and they come with a unique and deep understanding of the intersection of national security and emerging and disruptive technologies.

AFF is the most promising effort I have seen in tackling the long-term challenges of funding and scaling emerging and disruptive technologies head-on.

At stake is whether the rest of the 21st century will be determined by an authoritarian government wiling to impose a dystopian future on the world, or free nations able to determine their own future.

These are tough problems to solve, and no single fund is can take on the massive investments China is making, but it’s possible that the AFF’s market driven approach, when combined with the government’s halting steps reengaging in industrial policy, can tip the scale back in our favor.

Here’s hoping they succeed.

Steve Blank write about defense innovation and related topics at www.steveblank.com

Charles O’Reilly and Michael Tushman coined the term an “Ambidextrous Organization” to describe how some companies get this simultaneous execution and innovation process right. Their book Lead and Disrupt describes how others can learn how to do so.

I was honored to write the forward to their second edition. Here it is in its entirety.

— -

What you’re holding in your hand is a revolutionary document. It answers the questions of why some companies trace a brilliant arc as a shooting star and then flame out while others continue to thrive. Why are some companies able to reinvent themselves while others, once market leaders, are disrupted?

Is it that some CEOs are better than others? Are their people smarter? Do they have better sales, marketing, or product development groups?

The short answer is no. What the winners start with is the realization that in a world of continuous disruption, they have only a few years to develop new capabilities or be pushed over the brink. And they also recognize that simply exploiting their existing assets, capabilities, and business models is insufficient for long-term survival. So they prepare for future markets by exploring new ventures.

This radical idea of companies continuing to execute and exploit their existing business model while simultaneously exploring and creating new products, businesses, and business models is what O’Reilly and Tushman call ambidexterity. While simple at first glance, the concept is revolutionary in its ability to transform an enterprise. This book not only explains the “why does this happen” but more importantly gives you the tools for “what to do about it.”

In the 20th century, finding the successful formula for repeatable start-up success remained a black art. The idea of exploitation versus exploration was central in my own work in building the lean methodology for start-ups. The key was the realization that start-ups are not simply smaller versions of large companies, which execute/exploit known business models, and whose customers, problems, and necessary product features are all “knowns.” In sharp contrast, start-ups operate in “search/explore” mode, seeking a repeatable and profitable business model. The search for a business model requires dramatically different rules, roadmaps, skill sets, tools, and culture in order to minimize risk and optimize chances for success.

Recognizing the anomaly was just the first step. There were no standard tools, methods, or playbooks for start-ups. So we built our own tools to enable founders to rapidly translate their vision into hypotheses and then into validated facts. These tools — Customer Development, Agile Engineering, and Business Model design — became the lean start-up methodology, a rigorous approach to testing hypotheses and building prototypes, and, on the basis of data and evidence, adjusting or pivoting to a variant of the original hypothesis. Today, lean is the de facto method for building new start-ups.

Fast forward two decades, and many companies have adopted these start-up tools and methods to deal with disruption. However, after watching innovators in large companies try to use the lean start-up methodology, I’m embarrassed to say that it has mostly devolved into standalone innovation activities (corporate incubators, accelerators, and so on) resulting in “innovation theater,” with nice coffee mugs and posters but little impact on the top or bottom line.

In this book O’Reilly and Tushman succinctly articulate why these tools succeed in start-ups but fail in large companies. Most R&D budgets in established companies are spent on sustaining innovations that support existing products and operating divisions and the attendant processes and procedures, rigorous measurement, and controls. These formalized structures, necessary for managing execution/exploitation, actually strangle disruptive innovation before it can start.

Companies built around exploitation emphasize efficiency, productivity, and the reduction of variance, whereas exploration demands searching, discovering, and accepting risk and failure. To accomplish both simultaneously — to be an ambidextrous company — requires not only separate organizations for each function, but also different business models, competencies, systems, processes, incentives, and cultures. In short, it requires a different way not only to manage a company, but a different way to organize it as well.

This is a really big idea.

To be truly successful at ambidexterity firms must master the new skills of ideation, incubation, and scaling. Firms first generate new ideas via ideation: the last twenty years have seen an explosion of corporate venture capital, open innovation, and employee involvement via hackathons and incubators. A smaller number of companies have become proficient at the next step — incubation — rigorously testing new business concepts, using the lean start-up methods of Customer Development, Agile Engineering, and Business Model design. However, relatively few have successfully scaled new internal ventures to enable them to stay ahead of disruption. It is this discipline of scaling, actually building new, substantive, profitable businesses, that is critical to the success of new, highly innovative corporate ventures. It’s only when companies can scale that they truly win. Scaling is the crux of ambidexterity.

Recognizing the need for ambidexterity and building an ambidextrous organization are tests of corporate leadership.

In the end, exploitation pays your salary while exploration pays your pension. Companies that survive do both.

This book will do for companies what the lean methodology did for start-ups — give its leaders the essential playbook for transforming their organizations to meet the future.

Get your copy of Lead and Disrupt.

Steve Blank writes about disruptive innovation at www.steveblank.com

The award was for an entrepreneur who worked against all odds to buck the system to turn her insight into an application. She had realized it was possible to automate a process that was being done manually — reentering data from one spreadsheet to another and annotating it with additional data from another system. Inspired by her own work problem, she talked to her peers and other stakeholders, built multiple minimum viable products, and figured out how to get engineering, policy, legal, security and everyone else in the enterprise to actually approve it. And then she fought with the acquisition folks to buy the trivial amount of additional hardware needed to connect it. It was a development process that would’ve taken three weeks in a startup, but inside this agency took 10 months (which was considered fast.) At each step she was confronted with “we’re not budgeted for this” or “this isn’t on our schedule” and “this isn’t your job.” Most rational people would’ve given up and said “you can’t fight the system“ but yet she persisted.

Having seen this scenario play out multiple times at multiple large corporations and government agencies, I could’ve repeated the speech her agency director made at the ceremony verbatim. “Blah blah blah and a $100 bonus.” Everyone politely applauded and went back to work feeling good. I was simply depressed. Never once did anyone ever step back and say that what we just witnessed was leadership rewarding and perpetuating a dysfunctional and broken system.

I’m constantly puzzled why thoughtful and astute CEOs and Agency Directors never ask, “Why is it that innovations require heroics to occur in our organization? Why don’t we have a repeatable process for innovation? What are the obstacles in the way of delivering needed innovation with speed and urgency in our organization? Why is it that after each one of these awards we don’t go back and fix the parts of the system that made creating something new so difficult?”

Instead, everyone at this award ceremony just went back to work like it was business as usual. I realized that innovation in this organization was going to continue to happen by heroics and exception rather than by design. As I’ve seen play out way too many times, ultimately the innovators get tired of banging their heads against the wall and leave government service or large companies. Their organizations hemorrhage the very people they need to help them compete against aggressive adversaries or competitors who have them in their sights.

An Organizational Design Problem

Sadly, this wasn’t a single act of bad management or malice. No single individual thought they weren’t doing their job. However, if anyone had taken the time to deconstruct the reason for the roadblocks to innovation, they would have uncovered they weren’t just obstinate middle managers, or a single bad process. Asking a series of “five whys,” (see this HBR article) would have discovered that:

1. The agency’s existing processes were not designed for non-standard work. As in most large organizations, they were designed for the repeatable execution of pre-defined tasks.
2. There were no resources available for non-standard work or any parallel organization responsible for innovation.
3. The culture of the organization discouraged experimentation and punished the inevitable failures of a learning and discovery process.

Ultimately, the root cause was the entire government agency lacked an Innovation Doctrine. This manifested itself as an organizational design problem. There was simply no permanent place in the organization for unscheduled innovation to happen. And even if there had been, there was no way to turn demos into deployment with speed and at scale.

Innovation Doctrine

In peacetime and/or when you’re the dominant superpower (or a commercial market leader), the emphasis is on process, procedures, and sustainment of existing systems. Deviations from that create chaos and diverge from the predetermined are not welcomed, let alone promoted, and funded. They are eliminated. This works great when the external environment -competitors, adversaries, technologies, threats — is static. However in times of crisis, war or disruption, these unconventional thinkers and innovators are exactly what is needed, and their ideas need to be rapidly deployed.

Well-managed organizations realize that they need both innovation and execution. With execution being dominant in peacetime/competitive advantage you have managers of process. In crisis/wartime innovation is dominant. Instead of mangers of process you need innovation leaders who shepherd ideas through an innovation pipeline. (see this HBR article.) Successful organizations recognize that innovation isn’t a single activity (incubators, accelerators, hackathons); it is a strategically organized end-to-end process from idea to deployment.

While innovation and execution have different processes, people, and culture, they need to respect and depend on each other. This ambidexterity (see this HBR article) and the innovation processes that go with it require an innovation doctrine — and overall strategy and playbook for the entire organization and enterprise that includes an innovation pipeline and processes intended to drive innovation efforts, and describes the role of innovation leaders in an ambidextrous organization — all focused on rapid deployment of new capabilities.

Lessons Learned

• Innovation heroics are a symptom of a lack of an innovation doctrine
• An innovation doctrine has a playbook, and innovation pipeline and describes the role of innovation leaders in an ambidextrous organization — all focused on rapid deployment of new capabilities
• All large organizations — both government and corporate — need an innovation doctrine or else risk being outpaced by competitors.

Steve Blank writes about disruptive innovation at www.steveblank.com.

This article first appeared in Poets and Quants

Revolutions start by overturning the status quo. By the end of the 20th century, case studies and business plans had reached an evolutionary dead-end for entrepreneurs. Here’s why and what we did about it.

The Rise of Business Schools — Management as an Occupation
The business school was invented in the first decade of the 20th century in response to a massive economic transformation in the U.S. that took place in the last quarter of the 19th century. The country exited the Civil War as a nation of small businesses and ended the century with large national corporations (railroads, steel, oil, food, insurance, etc.). These explosions in company size and scale created a demand for professional managers. In 1908 Harvard Business School filled that need by creating a graduate degree — the Master of Business Administration. Its purpose was to educate management on best practices to run existing companies.

The MBA Curriculum — From Fieldwork to Case Studies
When Harvard started the MBA program there were no graduate-level business textbooks. The school used the “problem-method” which emphasized fieldwork — getting out of the classroom and visiting real companies– as an important part of the curriculum. Students observed how executives worked, interviewed them, and wrote up how real managers solved problems. Students then discussed these problems and solutions in class.

By the early 1920s a new dean changed the curriculum — shifting it from an industry orientation (steel, railroads, etc.) — to a functional one (marketing, factory and employment management (HR), etc.). This focus on a functional curriculum involved a switch to the case method; fieldwork now took second place. The case method assumes that students learn when they participate in a discussion of a theoretical situation they may face when they are a decision-maker rather than a real one they see in the field.

By 1923, 2/3rds of the courses at Harvard were taught with the case method, and the pattern was set for business education for the rest of the 20th century.

Entrepreneurship Becomes a Subject in Business Schools

While MBA programs proliferated during the first half of the 20th century, they focused on teaching management of existing companies. There were no classes on how to start a business. That is until 1947 when Myles Mace taught the first entrepreneurship course “Management of New Enterprises” at Harvard Business School. Soon others were created. In 1953 Peter Drucker offered an Entrepreneurship and Innovation class at New York University, and in 1954 Stanford’s business school offered “Small Business Management” its first small business course.

In 1967 the first contemporary MBA entrepreneurship courses were introduced at Stanford and NYU, and a year later Babson offered the first undergraduate entrepreneurship program. By 1970 sixteen schools were offering entrepreneurship courses, and in 1971 UCLA offered the first MBA in entrepreneurship. Entrepreneurship textbooks such as Small Business Management: Essentials of Entrepreneurship and Entrepreneurship: Playing to Win started to appear. In 1985 the University of Miami held the first national business plan competition. By 1991 there were 57 undergraduate and 22 MBA programs. Textbooks, papers, and journal articles proliferated.

By the end of the 20th century entrepreneurship education fell into two categories: 1) starting small businesses and 2) starting high-growth, high-risk scalable startups. But both types of entrepreneurship courses were taught using case studies and taught students how to write and execute a business plan. The curriculum of both types of courses were simply adaptations of what business schools were using to train managers for the administration and execution of existing organizations.

The case method and business plans are the antithesis of how entrepreneurs create startups

The case method assumes that students learn when they participate in a discussion of a situation they may someday face as a decision-maker. But the case method is the antithesis of how entrepreneurs create a startup. Cases teaches pattern recognition tools for static patterns — and has limited value as a tool for teaching entrepreneurship. Analyzing a case in the classroom, removed from the realities of a new venture, adds little to an entrepreneur’s preparation for the chaos, uncertainty, and conflicting customer responses that all entrepreneurs face.

Business plans presume that building a startup is a series of predictable steps requiring execution of a plan which assumes a series of known facts: known customers, known features, known pricing, known distribution channel. As a serial entrepreneur turned educator, this didn’t make sense to me. In a new venture none of these things are truly known. The reality is that most business plans don’t survive first contact with customers.

Neither cases nor business plans replicate the actual startup experience. Cases and plans are useful for teaching managers of process, not founders. Founders of startups (and new ventures inside existing companies) are searching for product/market fit and a repeatable and scalable business model. Searching, unlike execution, is not a predictable pattern. An entrepreneur must start with the belief that all their assumptions are simply hypotheses that will undoubtedly be challenged by what they learn from customers.

Yet up until 10 years ago, schools were still teaching entrepreneurs how to build startups on the premise that they were simply smaller versions of large companies. Entrepreneurial education was trapped in the 20th century.

21st Century Entrepreneurship curriculums

At the start of the 21st century, after two decades and 8 startups, I retired and had time to think about how VCs directed their startups using business plans. I began formulating the key ideas around what became the Lean Startup — that startups and existing companies were distinctly different — companies execute business models while startups search for them. Consequently the methodologies for launching products in startups were different than for existing companies.

A decade later, I began to teach the foundations of Lean, first at UC Berkeley (Customer Development) and then at Stanford using cases and business plans. After a few years of trial and error in front of a lot of students, I realized that the replacement for the case method was not better cases written for startups and that the replacement for business plans was not how to write better business plans and pitch decks. (I did both!). Instead, we needed a new management stack for company creation.

I posited that teaching “how to write a business plan” might be obsolete.

With Lean LaunchPad, we were going to toss teaching the business plan aside and try to teach students a completely new, hands-on approach to starting companies — one which combines customer development, agile development, business models and pivots.

Let’s Teach Lean Via Experiential Learning

First I searched the academic literature trying to learn what methods would best convey information that entrepreneurship students could understand, retain, and put to practical use. There were five parts to consider:

• What’s the level of ambiguity, realism and complexity of the course content
• How structured are the tasks within the class?
• What were the experiential techniques used to deliver the content?
• What were the pedagogical components of the class?
• How will we deliver feedback to the students?

For each of these parts of the course design we needed to consider where on the spectrum of directed versus experiential each of the five parts of the class would fall.

Direct Guidance Versus Experiential Classes

I concluded that best way to teach entrepreneurs (versus managers) was to create an experiential and inquiry-based class that would develop the mindset, reflexes, agility, and resilience needed to search for a business model certainty in a chaotic world.

Experiential learning (also called “active learning” or “learning by doing”) is designed to have a high degree of complexity and realism. It’s not about read and remember, but rather is about problem exploration, design and inventing and iterating solutions. This differs from a traditional class with directed learning where students are taught to remember facts, understand concepts, and perhaps apply procedures but not to discover these by themselves.

In contrast, experiential classes are designed with the theory that people learn best in an unguided or minimally guided environment, where the students, rather than being presented with all of the essential information, must discover, or construct that information rapidly for themselves.

This seemed to me to be the best way to teach entrepreneurship. Experiential learning is the core of how we teach the Lean LaunchPad/I-Corps/Hacking for X classes. Launched in 2011, the Lean LaunchPad capstone entrepreneurship class was unique in that it was:

1. team-based
2. experiential
3. Lean-driven (hypothesis testing/business model/customer development/agile engineering).

The class aimed to mimic the uncertainty all startups face as they search for a business model while imparting an understanding of all the components of a business model, not just how to give a pitch or a demo.

The figure below illustrates the spectrum of teaching techniques and shows where our class fits on the right.

The Syllabus

We were going to teach entrepreneurship like you teach artists — combining theory with intensive hands-on practice.

This Lean LaunchPad is built around the business model / customer development / agile development solution stack. Students start by mapping their initial assumptions (their business model). Each week they test these hypotheses with customers and partners outside the classroom (using customer development), then use iterative and incremental development (agile development) to build Minimal Viable Products.

The goal is to get students out of the building to test each of the 9 parts of their business model (or mission model for Hacking for Defense students), understand which of their assumptions were wrong, and figure out what they need to do to find product/market fit and then a validated business model.

Our objective is to get them using the tools that help startups test their hypotheses and adjust when they learn that their original assumptions are wrong. We want them to experience faulty assumptions not as a crisis, but as a learning event called a pivot — an opportunity to change the model. (More than just for use in startups, these problem-solving skills are increasingly crucial in today’s increasingly complex world.)

Each week every team presents to the teaching team — “Here’s what we thought, here’s what we did, here’s what we learned, here’s what we’re going to do next week.”

Designing the Lean LaunchPad/I-Corps Class — the “Pedagogy”

While the Lean LaunchPad/I-Corps/H4X students are experiencing what appears to them to be a fully hands-on, experiential class, it’s a carefully designed illusion. In fact, it’s highly structured. The syllabus has been designed so that we are offering continual implicit guidance, structure, and repetition. This is a critical distinction between our class and an open-ended experiential class.

Guidance, Direction and Structure

For example, students start the class with their own initial guidance — they believe they have an idea for a product or service (Lean LaunchPad/I-Corps) or have been given a clear real-world problem (Hacking for Defense). Coming into the class, students believe their goal is to validate their commercialization or deployment hypotheses. (The teaching team knows that over the course of the class, students will discover that most of their initial hypotheses are incorrect.)

Next, the business/mission model canvas offers students guidance, explicit direction, and structure. First, the canvas offers a complete, visual roadmap of all the hypotheses they will need to test over the entire class. Second, the canvas helps the students goal-seek, by visualizing what an optimal endpoint would look like — product/market fit / mission success — would look like. Finally, the canvas provides students with a map of they what they learn week-to-week through their customer discovery work.

(I can’t overemphasize the important role of the canvas. Unlike an incubator or accelerator with no frame, the canvas acts as the connective tissue — the frame — that students can fall back on when they got lost or confused. It allows us to teach the theory of how to turn an idea, need, or problem into commercial practice, week by week a piece at a time.)

Third, the tools for customer discovery (videos, sample experiments, etc.) offer guidance and structure for students to work outside the classroom. The explicit goal of 10–15 customer interviews a week along with the requirement for building a continual series of minimal viable products, provides metrics that track the team’s progress. The mandatory office hours with the instructors and support from mentors provide additional guidance and structure.

Working Memory and Reflection

One of the challenges we wanted to avoid is overloading students’ short-term memory. If you give students minimal feedback and provide no structure or guidance, most of what students experience gets forgotten. To counter that, we’ve built three techniques in to reduce the cognitive load: regular summing up, repetition, and reflection. This allows students to transfer their weekly experiences into long-term memory and knowledge.

By design, each week we make students stop, reflect, and summarize their learning (here’s what we thought, here’s what we did, here’s what we found and here’s what we’re going to do next week.) The teams present these reflections, along with required specific deliverables for each week. These weekly presentations also provide reinforcement — students need to remember their learning from each of the prior components in the business/mission model canvas to provide a context for the current week.

In addition to the week-to-week summaries, we give students a reflection week at the end of the class to synthesize, process and integrate those week-to-week learnings. And we teach them how to turn that learning into a compelling story of their learning journey.

Ambiguity, Realism and Complexity

Ambiguity in a class means the subject can have multiple right answers. Or even no right answer. Searching for answers to the business and mission problems i.e. product/market fit has maximum ambiguity — there isn’t always a correct answer, nor will the same path get you to the same answer in different circumstances.

Realism in a class means, how well does the class content match an actual problem in practice? Learning accounting in a classroom is likely similar to doing accounting in an office. However, reading case studies about startup problems in a classroom has little connection to the real world and has low realism.

Complexity refers to the number of things that can change that may affect the outcome of a decision. As the number of things that change goes up the so does the complexity of the learning process.

New ventures are ambiguous, real and complex. Teaching “how to write a business plan” as a method to build a startup assumes low ambiguity, low realism, and low complexity when the opposite is true. So we structured the class to model a startup; extremely ambiguous with multiple possible answers (or at times none,) realism in the pressures, chaos and uncertainty of a startup, and complex in trying to understand all parts of a business model.

The Flipped Classroom

Inside the classroom, we deliberately trade off lecture time for student/teaching team interaction. The class is run using a “flipped classroom.” Instead of lecturing about the basics during class time, we assign the core lectures, recorded as video clips, as homework.

Instructors then supplement the video lectures with their own in-class short lecture about this week’s business model topic. This allows instructors to use the class time for review of the concepts or short lectures customized for specific domains (e.g., hardware, life sciences, etc.).

Emotional Investment

In an experiential class students must be fully immersed in the experience, not just doing what the syllabus says is required of them. Project-based learning engages and motivates students Having each team present weekly in front of their peers raises the commitment (and heart rate) of the students. No one wants to be shown up by another team.

Speed and Tempo Outside Their Comfort Zones

One of the goals of the class is to talk to 100 customers and partners. That may seem like an absurdly unreasonable goal, yet all teams manage to do so. Most case-based or project classes do not offer time and resource constraints. Our class is purposely designed to offer maximum ambiguity while pushing students to achieve extraordinary results under relentless pressure and time constraints. We stress a relentless speed and tempo because we believe that learning is enhanced when students are given the opportunity to operate outside of their own perceived comfort zones.

Our objective is to have students experience what it’s like to operate in a real-world startup. Outside the classroom walls conditions will change so rapidly that their originally well thought out plans become irrelevant. If they can’t manage chaos and uncertainty, if they can’t bias themselves for action, and if they wait around for someone else to tell them what to do, then their investors and competitors will make their decisions for them and they will run out of money and their company will die.

Therefore, every successful founder needs a decisive mindset that can quickly separate the crucial from the irrelevant, synthesize the output, and use this intelligence to create islands of order in the all-out chaos of a startup. The class is designed to emulate that chaos and teach a bias for action.

Relentlessly Direct Feedback

There’s one last part of our pedagogy that might seem out of place in an experiential class — and that’s the relentlessly direct model of feedback.

The class moves at breakneck speed and is designed to create immediate action in time-, resource-, and cash-constrained environments. The teaching team practices Radical Candor — caring personally while challenging directly. At its core, Radical Candor is guidance and feedback that’s both kind and clear, specific, and sincere, and focused on helping the other person grow.

We give the students public feedback about the quality and quantity of their work in front of their peers weekly. For some, it’s the first time they’ve ever heard “not good enough.”

Class Design — Summary

The design of the class was a balance between ambiguity, complexity and uncertainty with structure and learning strategies.

While this process is extremely effective, it can be painful to watch. Our natural inclination (at least mine) is to offer specific guidance and solutions. (There are a few times in class when the team may need explicit directions such as, “It’s time to pivot” or “Your team needs to restart.” But these should be exceptions.)

The genius of the class design was making the class look like it wasn’t designed.

Results

In the first decade of the Lean LaunchPad class we’ve trained hundreds of other educators around the world to teach the class at their universities. By now 100s of thousands of students have taken some form of the class, and 100’s of companies have been created.

In addition, two government-funded programs have adopted the class at scale. The first was the National Science Foundation I-Corps. Errol Arkilic the then head of commercialization at the National Science adopted the class saying, “You’ve developed the scientific method for startups, using the Business Model Canvas as the laboratory notebook.” I-Corps which is now offered in 100 universities and has trained ~2,500 teams/7,500 scientists in 100 cohorts. The National Institute of Health also teaches a version, I-Corps @ NIH, in the National Cancer Institute.

Today, this Lean LaunchPad/I-Corps syllabus is also the basis for a series of Mission-Driven Entrepreneurship classes– Hacking for Diplomacy, Defense, Oceans, non-profits and cities. Hacking for Defense is now taught in over 55 universities in the U.S., with versions of the course offered in the UK and Australia.

While the Lean LaunchPad/I-Corps curriculum was a revolutionary break with the past, it’s not the end. In the last decade enumerable variants have emerged. The class we teach at Stanford has continued to evolve. Better versions from others will appear. And one day another revolutionary break will take us to the next level.

Steve Blank writes about teaching entrepreneurship at www.steveblank.com

We just finished the 11th annual Lean LaunchPad class at Stanford — our first version focused on deep science and technology.

I’ve always thought of the class as a minimal viable product — testing new ideas and changing the class as we learn. This year was no exception as we made some major changes, all of which we are going to keep going forward.

1. A focus on scientists and engineers. We created an additional Spring section of the class with a focus on commercializing inventions from Stanford’s scientists and engineers. The existing winter quarter of the class remains the same as we taught for the last 10 years — taking all students’ projects — e-commerce, social media, web, and mobile apps. This newly created Spring section focuses on scientists and engineers who want to learn how to commercialize deep science and technology — life sciences (medical devices, diagnostics, digital health, therapeutics,) semiconductors, health care, sensors, materials, artificial intelligence/deep learning, et al.
This allowed us to emphasize how to differentiate a technical spec from a value proposition and expand on the parts of the business model that are unique for science and engineering startups. For example, life sciences versus commercial applications have radically different reimbursement, regulatory, clinical trials, scientific advisory boards, demand creation, etc. In addition, we found we needed to add new material on Intellectual Property, how to license inventions from the university, and discussions about team dynamics. Going forward we’ll continue to offer the class in two sections with the second class focused on science and technology.

2. Remote Discovery — As the pandemic forced teaching remotely, we’ve learned that customer discovery is actually more efficient using video conferencing. It increased the number of interviews the students were able to do each week. When Covid restrictions are over, we plan to add remote customer discovery to the students’ toolkit. It remains to be seen whether customers will remain as available on Zoom as they were during the pandemic. (See here for an extended discussion of remote customer discovery.) Remote discovery also allowed a bigger pool of potential interviews not bounded by geography. The quality of interviewees seemed to improve by this larger pool.

3. Class size/configuration — For the past decade our class size was 8 teams of 4. This year we accepted 12 teams of 4. Previously all teams needed to sit through all 8 weekly presentations. That was tough in person and not sustainable via Zoom. This year, by moving into two breakout sections, we cut the number of presentations that each team sat through by half. The new format allowed students and teaching staff to devote greater attention to each presentation.

4. Adopt a team — in past years all instructors had office hours with all the teams. This year each instructor adopted three teams and saw them weekly for a half hour. Students really appreciated building a closer working relationship with one faculty member.

5. Alumni as guest speakers — Most weeks we invited a past student to guest speak about their journey through the class, highlighting “what I wish I knew” and “what to pay attention to.”

Below are the Lessons Learned presentations from the Lean LaunchPad for deep science and technology, as well as additional learnings from the class.

During the quarter the teams spoke to 1,237 potential customers, beneficiaries, regulators — all via Zoom. Most students spent 15–20 hours a week on the class, about double that of a normal class.

Team Gloflow

Started on Week 1 as a pathology slide digitization service.
Ended in Week 10 as response prediction for cancer treatments.

If you can’t see the Gloflow video, click here

If you can’t see the Gloflow slides, click here

Team Loomia

Started on Week 1 as flexible e-textile circuit looking for a problem.
Ended in Week 10 as easy-to-integrate components for automotive suppliers.

If you can’t see the Loomia video, click here

If you can’t see the Loomia slides, click here

Team Skywalk

Started on Week 1 as wearable gesture control device for real and virtual worlds.
Ended in Week 10 as a future-proof gesture control solution for AR headsets and the Department of Defense.

If you can’t see the Skywalk video, click here

If you can’t see the Skywalk slides, click here

Team EdgeAI

Started on Week 1 as a custom silicon chip with embedded memories and a Machine Learning accelerator targeting low-power, high-throughput, and low-latency applications.
Ended in Week 10 as a chip enabling AI vision applications on next generation battery powered surveillance cameras.

If you can’t see the EdgeAI video click here

If you can’t see the EdgeAI slides, click here

Team MushroomX

Started on Week 1 as Drone pollination of crops.
Ended in Week 10 as autonomous button mushroom harvesting.

If you can’t see the MushroomX video, see here

If you can’t see the MushroomX slides, click here

Team RVEX

Started on Week 1 as a Biomimetic Sleeve as a Left Ventricular Assist Device.
Ended in Week 10 as a Platform technology as a right heart failure device.

If you can’t see the RVEX video, click here

If you can’t see the RVEX slides, click here

Team Pause

Started on Week 1 as a Menopause digital health platform that connects women to providers and other women.
Ended in Week 10 as a D2C Menopause symptom tracking app and on-demand telehealth platform that offers women a personalized and integrative approach to menopause care.

If you can’t see the Pause video, click here

If you can’t see the Pause slides, click here

Team Celsius

Started on Week 1 as an IOT hardware sensor for environmental quality and human presence.
Ended in Week 10 as hybrid work collaboration + employee engagement.

If you can’t see the Celsius video, click here

If you can’t see the Celsius slides, click here

Team TakeCare

Started on Week 1 as a platform for finding and managing at-home senior care.
Ended in Week 10 as a B2C platform for scheduling on-demand at-home senior care.

If you can’t see the TakeCare video, click here

If you can’t see the Take Care slides, click here

Team CareMatch

Started on Week 1 as AI to Match Patients to Post-Acute Care.
Ended in Week 10 as Skilled Nursing Facility-at-Home for Wound Care.

If you can’t see the CareMatch video, click here

If you can’t see the CareMatch slides, click here

Team NeuroDB

Started on Week 1 as Unstructured data Tableau-like tool.
Ended in Week 10 as Cloud-based Pandas dataframe.

If you can’t see the NeuroDB video click here

If you can’t see the NeuroDB slides, click here

Team Drova

Started on Week 1 as a provider for autonomous drone delivery for restaurants and grocery stores.
Ended in Week 10 as Fleet management software for autonomous drone delivery.

If you can’t see the Drova video click here

If you can’t see the Drova slides, click here

Student Comments
I normally don’t include student comments in these summaries, but this year’s summarized why — after a decade — we still teach the class. The students find the class hard and exhausting, and say their instructors are tough and demanding. Yet in the end, the class and the work they invest in is highly rewarding to them.

• “Awesome course- one of the best I’ve taken so far. You get out what you put into it, but find a team you like working with, get ready to hustle and work hard, and trust the process. A must-take for entrepreneurs!”
• “Absolutely crucial to starting a company for a first-time founder. Couldn’t imagine a better teaching team or learning environment.”
• “Very worth taking, whether you want to do a start-up your own or not.”
• “Recommend to everyone considering entrepreneurship or want to learn about it.”
• “Great class if you are interested in learning about the Customer Discovery Model, but takes a lot of time and work.”
• “Intense course where you learn through experience on how to build a startup. I came with a product and I learned to find a solution and how to build from there.”
• “Incredible experience — really glad I took the class and happy with the outcome.”
• “Steve Blank tells you your slides are ugly”
• “Take this course if you get a chance, especially if you are a PhD student. Super useful and a different kind of learning than most case-based classes. Extremely experiential.”
• “A great class to learn about customer discovery and entrepreneurship methodologies! The teaching team is incredibly experienced and very honest in their feedback. It is quite time intensive and heavily based on your team. Make sure to clarify expectations with your team beforehand and communicate.”
• “Definitely recommend this course, it’s a great experience and will give you tools to launch your idea.”
• “A really excellent course to take to learn about entrepreneurship! An invaluable opportunity you might not find anywhere else. The instructors are extremely knowledgeable veteran entrepreneurs who give all the support and encouragement needed.”

Diversity
In past years, the students in the class were mostly men, reflecting the makeup of the applicants. While Ann Miura-Ko was part of the original teaching team, having all male instructors for the last five years didn’t help. Mar Hershenson joined the teaching team in 2018 and made an all-out effort to recruit women to apply. In this new Spring section of the class Heidi Roizen and Jennifer Carolan joined us as instructors. Mar, Heidi and Jennifer are all successful VC’s. They sponsored lunch sessions, mixers and meetings with women entrepreneurs and alumni for female students interested in the class and for male students looking to work with a more diverse team. I am happy to report that as a result of many people’s hard work the gender balance in the class substantially changed. Our Spring cohort focused on deep science and tech had 51 students — 25 were women.

The lessons for me were: 1) the class had been unintentionally signaling a “boys-only” environment, 2) these unconscious biases were easily dismissed by assuming that the class makeup simply reflected the applicant pipeline, and 3) when in fact it required active outreach by a woman to change that perception and bring more women into the pipeline and teams.

Teaching Assistants (TAs)
Our Teaching Assistants keep all the moving parts of the class running. This year their job was even more challenging running the class virtually and they made it run like clockwork.

Each year’s TAs have continued to make the class better (although I must admit it was interesting to watch the TAs remove any student uncertainty about what they need to do week-to-week by moving to a more prescriptive syllabus. Originally, I had designed a level of uncertainty into the class to mimic what a real-world startup feel like.) However, the art of teaching this class is remembering that it wasn’t designed by a focus group.

A Great Class Endures Beyond Its Author
I’ve always believed that great classes continue to thrive after the original teachers have moved on. While I created the Lean LaunchPad methodology and pedagogy (how to teach the class), over the past decade the Stanford class has had ten additional instructors, thirty-three wonderful TA’s and ninety volunteer mentors.

In addition to myself the teaching team has been:

2011 Instructors: Ann Miura-ko, Jon Feiber
Lead TA: Thomas Haymore, TA’s: Felix Huber, Christina Cacioppo

2012 Instructors: Ann Miura-ko, Jon Feiber
Lead TA: Thomas Haymore, TA:, Stephanie Glass

2013 Instructors: Ann Miura-ko, Jon Feiber
Lead TA: Rick Barber, TA: Stephanie Glass

2014 Instructors: Jeff Epstein, Jim Hornthal
Lead TA: Soumya Mohan, TA: Stephanie Zhan, Asst: Gabriel Garza, Jennifer Tsau

2015 Instructors: Jeff Epstein, Steve Weinstein
TA’s: Stephanie Zhan, Gabriel Garza TAs: Jennifer Tsau, Akaash Nanda, Asst: Nick Hershey

2016 Instructors: Jeff Epstein, Steve Weinstein
Lead TA: Jose Ignacio del Villar TA’s: Akaash Nanda, Nick Hershey, Zabreen Khan, Asst: Eric Peter

2017 Instructors: Jeff Epstein, Steve Weinstein
Lead TA: Eric Peter TA’s: Nick Hershey, Lorel Sim Karan Singhal Asst: Jenny Xia

2018 Instructors: Jeff Epstein, Steve Weinstein, Mar Hershenson, George John
Lead TA: Jenny Xia TA’s: Anand Upender, Marco Lorenzon, Lorel Sim Asst: Parker Ence, Trent Hazy, Sigalit Perelson

2019 Instructors: Jeff Epstein, Steve Weinstein, Mar Hershenson, George John, Tom Bedecarre
Lead TA: Parker Ence, Trent Hazy TA’s: Marco Lorenzon, Sigalit Perelson, Lorel Sim Asst:, Ashley Wu

2020 Instructors: Jeff Epstein, Steve Weinstein, Mar Hershenson, George John, Tom Bedecarre
Lead TA: Marco Lorenzon, Ashley Wu TA’s: Sigalit Perelson, Gopal Raman

2021 — Winter Instructors: Jeff Epstein, Mar Hershenson, George John, Tom Bedecarre
Lead TA: Erica Meehan, Anand Lalwani, TA’s: Gopal Raman, Andrew Hojel

2021 — Spring Instructors: Steve Weinstein, Heidi Roizen, Jennifer Carolan, Tom Bedecarre
Lead TAs: Sandra Ha, Lorenz Pallhuber TA: Manan Rai

Our Decade of Mentors
The mentors (industry experts) who volunteer their time have been supported and coordinated by Tom Bedecarre and Todd Basche. Each mentor’s contribution gets graded by the student team they coached.

Bryan Stolle, Charles Hudson, Dan Martell, David Feinlab, David Stewart, Doug Camplejohn, Eric Carr, George Zachary, Gina Bianchini, Heiko Hubertz, Hiten Shah, Jason Davies, Jim Greer, Jim Smith, Jonathan Ebinger, Josh Schwarzapel, Joshua Reeves, Justin Schaffer, Karen Richardson, Marianne Wu, Masheesh Jain, Ravi Belani, Rowan Chapman, Shawn Carolan, Steve Turner, Sven Strohbad, Thomas Hessler, Will Harvey, Ashton Udall, Ethan Bloch, Jonathan Abrams, Nick O’Connor, Pete Vlastellica, Steve Weinstein, Adi Bittan, Alan Chiu, George Zachary, Jeff Epstein, Kat Barr, Konstantin Guericke, Michael Borrus, Scott Harley, Jorge Heraud, Bob Garrow, Eyal Shavit, Ethan Kurzweil, Jim Anderson, George John, Dan Manian, Lee Redden, Steve King, Sunil Nagaraj, Evan Rapoport, Haydi Danielson, Nicholas O’Connor, Jake Seid, Tom Bedecarre, Lucy Lu, Adam Smith, Justin Wickett, Allan May, Craig Seidel, Rafi Holtzman, Roger Ross, Danielle Fong, Mar Hershenson, Heather Richman, Jim Cai, Siqi Mou, Vera Kenehan, Phil Dillard, Susan Golden, Todd Basche, Robert Locke, Maria Amundson, Freddy Dopfel, Don Peppers, Rekha Pai, Radhika Malpani, Michael Heinrich, MariaLena Popo, Jordan Segall, Mike Dorsey, Katie Connor, Anmol Madan, Kira Makagon, Andrew Westergren, Wendy Tsu, Teresa Briggs, Pradeep Jotwani.

And thanks to the continued support of Tom Byers, Tina Seelig, Kathy Eisenhardt, Ritta Katilla, Bob Sutton and Chuck Eesly at Stanford Technology Ventures Program (the entrepreneurship center in the Stanford Engineering School).

Steve Blank writes about teaching entrepreneurship at www.steveblank.com.

What a year. With the pandemic winding down it finally feels like the beginning of the end.

This was my sixth time teaching a virtual class during the lockdown — and for our students likely their 15th or more. Hacking for Defense has teams of students working to understand and solve national security problems. Although the class was run completely online, and even though they were suffering from Zoom fatigue, the 10 teams of 42 students collectively interviewed 1,142 beneficiaries, stakeholders, requirements writers, program managers, industry partners, etc. — while simultaneously building a series of minimal viable products.

At the end of the quarter, each of the teams gave a final “Lessons Learned” presentation. Unlike traditional demo days or Shark Tanks which are, “Here’s how smart I am, and isn’t this a great product, please give me money,” a Lessons Learned presentation tells the story of a team’s 10-week journey and hard-won learning and discovery. For all of them it’s a roller coaster narrative describing what happens when you discover that everything you thought you knew on day one was wrong and how they eventually got it right.

Here’s how they did it and what they delivered.

How Do You Get Out of the Building When You Can’t Get Out of the Building?
This class is built on conducting in-person of interviews with customers/ beneficiaries and stakeholders, but due to the pandemic, teams now had to do all their customer discovery via a computer screen. This would seem to be a fatal stake through the heart of the class. How would customer interviews work via video? After teaching remotely for the last year, we’ve learned that customer discovery is actually more efficient using video conferencing. It increased the number of interviews the students were able to do each week.

Many of the people the students needed to talk to were sheltering at home, which meant they weren’t surrounded by gatekeepers. While the students missed gaining the context of standing on a navy ship or visiting a drone control station or watching someone try their app or hardware, the teaching team’s assessment was that remote interviews were more than an adequate substitute. When Covid restrictions are over, we plan to add remote customer discovery to the students’ toolkit. (See here for an extended discussion of remote customer discovery.)

We Changed The Class Format
While teaching remotely we made two major changes to the class. Previously, each of the teams presented a weekly ten-minute summary consisting of “here’s what we thought, here’s what we did, here’s what we found, here’s what we’re going to do next week.” While we kept that cadence, it was too exhausting for all the other teams to stare at their screen watching every other team present. So we split the weekly student presentations into thirds — three teams presented to the entire class then three teams each went into two Zoom breakout rooms. During the quarter we rotated the teams and instructors through the main room and breakout sessions.

The second change was the addition of alumni guest speakers — students who had taken the class in the past. They offered insights about what they got right and wrong and what they wished they had known.

Lessons Learned Presentation Format
For the final Lessons Learned presentation many of the eight teams presented a 2-minute video to provide context about their problem. This was followed by an 8-minute slide presentation describing their customer discovery journey over the 10 weeks. While all the teams used the Mission Model Canvas, (videos here), Customer Development and Agile Engineering to build Minimal Viable Products, each of their journeys was unique.

By the end the class all the teams realized that the problem as given by the sponsor had morphed into something bigger, deeper and much more interesting.

All the presentations are worth a watch.

Team Fleetwise — Vehicle Fleet Management

If you can’t see the Fleetwise 2-minute video, click here

If you can’t see the Fleetwise slides, click here

Mission-Driven Entrepreneurship
This class is part of a bigger idea — Mission-Driven Entrepreneurship. Instead of students or faculty coming in with their own ideas, we ask them to work on societal problems, whether they’re problems for the State Department or the Department of Defense or non-profits/NGOs or the Oceans and Climate or for anything the students are passionate about. The trick is we use the same Lean LaunchPad / I-Corps curriculum — and the same class structure — experiential, hands-on– driven this time by a mission-model not a business model. (The National Science Foundation, National Security Agency and the Common Mission Project have helped promote the expansion of the methodology worldwide.)

Mission-driven entrepreneurship is the answer to students who say, “I want to give back. I want to make my community, country or world a better place, while being challenged to solve some of the toughest problems.”

Project Agrippa — Logistics and Sustainment in IndoPacific

If you can’t see the Project Agrippa 2-minute video, click here

If you can’t see the Project Agrippa slides, click here

It Started With An Idea
Hacking for Defense has its origins in the Lean LaunchPad class I first taught at Stanford in 2011. I observed that teaching case studies and/or how to write a business plan as a capstone entrepreneurship class didn’t match the hands-on chaos of a startup. Furthermore, there was no entrepreneurship class that combined experiential learning with the Lean methodology. Our goal was to teach both theory and practice.

The same year we started the class, it was adopted by the National Science Foundation to train Principal Investigators who wanted to get a federal grant for commercializing their science (an SBIR grant.) The NSF observed, “The class is the scientific method for entrepreneurship. Scientists understand hypothesis testing” and relabeled the class as the NSF I-Corps (Innovation Corps). The class is now taught in 9 regional locations supporting 98 universities and has trained over 1500 science teams. It was adopted by the National Institutes of Health as I-Corps at NIH in 2014 and at the National Security Agency in 2015.

Team Silknet — Detecting Ground Base Threats

If you can’t see the Silknet 2-minute video, click here

If you can’t see the Silknet slides, click here

Origins Of Hacking For Defense
In 2016, brainstorming with Pete Newell of BMNT and Joe Felter at Stanford, we observed that students in our research universities had little connection to the problems their government was trying to solve or the larger issues civil society was grappling with. As we thought about how we could get students engaged, we realized the same Lean LaunchPad/I-Corps class would provide a framework to do so. That year we launched both Hacking for Defense and Hacking for Diplomacy (with Professor Jeremy Weinstein and the State Department) at Stanford.

Team Flexible Fingerprints — Improve Cybersecurity

If you can’t see the Flexible Fingerprints 2-minute video, click here

If you can’t see the Flexible Fingerprints slides, click here

Goals for the Hacking for Defense Class
Our primary goal was to teach students Lean Innovation while they engaged in national public service. Today if college students want to give back to their country, they think of Teach for America, the Peace Corps, or AmeriCorps or perhaps the US Digital Service or the GSA’s 18F. Few consider opportunities to make the world safer with the Department of Defense, Intelligence community or other government agencies.

In the class we saw that students could learn about the nation’s threats and security challenges while working with innovators inside the DoD and Intelligence Community. At the same time the experience would introduce to the sponsors, who are innovators inside the Department of Defense (DOD) and Intelligence Community (IC), a methodology that could help them understand and better respond to rapidly evolving threats. We wanted to show that if we could get teams to rapidly discover the real problems in the field using Lean methods, and only then articulate the requirements to solve them, defense acquisition programs could operate at speed and urgency and deliver timely and needed solutions.

Finally, we wanted to familiarize students with the military as a profession and help the better understand its expertise, and its proper role in society. We hoped it would also show our sponsors in the Department of Defense and Intelligence community that civilian students can make a meaningful contribution to problem understanding and rapid prototyping of solutions to real-world problems.

Team Neurosmart — Optimizing Performance of Special Operators

If you can’t see the Neurosmart 2-minute video, click here

If you can’t see the Neurosmart slides, click here

Mission-Driven in 50 Universities and Continuing to Expand in Scope and Reach
What started as a class is now a movement.

From its beginning with our Stanford class, Hacking for Defense is now offered in over 50 universities in the U.S., as well as in the UK and Australia. Steve Weinstein started Hacking for Impact (Non-Profits) and Hacking for Local (Oakland) at U.C. Berkeley, and Hacking for Oceans at both Scripps and UC Santa Cruz. Hacking for Homeland Security launched last year at the Colorado School of Mines and Carnegie Mellon University. A version for NASA is coming up next.

And to help businesses recover from the pandemic, the teaching team taught a series of Hacking For Recovery classes last summer.

Our Hacking for Defense team continues to look for opportunities to adapt and apply the course methodology for broader impact and public good. Project Agrippa, for example, piloted a new “Hacking for Strategy” initiative inspired by their experience in Stanford’s “Technology, Innovation and Modern War” class that Raj Shah, Joe Felter and I taught last fall. This all-star team of 4 undergraduates and a JD/MBA developed new ways to provide logistical support to maritime forces in the Indo-Pacific region. Their recommendations drew on insights gleaned from over 242! interviews (a national H4D class record.) After in-person briefings to Marine Corps and Navy commanders and staff across major commands from California to Hawaii, they received interest in establishing a future collaboration, validating our hypothesis that Hacking for Strategy would be a welcome addition to our course offerings. Its premise is that keeping America safe not only requires us maintaining a technological edge but also using these cutting edge technologies to develop new operational concepts and strategies. Stay tuned.

Team AngelComms — Rescuing Downed Pilots

If you can’t see the AngelComms 2-minute video, click here

If you can’t see the AngelComms slides, click here

Team Salus — Patching Operational Systems to Keep them Secure

If you can’t see the Salus 2-minute video, click here

If you can’t see the Salus slides, click here

Team Mongoose — Tracking Hackers Disposable Infrastructure

If you can’t see the Mongoose 2-minute video, click here

If you can’t see the Mongoose slides, click here

Team Engage — Preparing Aviators to Make Critical High Stakes Decisions

If you can’t see the Engage slides, click here

What’s Next For These Teams?
When they graduate, the Stanford students on these teams have the pick of jobs in startups, companies, and consulting firms. Most are applying to H4X Labs, an accelerator focused on building dual-use companies that sell to both the government and commercial firms. Many will continue to work with their problem sponsor. Several will join the new Stanford Gordian Knot Center which is focused on the intersection of policy, operational concepts, and technology.

In our post class survey 86% of the students said that the class had impact on their immediate next steps in their career. Over 75% said it changed their opinion of working with the Department of Defense and other USG organizations.

It Takes A Village
While I authored this blog post, this class is a team project. The secret sauce of the success of Hacking for Defense at Stanford is the extraordinary group of dedicated volunteers supporting our students in so many critical ways.

The teaching team consisted of myself and:

• Pete Newell, retired Army Colonel and ex Director of the Army’s Rapid Equipping Force, now CEO of BMNT.
• Joe Felter, retired Army Colonel; and former deputy assistant secretary of defense for South Asia, Southeast Asia, and Oceania; and William J. Perry Fellow at Stanford’s Center for International Security and Cooperation.
• Steve Weinstein, 30-year veteran of Silicon Valley technology companies and Hollywood media companies. Steve was CEO of MovieLabs, the joint R&D lab of all the major motion picture studios. He runs H4X Labs.
• Tom Bedecarré, the founder and CEO of AKQA, the leading digital advertising agency.
• Jeff Decker, a Stanford researcher focusing on dual-use research. Jeff served in the U.S. Army as a special operations light infantry squad leader in Iraq and Afghanistan.

Our teaching assistants this year were Nick Mirda, Sally Eagen, Joel Johnson, past graduates of Hacking for Defense, and Valeria Rincon. A special thanks to the National Security Innovation Network (NSIN) and Rich Carlin and the Office of Naval Research for supporting the program at Stanford and across the country, as well as Lockheed Martin and Northrop Grumman. And our course advisor, Tom Byers, Professor of Engineering and Faculty Director, STVP.

Thanks to Mike Brown, Director of the Defense Innovation Unit for giving an extraordinary closing keynote.

We were lucky to get a team of mentors (VCs and entrepreneurs) as well as an extraordinary force of military liaisons from the Hoover Institution’s National Security Affairs Fellows program, Stanford senior military fellowship program and other accomplished military affiliated volunteers. This diverse group of experienced experts selflessly volunteer their time to help coach the teams. Thanks to Todd Basche, Rafi Holtzman, Kevin Ray, Craig Seidel, Katie Tobin, Jennifer Quarrie, Jason Chen, Matt Fante, Richard Tippitt, Rich Lawson, Commander Jack Sounders, Mike Hoeschele, Donnie Hasseltine, Steve Skipper, LTC Jim Wiese, Col. Denny Davis, Commander Jeff Vanak, Marco Romani, Rachel Costello, LtCol Kenny Del Mazo, Don Peppers, Mark Wilson and LTC Ed Cuevas

And of course a big shout-out to our problem sponsors across the DoD and IC: MSgt Ashley McCarthy, Jason Stack, Col Sean Heidgerken, LTC Richard Barnes, George Huber, Neal Ziring, Shane Williams, Anthony Ries, Russell Hoffing, Javier Garcia, Matt Correa, Shawn Walsh, and Claudia Quigley.

Steve Blank writes about defense innovation at www.steveblank.com.

Over a Zoom call Suresh explained, “I’m trying to push the importance of running customer discovery and testing these hypotheses before we build our U.S. product, but I’m running into a pushback from my CEO. He says, “We’re disruptors! Discovery is going to slow us down. We need to move quickly!”

Suresh was concerned. “If we don’t test our assumptions about the market and any changes needed to our products, we’ll build something I can’t sell. Worse, given how expensive clinical trials are in medtech, I’m concerned if we build a product that isn’t commercially viable, we’ll be out of business before we even start.”

I could hear his frustration and concern when he asked, “How can I convince my boss to use customer discovery to test our hypotheses?”

That’s when I realized that Suresh was overlooking a few things.

1. He was trying to sell the “story” of Customer Discovery as part of the Lean Methodology to his CEO by explaining how discovery worked with the business model canvas, agile engineering, pivots and MVPs.
2. But talking about the method to others is not the same as “doing” Customer Discovery.
3. Customer Discovery is about gathering validated evidence, not proselytizing a method.
4. The goal of discovery is to gather evidence to test hypotheses, deeply understand the customer problem and validate a solution.
5. As head of sales and marketing, Suresh didn’t need his CEO to buy into the process or give his permission to start the discovery process. He was in charge.
6. Given the ubiquity of Zoom, he could use it to rapidly get out of the building to the U.S. to test some hypotheses and gather some initial insights.

I pointed out that once he had potential customer, regulator, and reimbursement data from his Discovery interviews, he could bring that data into conversations with his CEO.

Having real data turns conversations from faith-based to evidence-based.

Lessons Learned

• Talking about the Lean method to others is not the same as doing it
• If you’re in charge or part of a customer-facing organization, you don’t need to wait for permission to talk to customers to test hypotheses
• Having real data turns conversations from faith-based to evidence-based

Steve Blank writes about how to build a successful startup at www.steveblank.com