I’ve always thought of myself as a practitioner. In the startups I was part of, the only “strategy” were my marketing tactics on how to make the VP of Sales the richest person in the company. After I retired, I created Customer Development and co-created the Lean Startup as a simple methodology which codified founders best practices – in a language and process that was easy to understand and implement. All from a practitioner’s point of view.
So you can imagine my surprise when I received the annual “Strategy Leadership Impact” Award from the Strategic Management Society (SMS). The SMS is the strategy field’s main professional society with over 3,100 members. They publish three academic journals; the Strategic Management Journal, Strategic Entrepreneurship Journal, and Global Strategy Journal.
The award said, [Steve Blank] as the Father of Modern Entrepreneurship, changed how startups are built, how entrepreneurship is taught, how science is commercialized, and how companies and government innovate.
Here’s my acceptance speech.
Thank you for the Strategy Leadership Impact Award. As a practitioner standing in front of a room full of strategists, I’m humbled and honored.
George Bernard Shaw reminded us that Americans and British are “one people separated by a common language.” I’ve often felt the same way about the gap between practitioners and strategists.
The best analogy I can offer, is the time after a long plane flight to Sydney, I jumped into a taxi and as the taxi driver started talking I started panicking – wondering what language he was speaking, and how I was going to be able to communicate to him.
It took me almost till we got to the hotel to realize he was speaking in English.
That’s sometimes how it feels between those who do strategy and those who study it.
So today, I’d like to share with you how this practitioner accidently became a strategist and how that journey led to what we now call the Lean Startup.
It’s a story that begins, perhaps surprisingly with what I call the Secret History of Silicon Valley.
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Silicon Valley’s roots lie in solving urgent, high-uncertainty national-security problems during World War II and the Cold War with the Soviet Union.
During WW II, the United States mastered scale and exploitation—mass-producing ships, aircraft, and tanks through centralized coordination. Ford, GM, Dupont, GE and others became the “arsenals of democracy.” In less than 4 years the U.S. built 300,000 aircraft, 124,000 of all types of ships, 86,000 tanks.
But simultaneously we created something radically different, something no other nation did – we created the Office of Science and Research and Development – OSR&D. This was a decentralized network of university labs that worked on military problems that involved electronics, chemistry and physics. These labs solved problems where outcomes were unknown and time horizons uncertain—exactly the conditions that later came to define innovation under uncertainty.
These labs delivered radar, rockets, proximity fuses, penicillin, sulfa drugs, and for the first two years ran the U.S. nuclear weapons program.
In hindsight, way before we had the language, the U.S. was practicing dynamic capabilities: the capacity to sense, seize, and transform under extreme uncertainty. It was also an early case of organizational ambidexterity—balancing mass production with rapid exploration.
One branch of this Office of Science and Research and Development – focused on electronic warfare—became the true genesis of the Valley’s innovation model.
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In 1943, U.S. bombers over Europe faced catastrophic losses—4–5% of planes were shot down every mission. The German’s had built a deadly effective radar-based air defense system. The U.S. responded by creating the Harvard Radio Research Lab, led by Stanford’s Fred Terman. The lab had nothing to do with Harvard, Radio or Research.
Its goal was to rapidly develop countermeasures: jammers, receivers, and radar intelligence.
In the span of three years, Terman’s lab created an entire electronic ecosystem to defeat the German air defense systems. By war’s end U.S. factories were running 24/7 mass producing tens of thousands of the most complicated electronics and microwave systems that went on every bomber over Europe and Japan.
These teams were interdisciplinary, field-connected, and operating in continuous learning cycles:
- Scientists and engineers worked directly with pilots and operators—what we’d now call frontline customer immersion.
- They built rapid prototypes—the Minimum Viable Products of their time.
- They engaged in short feedback loops between lab and battlefield—what John Boyd would later formalize as the OODA loop.
- They were, in essence, running a learning organization under fire—a live example of strategic adaptation and iterative sensemaking.
But what does this have to do with Silicon Valley?
When the war ended Terman came back to Stanford and became Dean of Engineering and institutionalized this model. He embedded government research into the university, recruited his wartime engineers as faculty, and redefined Stanford as an outward-facing institution.
While most universities pursued knowledge exploitation – publishing, teaching, and extending established disciplines, Terman at Stanford did something that few universities in the 1950’s, 60’s or 70’s were doing – he pursued knowledge exploration and recombination. Turning Stanford into an outward facing university – with a focus on commercializing their inventions.
- He reconfigured incentives — encouraging professors to consult and found companies, an unprecedented act of strategic boundary spanning
- He believed spinning out microwave and electronics companies from his engineering labs was good for the university and for the country.
- He embedded exploration in the curriculum — mixing physics, electronics, and systems engineering.
- Cultivating external linkages — he and his professors were on multiple advisory boards with the Department of Defense, intelligence agencies, and industry.
Terman’s policies as now Provost effectively turned Stanford into an early platform for innovation ecosystems—decades before the term existed.
The technology spinouts from Stanford and small business springing up nearby were by their very nature managing uncertainty, complexity, and unpredictability. These early Valley entrepreneurs weren’t “lone inventors”; they were learning organizations, long before that term existed. They were continuously testing, learning, and iterating based on real operational data and customer feedback rather than long static plans.
However, at the time there was no risk capital to guide them. They were undercapitalized small businesses chasing orders and trying to stay in business.
It wasn’t until the mid 1970’s when the “prudent man” rule was revised for pension funds, and Venture Capital began to be treated as an institutional asset class, that venture capital at scale became a business in Silicon Valley. This is the moment when finance replaced learning as the dominant logic.
For the next 25 years, Venture investors – most of them with MBAs or with backgrounds in finance, treated startups like smaller versions of large companies. None of them had worked on cold war projects nor were they familiar with the agile and customer centric models defense innovation organizations had built. No VC was thinking about whether lessons from corporate strategic management thinkers of the time could be used in startups. Instead, VCs imposed a waterfall mindset —business plans and execution of the strategy in the plan — the opposite of how the Valley first innovated. The earlier language of experimentation, iteration, and customer learning disappeared.
And now we come full circle – to the Lean Startup.
At the turn of the century after 21 years as a practitioner, and with a background working on cold war weapons systems, I retired from startups and had time to think.
The more I looked at the business I had been in, and the boards I was now sitting on, I realized a few things.
- No business plan survived first contact with customers.
- On day one all startups have is a series of untested hypotheses
- Yet startups were executing rather than learning
- Our strategic language and tools—all designed for large firms—were useless in contexts of radical uncertainty.
- Startups that succeeded were the ones that learned from their customers and iterated on the plan. Those that didn’t, ended up selling off their furniture.
- Most importantly – as I started reading all the literature I found on innovation strategy, almost all of it was about corporate innovation.
- We had almost a century of management tools and language to describe corporate strategy for both growth and innovation – yet there were no tools, language or methods for startups.
- But it was worse. Because both practitioners and their investors weren’t strategists, we had been trapped in thinking that startups were smaller versions of large companies
- When the reality was that at their core, large companies were executing known business models, but startups? Startups were searching for business models
- This distinction between startup search and large company execution had never been clearly articulated.
- There was a mismatch between the reality and practice.
- We needed to reframe entrepreneurship as a strategic process, not a financial one
- I realized that every startup believed their journey was unique, and thought they had to find their own path to profitability and scale.
- That was because we had no shared methodology, language or common tools. So I decided to build them.
- The first was Customer Development – at its heart a very simple idea – there are no facts inside the building – so get outside.
- Here we were reinventing what the best practices from the wartime military organizations, and from Lead User Research and Discovery Driven Planning – this time for startups
- The goal is to test all the business model hypotheses – including the two most important – customer and value proposition – which we call product/ market fit.
- The next, Agile Engineering – a process to build products incrementally and iteratively – was a perfect match for customer development.
- And then finally, repurposing Alexander Osterwalder’s Business Model Canvas to map the hypotheses needed in commercialization of a technology
The sum of these tools – Customer Development, Agile Engineering and the Business Model Canvas – is the Lean Methodology.
What I had done is turn a craft into a discipline of strategic learning—a continuous loop of hypothesis testing, experimentation via minimum viable products, and adaptation via pivots.
Lean is a codified system for strategy formation under uncertainty.
Over the last two decades Lean has turned into the de facto standard for starting new ventures. The classes I created at Stanford were adopted by the National Science Foundation and the National Institutes of Health, to commercialize science in the U.S.
And while contemporary entrepreneurs didn’t know it they were adopting the continuous learning cycles that had fueled wartime innovation.
What comes next is going to be even more interesting.
We’re going to remember – for better or worse – 2025 as another inflection point.
AI in everything, synthetic biology, and capital at previously unimaginable scale, are collapsing the distance between exploration and exploitation.
The boundary between discovery, invention, and strategy is dissolving.
Given how fast things are changing I’m looking forward to seeing strategy itself become a dynamic capability—not a plan, but a process of learning faster than the environment changes.
I can’t wait to see what you all create next.
In closing, my work at Stanford was made possible by the unflinching support from Tom Byers, Kathy Eisenhardt and Riitta Katila in the Stanford Technology Ventures Program who let a practitioner into the building.
Thank you.
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Theorists
When he wrote it down, it was just theory. Other theorists in the 1930s and ’40s took Einstein’s theory and provided the impetus for building the atomic bomb. (Leo Szilard conceived neutron chain reaction idea, Hans Bethe led the Theoretical Division at Los Alamos, Edward Teller developed hydrogen bomb theory.) Einstein’s theory was demonstrably proved correct over Hiroshima and Nagasaki.
Professors (especially in Science, Technology, Engineering and Math) run labs that function like mini startups. They ask research questions, then hire grad students, postdocs, and staff and write grant proposals to fund their work, often spending 30–50% of their time writing and managing grants. When they get a grant the lead researcher (typically a faculty member/head of the lab) is called the Principal Investigator (PI).
