Founders Need to Be Ruthless When Chasing Deals

One of the most exciting things a startup CEO in a business-to-business market can hear from a potential customer is, “We’re excited. When can you come back and show us a prototype?”

This can be the beginning of a profitable customer relationship or a disappointing sinkhole of wasted time, money, resources, and a demoralized engineering team.

It all depends on one question every startup CEO needs to ask.


I was having coffee and pastries with Justin, an ex-student, listening to him to complain over the time he wasted with a potential customer. He was building a complex robotic system for factories. “We spent weeks integrating the sample data they gave us to build a functional prototype, and then after our demo they just ghosted us. I still don’t know what happened!”

After listening to how he got into that predicament, I realized it sounded exactly like the mistake I had made selling enterprise software.

Enthusiasm Versus Validation
Finding product/market fit is the holy grail for startups. For me, it was a real rush when potential users in a large company loved our slideware and our minimum viable product (MVP). They were ecstatic about the time the product could save them and started pulling others into our demos. A few critical internal recommenders and technical evaluators gave our concept the thumbs up. Now we were in discussions with the potential buyers who had the corporate checkbook, and they were ready to have a “next step” conversation.

This buyer wanted us to transform our slideware and MVP into a demonstration of utility with their actual data. This was going to require our small, overcommitted engineering team to turn the MVP into a serviceable prototype.

When I heard a potential customer offer us their own internal customer data I was already imagining popping Champagne corks once we showed them our prototype. (For context, our products sold for hundreds of thousands of dollars, and lifetime value to each customer was potentially measured in millions.) I rallied our engineering team to work for the next few months to get the demo of the prototype ready. As much as we could, we integrated the customers’ users and technical evaluators into our prototype development process. Then came the meeting with the potential customer. And it went great. The users were in the room, the buyer asked lots of questions, everyone made some suggestions and then we all went home. And the follow up from the potential customer? Crickets…

Even our user advocates stopped responding to emails.

What did I do wrong?
In my unbridled and very naive enthusiasm for impressing a potential customer, I made a rookie mistake – I never asked the user champion or the potential buyer what were the steps for turning the demo into a purchase order. I had made a ton of assumptions – all of them wrong. And most importantly I wasted the most precious things a startup has – engineering resources, time, and money.

In hindsight I had no idea whether my potential customer was asking other companies to demo their product. I had no idea whether the buyer had a budget or even purchase authority. If they did, I had no idea of their timeline for a decision. I had no idea who were the other decision-makers in the company to integrate, deploy and scale the product. I didn’t even know what the success criteria for getting an order looked like. I didn’t check for warning signs of a deal that would go nowhere: whether the person requesting the demo was in a business unit or a tech evaluation/innovation group, whether they’d pay for a functional prototype they could use, etc.  And for good measure, I never even considered asking the potential customer to pay for the demo and/or my costs.

(My only excuse was that this was my first foray into enterprise sales.)

Be Ruthless about the Opportunity Costs of Chasing Deals
After that demoralizing experience I realized that every low probability demo got us further from success rather than closer. While a big company could afford to chase lots of deals I just had a small set of engineering resources. I became ruthless about the opportunity costs of chasing deals whose outcome I couldn’t predict.

So we built rigor into our sales process.

We built a sales road map of finding first product/market fit with the users and recommenders. However, we realized that there was a second product/market fit with the organization(s) that controlled the budget and the path to deployment and scale.

For this second group of gatekeepers we came up with a cheap hack to validate that a demo wasn’t just a tire-kicking exercise on their part. First, we asked them basic questions about the process: the success criteria, the decision timeline, did a budget exist, who had the purchase authority, what were the roles and approval processes of other organizations (IT, Compliance and Security, etc.) and what was the expected rate of scaling the product across their enterprise. (All the rookie questions I should have asked the first time around.)

That was just the starting point to decide if we wanted to invest our resources. We followed up our questions by sending them a fully cancelable purchase order. We listed all the features we had demoed that had gotten the users excited and threw in the features the technical evaluators had suggested. And we listed our price. In big letters the purchase order said, “FULLY CANCELABLE.” And then we sent it to the head of the group that asked us for the prototype.

As you can imagine most of the time the response was – WTF?

Figure Out Who’s A Serious Prospect
That’s when the real learning started. It was more than OK with me if they said they weren’t ready to sign. Or they told me there were other groups who needed be involved. I was now learning things I never would have if I just showed up with a prototype. By asking the customer to sign a fully cancelable purchase order we excluded “least likely to close prospects”; those who weren’t ready to make a purchase decision, or those who already had a vendor selected but needed to go through “demo theater” to make the selection seem fair. But most importantly it started a conversation with serious prospects that informed us about the entire end-to-end approval process to get an order- who were the additional people who needed to say yes across the corporation – and what were their decision processes.

Our conversions of demos into orders went through the roof.

Finally, I was learning some of the basics of complex sales.

Justin stared at his uneaten pastry for a while and then looked up at me and said smiling, “I never knew you could do that. That’s given me a few ideas what we could do.”  And just like that he was gone.

Lessons Learned

  • In complex sales there are multiple product/market fits – Users, Buyers, etc. — each with different criteria
  • Don’t invest time and resources in building on-demand prototypes if you don’t know the path to a purchase order
  • Use polite forcing functions, e.g. cancelable purchase orders, to discover who else needs to say “yes”

Is a $100 Million Enough?

This article first appeared in Inc.

Capitalism has been good to me. After serving in the military during Vietnam, I came home and had a career in eight startups. I got to retire when I was 45. Over the last quarter century, in my third career, I helped create the methods entrepreneurs use to build new startups, while teaching 1,000’s of students how to start new ventures. It’s been rewarding to see tech entrepreneurship become an integral part of the economy and tech companies become some of the most valued companies in the world.

What has made this happen is the relentless cycle of innovation and creative destruction of old industries driven by new startups with new tech and new business models (network television replaced by streaming services, Nvidia GPUs versus Intel CPUs, electric cars versus the internal combustion engine, film cameras versus smartphones, programmers versus AI), all fueled by venture capital.


It makes me wonder – are startups still founded by people with a passion for creating something new? Or has the motivation changed to accruing the biggest pile of cash?

When I was an entrepreneur, what got me up in the morning was building something amazing that people wanted to grab out of my hands and use. The thought that I might make a $1 million or even $10 million on the way was always in the back of my head, but that wasn’t why I did it.

I wonder if it’s different for today’s entrepreneurs.

Here’s a thought experiment: What if we told every new entrepreneur that regardless of how successful they were, their total compensation would be capped at $100 million.

How many aspiring entrepreneurs would decide it wasn’t worth starting a company? Would Steve Jobs, Jeff Bezos, Elon Musk, et al have quit earlier? Have picked other careers?

How many would decide it wasn’t worth sticking around after their company was large and successful? (Would that be a bad thing?)

Would entrepreneurship suffer? Would we get less innovation? If so, why?

Would the best and brightest move to other countries?

Then let’s run the same thought experiment with Venture Capitalists. Would they pick other careers? Invest less?

At $100 million would capitalism crumble?  Would we all be, heaven forbid, be “Socialists” or worse, to even have this conversation?

Questions
I’m curious what you think.

Should there be any limit?

If so, why?

Or why not.

What would be the consequences?

Apple Vision Pro – Tech in the Search of a Market

A version of this article previously appeared in Fortune.


If you haven’t been paying attention Apple has started shipping its Apple Vision Pro, its take on a headset that combines Virtual Reality (VR) and Augmented Reality (AR). The product is an amazing technical tour de force.

But the product/market fit of this first iteration is a swing and a miss.


I’ve watched other world class consumer product companies make the same mistakes:

  1. Come up with amazing hardware that creates entirely new capabilities
  2. Forecast demand based on volumes of their previous consumer products
  3. Confuse consumers by defining a new category without a frame of reference
  4. Discover the hardware doesn’t match their existing consumer customer base needs
  5. Work hard (read spend a lot of money) on trying to “push” sales to their existing customers
  6. Revenue is woefully short of forecast. Marketing and capital expenses (new factory, high R&D expense) were predicated on consumer-scale sales. The new product is burning a ton of cash
  7. Ignore/not understand adjacent niche markets that would have “pulled” the product out of their hands, if they had developed niche-specific demos and outreach
  8. Eventually pivot to the niche markets that are excited about the product
  9. The niche markets make great beachhead markets, but are too small to match the inflated forecasts and the built-in burn rates of consumer scale sales
  10. Either…
    • After multiple market pivots and changes in leadership, abandon the product
    • Pivot and perserve

Déjà vu All Over Again
I lived the equivalent of this when Kodak (remember them?) launched a product in 1990 called PhotoCD. Kodak wanted consumers to put their film photos on their home CDROM drive and then display them on their televisions. You dropped off your film at a film processor and instead of just getting physical prints of your pictures they would scan the film, and burn them onto a Compact Disc. You’d go home with a Compact Disc with your pictures on it.

I got a preview of PhotoCD when I was the head of marketing at SuperMac, a supplier of hardware and software for graphics professionals. The moment I saw the product I knew every one of my professional graphics customers (ad agencies, freelancers, photo studios, etc.) would want to use it. In fact, they would have paid a premium for it. I was floored when Kodak told me they were launching PhotoCD as a consumer product.

The problem was that in 1990 consumers did not have CDROM drives to display the pictures. At the time even most personal computers lacked them. But every graphics professional did own a CDROM drive but most didn’t own a high-resolution film scanner – and PhotoCD would have been perfect for them – and the perfect launch customer. To this day I remember being lectured by a senior Kodak executive, “Steve you don’t get it, we’re experts at selling to consumers. We’ll sell them the CDROM drives as well.”  (The Kodak CDROM drives were the size of professional audio equipment and depending on the model, costing $600-$1000 in today’s dollars.)

(And when consumer CDROM drives became available they couldn’t play the PhotoCD disks as they were encoded in a proprietary Kodak standard to lock you into their drives!)  The result was that PhotoCD failed miserably as a consumer product. Subsequent pivots to professional graphics users (a segment another part of Kodak knew well) came too late, as low cost scanners and non-proprietary standards (JPEG) prevailed.

So what’s the lesson for Apple?

  1. Apple is trying to push Vision Pro into their existing consumer customers
  2. All the demos and existing applications are oriented to their consumer customers
  3. Apple did not create demos for how the Vision Pro could be used in new markets where users would jump on buying a Vision Pro. For example,
    1. There is proof of demand (here, here and here) of an adjacent mass market, helping millions of home owners repair things around the home
    2. There is proof of demand in industrial applications outside of the consumer space (here.) Every company that has complex machinery have been experimenting with AR for years. Imagine car repair with a Vision Pro AR tutorial. Or jet engine maintenance. Or the entire gamut of complex machinery.

All of these would have been great Vision Pro demos for training and repair. It’s hard to understand why Apple ignored these easy wins.

Getting it Right
Apple’s entry into new markets by creating new product categories –  iPods, iPads, iPhones – is unprecedented in the history of the modern corporation – $300 billion (75% of their revenue) is from non-computer hardware. In addition, they’ve created an entirely new $85+ billion subscription business model; the App Store, iTunes, Apple Care, Apple Pay, Apple Cash, Apple Arcade, Apple Music, Apple TV.

It’s hard to remember, but the first version of these products launched with serious limitations that follow-on versions remedied. The first version of the iPhone only ran Apple software, it was a closed system without an app store, had no copy and paste, couldn’t record video, etc. The original Apple Watch was positioned as a fashion accessory. It wasn’t until later that Apple realized that the killer apps for the Watch were fitness and health. Fixing the technical flaws while finding the right markets for all these products took time and commitment.

The same will likely be true for the Vision Pro. Apple marketers will realize that adjacent spaces they are less familiar with will provide the first “got to have it” beachhead markets. Newer versions will ride the technology wave of lighter, and cheaper versions.

Apple’s CEO Tim Cook has made a personal bet on the Vision Pro. More than any other company they have sufficient resources (cash on hand and engineering talent) to pivot their way to product/market fit in the real markets that need it.

Here’s hoping they find it.

Technology, Innovation, and Great Power Competition – 2023 Wrap Up

We just wrapped up the third year of our Technology, Innovation, and Great Power Competition class –part of Stanford’s Gordian Knot Center for National Security Innovation.

Joe Felter, Mike Brown and I teach the class to:

  • Give our students an appreciation of the challenges and opportunities for the United States in its enduring strategic competition with the People’s Republic of China, Russia and other rivals.
  • Offer insights on how commercial technology (AI, autonomy, cyber, quantum, semiconductors, access to space, biotech, hypersonics, and others) are radically changing how we will compete across all the elements of national power e.g. diplomatic, informational, military, economic, financial, intelligence and law enforcement (our influence and footprint on the world stage).
  • Expose students to experiential learning on policy questions. Students formed teams, got out of the classroom and talked to the stakeholders and developed policy recommendations.

Why This Class?
The recognition that the United States is engaged in long-term strategic competition with the Peoples Republic of China and Russia became a centerpiece of the 2017 National Security Strategy and 2018 National Defense Strategy. The 2021 interim National Security Guidance and the administration’s recently released 2022 National Security Strategy make clear that China has rapidly become more assertive and is the only competitor potentially capable of combining its economic, diplomatic, military, and technological power to mount a sustained challenge to a stable and open international system. And as we’ve seen in Ukraine, Russia remains determined to wage a brutal war to play a disruptive role on the world stage.

Prevailing in this competition will require more than merely acquiring the fruits of this technological revolution; it will require a paradigm shift in the thinking of how this technology can be rapidly integrated into new capabilities and platforms to drive new operational and organizational concepts and strategies that change and optimize the way we compete.

Class Organization
The readings, lectures, and guest speakers explored how emerging commercial technologies pose challenges and create opportunities for the United States in its strategic competition with great power rivals with an emphasis on the People’s Republic of China. We focused on the challenges created when U.S. government agencies, our federal research labs, and government contractors no longer have exclusive access to these advanced technologies.

This course included all that you would expect from a Stanford graduate-level class in the Masters in International Policy – comprehensive readings, guest lectures from current and former senior officials/experts, and written papers. What makes the class unique however, is that this is an experiential policy class. Students formed small teams and embarked on a quarter-long project that got them out of the classroom to:

  • identify a priority national security challenge, and then …
  • validate the problem and propose a detailed solution tested against actual stakeholders in the technology and national security ecosystem.

The class was split into three parts.

Part 1, weeks 1 through 4 covered the international relations theories that attempt to explain the dynamics of interstate competition between powerful states, U.S. national security and national defense strategies and policies guiding our approach to Great Power Competition specifically focused on the People’s Republic of China (PRC) and the Chinese Communist Party (CCP).

In between parts 1 and 2 of the class, the students had a midterm individual project. It required them to write a 2,000-word policy memo describing how a U.S. competitor is using a specific technology to counter U.S. interests and a proposal for how the U.S. should respond.

Part 2, weeks 5 through 8, dove into the commercial technologies: semiconductors, space, cyber, AI and Machine Learning, High Performance Computing, and Biotech. Each week the students had to read 5-10 articles (see class readings here.) And each week we had guest speakers on great power competition, and technology and its impact on national power and lectures/class discussion.

Guest Speakers
In addition to the teaching team, the course drew on the experience and expertise of guest lecturers from industry and from across U.S. Government agencies to provide context and perspective on commercial technologies and national security.

The students were privileged to hear from extraordinary  guest speakers with significant experience and credibility on a range of topics related to the course objectives. Highlights of this year’s speakers include:

On National Security and American exceptionalism: General Jim Mattis, US Marine Corps (Ret.), former Secretary of Defense.

On China’s activities and efforts to compete with the U.S.: Matt Pottinger – former Deputy National Security Advisor, Elizabeth Economy – leading China scholar and former Dept of Commerce Senior Advisor for China, Tai Ming Cheung, – Author of Innovate to Dominate: The Rise of the Chinese Techno-Security State.

On U.S. – China Policy: Congressman Mike Gallagher, Chair House Select Committe on China.

On Innovation and National Security: Chris Brose – Author of The Kill Chain, Doug Beck – Director of the Defense Innovation Unit, Anja Manuel – Executive Director of the Aspen Strategy and Security Forum.

For Biotech: Ben Kirukup – senior biologist US Navy, Ed You – FBI Special Agent Biological Countermeasures Unit, Deborah Rosenblum – Asst Sec of Defense for Nuclear, Chemical, and Biological Defense Programs, Joe DeSimone – Professor Chemical Engineering.

For AI: Jared Dunnmon – Technical Director for AI at the Defense Innovation Unit, Lt. Gen. (Ret) Jack Shanahan – Director, Joint Artificial Intelligence Center, Anshu Roy-  CEO Rhombus AI

For Cyber: Anne Neuberger – deputy national security advisor for cyber

For Semiconductors: Larry Diamond – Senior Fellow at the Hoover Institution

Significantly, the students were able to hear the Chinese perspective on U.S. – China competition from Dr. Jia Qingguo – Member of the Standing Committee of the Central Committee of China.

The class closed with a stirring talk and call to action by former National Security Advisor LTG ret H.R. McMaster.

In the weeks in-between we had teaching team lectures followed by speakers that led discussions on the critical commercial technologies.

Team-based Experiential Project
The third part of the class was unique – a quarter-long, team-based project. Students formed teams of 4-6 and selected a national security challenge facing an organization or agency within the U.S. Government. They developed hypotheses of how commercial technologies can be used in new and creative ways to help the U.S. wield its instruments of national power. And consistent with all our Gordian Knot Center classes, they got out of the classroom. and interviewed 20+ beneficiaries, policy makers, and other key stakeholders testing their hypotheses and proposed solutions.

Hacking For Policy – Final Presentations:
At the end of the quarter, each student teams’ policy recommendations were summarized in a 10-minute presentation. The presentation was the story of the team’s learning journey, describing where they started, where they ended, and the key inflection points in their understanding of the problem. (A written 3000 word report followed focusing on their recommendations for addressing their chosen security challenge and describing how their solutions can be implemented with speed and urgency.)

By the end of the class all the teams realized that the policy problem they had selected had morphed into something bigger, deeper, and much more interesting.

Their policy presentations are below.

The class is as exhausting to teach as it to take. We have an awesome set of teaching assistants.

Team 1: Precision Match (AI for DoD Operations)

Click here to see the presentation.

What makes teaching worthwhile is the feedback we get from our students:

TIGPC has been the best class I’ve taken at Stanford and has caused me to do some reflection in what I want to do after my time at Stanford. I’m only a sophomore but doing such a deep dive into energy and (as Steve says) getting out of the building, I’m starting to seriously consider a career in clean energy security post graduation.

Team 2: Outbound Investment to China

Click here to see the presentation.

Team 3: Open-Source AI

Click here to see a summary of the presentation.

Team 4: AlphaChem

Click here to see the presentation.

One of my takeaways from the class is that you can be the smartest person in the room, but you will never have as much knowledge as everyone else combined so go talk to people, it will make you far smarter

Team 5: South China Sea

Click here to see the presentation.

Awesome class! … incredible in bringing prestigious guest speakers into the class and having engaging discussions. My background was not in national security and this class really offered an important perspective on the opportunities for technology innovation to impact and help with national security.

Team 6: Chinese Real Estate Investment in the U.S.

Click here to see the presentation.

Team 7: Public Private Partnerships

Click here to see the presentation.

Just wanted to let you know that, as a Senior, this is one of the best classes I’ve taken across my 4 years at Stanford.

Team 8: Ukraine Aid

Click here to see the presentation.

Lessons Learned

  • We combined lecture and experiential learning so our students can act on problems not just admire them
    • The external input the students received was a force multiplier
    • It made the lecture material real, tangible and actionable
    • Lean problem solving methods can be effectively employed to address pressing national security and policy challenges
    • This course was akin to a “Hacking for Policy class” and can be tweaked and replicated going forward.
  • The class created opportunities for our best and brightest to engage and address challenges at the nexus of technology, innovation and national security
    • When students are provided such opportunities they aggressively seize them with impressive results
    • The final presentations and papers from the class are proof that will happen
  • Pushing students past what they think is reasonable results in extraordinary output. Most rise way above the occasion

The Department of Defense Is Getting Its Innovation Act Together – But More Can Be Done

This post previously appeared in Defense News  and C4SIR.

Despite the clear and present danger of threats from China and elsewhere, there’s no agreement on what types of adversaries we’ll face; how we’ll fight, organize, and train; and what weapons or systems we’ll need for future fights. Instead, developing a new doctrine to deal with these new issues is fraught with disagreements, differing objectives, and incumbents who defend the status quo. Yet change in military doctrine is coming. Deputy Defense Secretary Kathleen Hicks is navigating the tightrope of competing interests to make it happen – hopefully in time.

From left, Skydio CEO Adam Bry demonstrates the company’s autonomous systems technology for Deputy Defense Secretary Kathleen Hicks and Doug Beck, director of the Defense Innovation Unit, during a visit to the company’s facility in San Mateo, Calif. (Petty Officer 1st Class Alexander Kubitza/U.S. Navy)


There are several theories of how innovation in military doctrine and new operational concepts occur. Some argue new doctrine emerges when civilians intervene to assist military “mavericks,” e.g., the Goldwater-Nichols Act. Or a military service can generate innovation internally when senior military officers recognize the doctrinal and operational implications of new capabilities, e.g., Rickover and the Nuclear Navy.

But today, innovation in doctrine and concepts is driven by four major external upheavals that simultaneously threaten our military and economic advantage:

  1. China delivering multiple asymmetric offset strategies.
  2. China fielding naval, space and air assets in unprecedented numbers.
  3. The proven value of a massive number of attritable uncrewed systems on the Ukrainian battlefield.
  4. Rapid technological change in artificial intelligence, autonomy, cyber, space, biotechnology, semiconductors, hypersonics, etc, with many driven by commercial companies in the U.S. and China.

The Need for Change
The U.S. Department of Defense traditional sources of innovation (primes, FFRDCs, service labs) are no longer sufficient by themselves to keep pace.

The speed, depth and breadth of these disruptive changes happen faster than the responsiveness and agility of our current acquisition systems and defense-industrial base. However, in the decade since these external threats emerged, the DoD’s doctrine, organization, culture, process, and tolerance for risk mostly operated as though nothing substantial needed to change.

The result is that the DoD has world-class people and organizations for a world that no longer exists.

It isn’t that the DoD doesn’t know how to innovate on the battlefield. In Iraq and Afghanistan innovative crisis-driven organizations appeared, such as the Joint Improvised-Threat Defeat Agency and the Army’s Rapid Equipping Force. And armed services have bypassed their own bureaucracy by creating rapid capabilities offices. Even today, the Security Assistance Group-Ukraine rapidly delivers weapons.

Unfortunately, these efforts are siloed and ephemeral, disappearing when the immediate crisis is over. They rarely make permanent change at the DoD.

Bu in the past year several signs of meaningful change show that the DoD is serious about changing how it operates and radically overhauling its doctrine, concepts, and weapons.

First, the Defense Innovation Unit was elevated to report to the of defense secretary. Previously hobbled with a $35 million budget and buried inside the research and engineering organization, its budget and reporting structure were signs of how little the DoD viewed the importance of commercial innovation.

Now, with DIU rescued from obscurity, its new director Doug Beck chairs the Deputy’s Innovation Steering Group, which oversees defense efforts to rapidly field high-tech capabilities to address urgent operational problems. DIU also put staff in the Navy and U.S. Indo-Pacific Command to discover actual urgent needs.

Furthermore, the House Appropriations Committee signaled the importance of DIU with a proposed a fiscal 2024 budget of $1 billion to fund these efforts. And the Navy has signaled, through the creation of the Disruptive Capabilities Office, that it intends to fully participate with DIU.

In addition, Deputy Defense Secretary Hicks unveiled the Replicator initiative, meant to deploy thousands of attritable autonomous systems (i.e. drones – in the air, water and undersea) within the next 18 to 24 months. The initiative is the first test of the Deputy’s Innovation Steering Group’s ability to deliver autonomous systems to warfighters at speed and scale while breaking down organizational barriers. DIU will work with new companies to address anti-access/area denial problems.

Replicator is a harbinger of fundamental DoD doctrinal changes as well as a solid signal to the defense-industrial base that the DoD is serious about procuring components faster, cheaper and with a shorter shelf life.

Finally, at the recent Reagan National Defense Forum, the world felt like it turned upside down. Defense Secretary Lloyd Austin talked about DIU in his keynote address and came to Reagan immediately following a visit to its headquarters in Silicon Valley, where he met with innovative companies. On many panels, high-ranking officers and senior defense officials used the words “disruption,” “innovation,” “speed” and “urgency” so many times, signaling they really meant it and wanted it.

In the audience were a plethora of venture and private capital fund leaders looking for ways to build companies that would deliver innovative capabilities with speed.

Conspicuously, unlike in previous years, sponsor banners at the conference were not the incumbent prime contractors but rather insurgents – new potential primes like Palantir and Anduril. The DoD has woken up. It has realized new and escalating threats require rapid change, or we may not prevail in the next conflict.

Change is hard, especially in military doctrine. (Ask the Marines.) Incumbent suppliers don’t go quietly into the night, and new suppliers almost always underestimate the difficulty and complexity of a task. Existing organizations defend their budget, headcount, and authority. Organization saboteurs resist change. But adversaries don’t wait for our decades-out plans.

But More Can Be Done

  • Congress and the military services can support change by fully funding the Replicator initiative and the Defense Innovation Unit.
  • The services have no procurement budget for Replicator, and they’ll have to shift existing funds to unmanned and AI programs.
  • The DoD should turn its new innovation process into actual, substantive orders for new companies.
  • And other combatant commands should follow what INDOPACOM is doing.
  • In addition, defense primes should more often aggressively partner with startups.

Change is in the air. Deputy Defense Secretary Hicks is building a coalition of the willing to get it done.

Here’s to hoping it happens in time.

The Secret History of Minnesota Part 1: Engineering Research Associates

This post is the latest in the “Secret History Series.” They’ll make much more sense if you watch the video or read some of the earlier posts for context. See the Secret History bibliography for sources and supplemental reading.


No Knowledge of Computers

Silicon Valley emerged from work in World War II led by Stanford professor Fred Terman developing microwave and electronics for Electronic Warfare systems. In the 1950’s and 1960’s, spurred on by Terman, Silicon Valley was selling microwave components and systems to the Defense Department, and the first fledging chip companies (Shockley, Fairchild, National, Rheem, Signetics…) were in their infancy. But there were no computer companies. Silicon Valley wouldn’t have a computer company until 1966 when Hewlett Packard shipped the HP 2116 minicomputer.

Meanwhile the biggest and fastest scientific computer companies were in Minnesota. And by 1966 they had been delivering computers for 16 years.

Minneapolis/St. Paul area companies ERA, Control Data and Cray would dominate the world of scientific computing and be an innovation cluster for computing until the mid-1980s. And then they were gone.

Why?

Just as Silicon Valley’s roots can be traced to innovation in World War II so can Minneapolis/St. Paul’s. The story starts with a company you probably never heard of – Engineering Research Associates.

It Started With Code Breaking
For thousands of years, every nation has tried to keep its diplomatic and military communications secret. They do that by encrypting (protecting the information by using a cipher/code) to scramble the messages. Other nations try to read those messages by attempting to break those codes.

During the 1930s the U.S. Army and Navy each had their own small code breaking groups. The Navy’s was called CSAW (Communications Supplemental Activity Washington) also known as OPS-20-G. The Army codebreaking group was the Signal Intelligence Service (SIS) at Arlington Hall.

The Army focused on decrypting (breaking/decoding) Japan’s diplomatic and Army codes while the Navy worked on breaking Japan’s Naval codes. This was not a harmonious arrangement. The competition between the Army and Navy code breaking groups was so contentious that in 1940 they agreed that the Army would decode and translate Japanese diplomatic code on the even days of the month and the Navy would decode and translate the messages on the odd days of the month. This arrangement lasted until Dec. 7, 1941.

At the start of WWII the Army and Navy code breaking groups each had few hundred people mainly focused on breaking Japanese codes. By the end of WWII, with the U.S. now fighting Germany, and the Soviet Union looming as a potential adversary U.S. code breaking would grow to 20,000 people working on breaking the codes of Germany, Japan and the Soviet Union.

The two groups would merge in 1949 as the Armed Forces Security Agency and then become the National Security Agency (NSA) in 1952.

The Rise of the Machines in Cryptography
Prior to 1932 practically all code breaking by the Army and Navy was done by hand. That year they began using commercial mechanical accounting equipment – the IBM keypunch, card sorters, reproducers and tabulators. The Army and Navy each had their own approach to automating cryptography. The Navy had a Rapid Analytical Machines project with hopes to build machines to integrate optics, microfilm and electronics into cryptanalytic tools. (Vannevar Bush at MIT was trying to build one for the Navy.) As WWII loomed, the advanced Rapid Machines projects were put on hold, and the Army and Navy used hundreds of specially modified commercial IBM electromechanical systems to decrypt codes.

Read the sidebars for more detailed information

Electromechanical Cryptologic Systems in WWII

By the spring 1941, the Army built the first special-purpose cryptologic attachment to the IBM punched card equipment – the GeeWhizzer using relays and rotary switches to help break the Japanese diplomatic codes. That same year, the Navy received the first in a series of 13 electro-mechanical IBM Navy Change Machines to automate decrypting cipher systems used by the Japanese Navy. The Navy attachments were extensive modifications of IBM’s standard card sorters, reproducers and tabulators. Some could be manually reconfigured via plugboards to do different tasks.

During the war the Army and Navy built ~75 of these electro-mechanical and optical systems. Some were standalone units the size of a room.

However, the bulk of the cryptoanalysis was done with IBM punch cards, sorters and tabulators, along with special microfilm comparators from Eastman Kodak. By the end of the War the Army and Navy had 750 IBM machines using several million punch cards every day.

IBM’s other mechanical contribution to cryptanalysts was the Letterwriter, (codenamed CXCO) a desktop machine that tied together electric typewriters to teletype, automatic tape and card punches, microfilm and eventually to film-processing machines. By adding plug-boards they could automate some analysis steps. Hundreds of these were bought.

The Navy’s most advanced cryptographic machine work in WWII was building 125 U.S. versions of the British code breaking machine called the BOMBE. These electromechanical BOMBES were used to crack the ENIGMA, the cipher machine used by the Germans.

Designed by the Navy’s OPS-20-G team and built at National Cash Register (NCR) in Dayton, this same Computing Machine Lab would build ~25 other types of electromechanical and optical machines, some the size of a room with 3,500 tubes, to assist in breaking Japanese and German codes. By the end of the war the Naval Computing Machine Lab was arguably building the most sophisticated electronic machines in the U.S. However, none of these machines were computers. They had no memory, and both were “‘hard-wired” to perform just one task.

(Meanwhile in England the British code breaking group in Bletchley Park built Colossus, arguably the first digital computer. At the end of the War the British offered the Navy OPS-20-G code breaking group a Colossus but the Navy turned it down.)

Dual-Use Technology
As the war was winding down, the leadership of the Navy Computing Machine Lab in OPS-20-G was thinking about how they could permanently link commercial, academic and military computing science and innovation to the Navy. After discovering that no commercial company was willing to continue their wartime work of building the specialized hardware for codebreaking, the Navy realized they needed a new company. The decided that the best way to do that was to encourage a private for-profit company to spin out and build advanced crypto-computing systems.

The Secretary of the Navy gave his OK and three officers in the Navy’s code breaking group (Commander Howard Engstrom, who had been a math professor at Yale; Lieutenant Commander William “Bill” Norris, an electrical engineer; and their contracting officer Captain Ralph Meader,) agreed to start a civilian company to continue building specialized systems to help break codes. While unique for the time, this public-private partnership was in-line with the wartime experiment of Vannevar Bush’s OSRD – using civilians in universities to develop military weapons.

Why Minneapolis/St. Paul?
While it seemed like a good idea and had the Navy’s backing, the founders got turned down for funding by companies, investment bankers and everyone, until they talked to John Parker.

Serendipity came to Minneapolis-St. Paul when the Navy team met John Parker. Parker was a ex Naval Academy graduate and a Minneapolis businessman who owned a glider manufacturing company and was well connected in Washington. Parker agreed to invest. In January 1946, they founded Engineering Research Associates (ERA). Parker became President, and got 50% of the company’s equity for a $20,000 investment (equal to $315K today) and guaranteed a $200,000 line of credit (equal to $3M today). The professional staff owned the other 50%. The new company moved into Parker’s glider hanger. Norris became the VP of Engineering, Engstrom the VP of Research, and Meader VP of Manufacturing.

The company hit the ground running. 41 of the best and brightest ex-Navy technical team members of the Naval Computing Machine Lab in Dayton moved and became the initial technical staff of ERA. When the Navy added their own staff from the Dayton Laboratory the ERA facility was designated a Naval Reserve Base and armed guards were posted at the entrance. The company took on any engineering work that came their way but were kept in business developing new code-breaking machines for the Navy. Most of the machines were custom-built to crack a specific code, and increasingly used a new ERA invention – the magnetic drum memory to process and analyze the coded texts.

ERA’s headcount grew rapidly. Within a year the company had 145 people. A year later, 420. And by 1949, 652 employees and by 1955, 1400.  Sales in their first fiscal year were $1.5 million ($22 million in today’s dollars).

During World War II the demands of war industries caused millions more Americans to move to where most defense plants located. Post-war era Americans were equally mobile, willing to move where the opportunities were. And if you were an engineer who wanted to work on the cutting edge of electronics, and electromechanical systems, ERA in Minneapolis-St. Paul was the place to be. (Applicants were told that ERA was doing electronics work for government and industry. Those who wanted more detail were given a number of cover stories. Many were told that ERA was working on airline seat reservation systems.)

How Did ERA Grow So Quickly?
The Navy thought of ERA as its “captive corporation.” From the first day ERA started with contracts from the Navy OPS-20-G codebreaking group. ERA built the most advanced electronic systems of the time. Unfortunately for the company they couldn’t tell anyone as their customer was the most secret government agency in the country – the National Security Agency.

ERAs systems were designed to solve problems defined by their Navy code-breaking customer. They fell into two categories: some projects were designed to automate existing workflows of decoding known ciphers; others were used to discover breaks into new ciphers. And with the start of the Cold War, that meant Soviet cryptosystems. ERAs cryptanalytic devices were most often designed to break only one particular foreign cipher machine (which kept a stream of new contracts coming.) The specific purpose and target of each of these systems with colorful codenames are still classified.

What Did ERA Build For the National Security Agency (NSA)?

By the end of ERA’s first year, ERA had contracts for a digital device called Alcatraz which used thousands of vacuum tubes and relays. A contract for a system named O’Malley followed. Then two “exhaustive trial” systems called Hecate for $250,000 ($3.2 million in today’s dollars) and the follow-on system, Warlock ($500,000 – $6.4 million today.) Warlock was so large that it was kept at the ERA factory and operated as a remote operations center.

Next were the Robin machines, a photoelectric comparator, used to attack the Soviet Albatross code. The first two were delivered in the end of 1950. Thirteen more were delivered to NSA over the next two years.

ERA Disk Drives
One of the problems code breakers had was the difficulty of being able to store and operate on large sets of data. To do so, cryptanalysts used thousands of punched cards, miles of paper tapes and microfilm. ERA was the pioneer in the development of an early form of disk drives called magnetic drum memories.

ERA used these magnetic drums in the special systems they built for NSA and later in their Atlas computers. They also sold them as peripherals to other computer companies.

Goldberg, which followed, was another room-sized special purpose machine – a comparator with statistical capabilities – that took photoelectric sensing and paper tape scanning to new heights.

Costing $250,000 ($3.2 million in today’s dollars), it had 7,000 tubes and was one of the first Agency machines to use a magnetic drum to store and handle data.

Another similarly sized system, Demon, followed. It was a dictionary machine designed to crack a Soviet code. It also used 34-inch-diameter magnetic drum to perform a specialized version of table lookup. Three of these large systems were delivered.

ERA engineers operated at the same relentless and exhausting pace as they had done in war time – similar to how Silicon Valley silicon and computer companies would operate three decades later.

For the next decade ERA would continue to deliver a stream of special-purpose code breaking electronic systems and subsystems for the Navy cryptologic community. (These NSA documents give a hint at the number and variety of encryption and decryption equipment at NSA in the early 1950’s: here, here, here, here, and here.)

ERA was undercapitalized and always looking for other products to sell. At the same time ERA was building systems for the NSA they pursued other lines of businesses; research studies on liquid fueled rockets, aircraft antenna couplers (which turned into a profitable product line,) a Doppler Miss Distance Indicator, Ground Support Equipment (GSE) for airlines, and Project Boom to produce instrumentation for what would become  underground nuclear tests. A 1950 study for the Office of Naval Research called High-Speed Computing Devices – a survey of all computers then existent in the U.S. As there was no single source of information about what was happening in the rapidly growing computer field, this ERA report became the bible of early U.S. computers.

The Holy Grail – A Digital Computer for Cryptography?
As complicated as the ERA machines were, they were still single function machines, not general purpose computers. But up until 1946 no one had built a general purpose computer.

With the war over what the Navy OP-20-G’s and Army SIS computing wizards really wanted was to create a single machine that could perform all the major cryptanalytic functions. The most important of the crypto techniques were based upon either locating repeated patterns, tallying massive numbers of letter patterns, and recognizing plain text, or performing some form of “exhaustive searching.”

How the NSA Got Their First Computers

Their idea was to put each of these major cryptanalytic functions in separate, dedicated, single-function hardware boxes and connect them through a central switching mechanism. That would allow cryptanalysts to tie them together in any configuration; and hook it all to free-standing input/output mechanisms. With a stock of these specialized boxes the agencies believed they could create any desired cryptanalytic engine.

Just as the consensus for this type of architecture was coalescing, a new idea emerged in 1946 – the concept of a general purpose digital computer with a von Neumann architecture. In contrast to having many separate hardwired functions, a general purpose computer would have just the four basic arithmetic ones (add, subtract, multiple and divide) along with a few that allowed movement of data between the input-output components, memory, and a single central processor. In theory, one piece of hardware could be made to imitate any machine through an inexpensive and easily changed set of instructions.

Opponents to the project believed that a von Neumann design would always be too slow because it had only a single processor to do everything. (This debate between dedicated special purpose hardware versus general purpose computers continues to this day.)

The tipping point in this debate happened in 1946 when an OPS-20-G engineer went to the Moore School’s 1946 summer course on computers. The Moore School’s computer group had just completed the ENIAC, arguably the first programmable digital computer, and they were beginning to sketch the outlines of their own new computer, the UNIVAC the first computer for business applications. The engineer came back to the Navy computing group an advocate for building a general-purpose digital computer for codebreaking having convinced himself that most cryptanalysis could be performed through digital methods. He prepared a report to show that his device would be useful to everyone at OP-20-G. The report remained Top Secret for decades.

The report detailed how a general-purpose machine could have successfully attacked the Japanese Purple codes as well as German Enigma, and Fish systems, and how it would be usefully against the current Soviet and Hagelin systems.

This changed everything for the NSA. They were now in the computer business.

ERA’s ATLAS
In 1948 the Navy gave ERA the contract to produce its first digital computer called ATLAS to be used by OPS-20-G for codebreaking.

Twenty four months later, ERA delivered the first of two 24-bit ATLAS I computers. The Atlas was 45’ wide and 9’ long. It weighed 16,000 pounds and was water cooled. Each ATLAS I cost the NSA $1.3 million ($16 million in today’s dollars).

In hindsight, the NSA crossed the Rubicon when the ATLAS I arrived. Today, an intelligence agency without computers is unimaginable. Its purchase showed incredible foresight and initiated a new era of cryptanalysis at the NSA. It was one of the handful of general purpose, binary computers anywhere. Ten years later the NSA would have 53 computers.

ERA asked the NSA for permission to offer the computer for commercial sale. The NSA required ERA to remove instructions that made the computer efficient for cryptography, and that became the commercial version – the ERA 1101 announced in December 1951. It had no operating or programming manual and its input/output facilities was a typewriter, a paper tape reader, and a paper tape punch. At the time, no programming languages existed.

ERA had delivered a breakthrough computer without having an understanding of its potential application or what a customer might have to do to use the machine. In search of commercial customers, ERA set up a ERA 1101 computer in Washington and offered it to companies as a remote computing center. As far as the commercial world knew ERA was a startup with no real computing expertise and this was their first offering. In addition, the only people with experience in writing applications for the 1101 were hidden away at NSA, and ERA was unable to staff the Arlington office to create programs for customers. Finally, ERA’s penchant for extreme secrecy left them unschooled in the art of marketing, sales, and Public Relations. When they couldn’t find any customers they donated the ERA 1101 to Georgia Tech.

With their hands on their first ever general purpose digital computer, the Navy and ERA rapidly learned what needed to be improved. ERA’s follow-on computer, the ATLAS II was a 32-bit system with additional instruction extensions for cryptography. Two were delivered to NSA between 1953 and 1954. ATLAS II cost the NSA $2.3 million ($35 million today.)

Late in 1952, a year before the ATLAS II was delivered to the NSA, ERA told Remington Rand (who now owned the company) the ATLAS II computer existed (and the government had paid for its R&D costs) and it was competitive with the newly announced IBM 701. When the ATLAS II was delivered to the NSA in 1953 they again asked for permission to sell it commercially (and again had to remove some instructions) which turned the Atlas II into the commercial ERA/Univac 1103. (see its 1956 reference manual here.)

This time with Remington Rand’s experience in sales and marketing, the computer was a commercial success with about twenty 1103s sold.

ERA’s Bogart
In 1953, with the ATLAS computers in hand, the Navy realized that a smaller digital computer could be used for data conversion and editing, and to “clean up” raw data for input to larger computers. This was the Bogart.

Physically Bogart was a “small, compact” (compared to the ATLAS) computer that weighed 3,000 pounds and covered 20 square feet of floor space. To get a feel of how insanely difficult it was to program a 1950’s computer take a look at the 1957 Bogart programming manual here.) The Bogart design team was headed by Seymour Cray. ERA delivered five Bogart machines to NSA.

Seymour Cray would reuse features of the Bogart logic design when he designed the Navy Tactical Data System computers, the UNIVAC 490 and the Control Data Corporation’s CDC 1604 and CDC 160.

By 1953, 40% of the University of Minnesota electrical engineering graduates – including Cray –  were working for ERA.

The End of an ERA
By 1952, the mainframe computer industry was beginning to take shape with office machine and electronics companies such as Remington Rand, Burroughs, National Cash Register, Raytheon, RCA and IBM. Parker, still the CEO, realized that the frantic chase of government contracts was unsustainable. (The relationship with the NSA’s procurement offices now run by Army staff, had become so strained that the Navy Computing Lab was unable to get an official letter of thanks sent to ERA for having developed the ATLAS.)

Parker calculated that ERA needed $5 million to $10 million ($75 to $150 million in today’s dollars) to grow and compete with the existing companies in the commercial computing market. Even after the NSA took over the cryptologic work of OPS-20-G the formal contracts with ERA were done through the Navy’s Bureau of Ships. NSA was known as No Such Agency and on paper its relationship with ERA didn’t exist. As far as the public knew, ERA’s products were for “the Navy.” Given that ERA’s extraordinary technical work was unknown to anyone other than the NSA, Parker didn’t think he could raise the money via a public offering (venture capital as we know it didn’t exist.)

Instead, in 1952, Parker sold ERA to Remington Rand (best known for producing typewriters) for $1.7M (about $12M in today’s dollars.) A year earlier, Remington Rand had bought Eckert-Mauchly – one of the first U.S. commercial computer companies – and its line of UNIVAC computers. They wanted ERA to get its government customers. ERA remained a standalone division. The ERA 1101 and 1103 became a part of the UNIVAC product line.

Parker became head of sales of the merged computer division. He left in 1956 and years later he became chairman of the Teleregister Corporation, the predecessor to Bunker-Ramo. He went on to become a director of several companies, including Northwest Airlines and Martin Marietta.

Remington Rand itself would be acquired by Sperry in 1955 and both ERA and Eckert–Mauchly were folded into a computer division called Sperry-UNIVAC. Much of ERA’s work was dropped, while their drum technology was used in newer UNIVAC machines. In 1986 Sperry merged with Burroughs to form Unisys.

Epilogue
For the next 60 years the NSA would have the largest collection of commercial computers and computing horsepower in the world. They would continue to supplement those with dedicated special purpose hardware.

The reorganization of American Signals Intelligence, leading to the creation of the Armed Forces Signals Agency (AFSA) in 1949, then the NSA in 1952, contributed to the demise of the special relationship between ERA and the code- breakers. The integration of the Army and Navy brought a shift in who made decisions about computer purchasing. NSA inherited a computer staff from the Army side of technical SIGINT. They had different ties and orientations than the few remaining old Navy hands. As a result, the new core NSA group did not protest when the special group that integrated Agency and ERA work was disbanded. The 1954 termination of the Navy Computing Machine Lab in St. Paul went almost unnoticed.

But the era of Minnesota’s role as a scientific computing and innovation cluster wasn’t over. In fact, it was just getting started. In 1957 ERA co-founder William Norris, and Sperry-Univac engineers Seymour Cray, Willis Drake, and ERA’s treasurer Arnold Ryden, along with a half dozen others, left Sperry-Univac and teamed up with three investors to form a new Minneapolis-based computer company: Control Data Corporation (CDC). For the next two decades Control Data would build the fastest scientific computers in the world.

More in part 2 of The Secret History of Minnesota

Even the Smartest VCs Sometimes Get it Wrong – Bill Gurley and Regulated Markets

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 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

Leaving Government for the Private Sector – Part 2

Laura Thomas is a former CIA operations officer. Reading how she moved in 2021 from CIA ops to a quantum technology company offered insightful career transition advice for those leaving her agency. Most of her lessons were applicable to any government employee venturing out to the private sector.

Below is the second of her three-part series. Read part one here.


Before leaving government service one of my biggest challenges was to understand how my skill as a Case Officer would translate into a job in the commercial world. I had to spend a lot of time learning a new language and new job descriptions. Here’s what I learned.

What would you like to do/can do? Some commercial company roles:

Business Development or “BD” roles: Case Officers are well suited for business development (BD) roles as its akin to first half of the CIA recruitment cycle. In a business development role you’re out shaping the perception of your company in the market (networking), determining leads, and contacting leads. The larger the company, the more they’ll separate out business development and sales, with business development focused primarily on lead generation and sales focused on sealing the actual sale of the product or service.

Sales roles: The sales cycle is similar to the recruitment cycle of a source. At a small company, you have the ability to do the whole sales cycle, which integrates strategy, business development, sales, and customer success: figure out what you should sell, who you should sell it to, how to get in touch with them, actually get in touch with them, sell it, keep selling to them and make sure they’re happy (customer success), and at some point, decide whether to move on to better sales targets, or convince your company they need to be selling something different. At a large company, sales usually means someone else has done the broad shaping for a potential customer. You just have to go in and work through the mechanics of selling them on your product or service.

Customer Success roles: This is akin to handling a source. You make sure the customer is happy and keeps buying, preferably more.

Security roles: Some ex-Agency people gravitate to roles in security. I discovered that while I know a lot about tradecraft-related security and how to stay alive for the first minutes of an ambush, I know little about building security and computer systems security. Some companies will see your CIA background and confuse it with roles that are more akin to FBI or law enforcement. If you worked in an actual cybersecurity or security role, you can learn it and integrate well into those teams.

Trust and Safety roles, Threat and Business Intelligence roles: If you’ve been a targeter and/or an analyst these might be good fits. The role broadly is to protect a company and its people/users (or multiple companies) by tracking bad actors and threats. In large companies these roles report to a security division (however there are entire companies  just providing Threat and Business Intelligence).

Government Affairs/Legislative Affairs roles: Large companies pay to have people represent them on Capitol Hill and advocate for their interests. If you have significant experience engaging with and briefing the Hill, this is a possibility, however you’ll be competing against staffers rotating off committees who are actually much better equipped than you as far as networking and know-how. You may be able to join a larger company’s government affairs team at a more junior to mid-level, and you’ll probably find your skills most relevant to a company that works on national security-related issues.

At first many start-ups hire a lobbying firm. You may be able to step in once they want to transition into an in-house role for this, but keep in mind that they’re looking for the Capitol Hill contacts you already have, as well as your ability to work the legislative process, not just your briefing or networking skills.

Strategy and Operations roles: These roles help make sure vision, resources (budgets and people), and the market opportunity are aligned. Working closely with the CEO or CFO, they help figure out what to do to make things go right, and what to do when things go wrong. The smaller the company, the bigger your chance at a role like this.

Chief of Staff role, for example, is largely a strategy role, but is heavily dependent on the needs of the CEO/company. In my case, at Infleqtion I’m the person who tells our CEO what he needs to hear, not necessarily what he wants to hear. I also serve as an executive advisor – from product strategy to setting business milestones to working with investors. I also work closely with all members of the executive team, the Board of Directors, and Advisory Board. I think this role is ideal for a former Case Officer, but I’m obviously biased.

Larger companies hiring a Chief of Staff often look for someone who has an MBA, experience with one of the big consulting firms, or experience doing the job already.

Entrepreneur: A successful CIA case officer must be able to operate amid ambiguity and make judgment calls that require strong second- and third-order thinking. Achievement-focused and good storytellers, they know how to figure things out, “read the room,” and assess and mitigate risk. Most people believe case officers and entrepreneurs are big risk takers, when, in fact, they’re risk mitigators.

If you find an A-player CIA officer jumping into a founder role mid-way in their career (or decide to start something yourself,) they’ll probably go on to do great things. They have enough confidence in themselves to leave without the safety net of a future pension as well as the energy, ambition, and know-how to navigate uncertainty. The same Emotional Quotient and approach that attracts investors will also attract excellent employees.

Venture Capitalist: An early-stage VC requires some of the same skills as a Case Officer – spotting, assessing, developing, recruiting, and handling founders building a company amid an uncertain operating environment that will bring a heavy return on investment. (However, many VCs have also accrued years/decades as domain experts in the technologies/and or industries they invest in.) Being a successful VC and successful case officer both involve some levels of luck and timing misattributed to skill. The biggest difference is in the VC world, nobody is going to die.

If you’re a Retiree leaving with a full pension – you have different choices than a “job.” You can:

  • consult
  • sit on a company Advisory Board or Board of Directors
  • serve as a senior executive at a small company (you’ll be expected to actually work, not pontificate and delegate) or mid- to senior level at a larger company (you might just be a face)
  • get hired by Wall Street/Private Equity/VC firms assuming you’re senior enough and have enough New York or Silicon Valley connections

For 2-4, you’re generally being hired for your name and the introductions you can make assuming you’re within the top 15 of leadership.

Boards: The term “board” can mean two very different things in the commercial world – an Advisory Board versus a Board of Directors. An Advisory Board provides advice. It has no legal role in the company. Often companies will put you on their advisory board just to use your name and image (and not really want your advice). Every company can organize and compensate its advisory board any way it likes. Some Advisory Boards meet once a quarter, others once a year. Advisory Board members may field weekly to monthly emails and calls from the company executive team to provide feedback on strategy and positioning and make introductions. Advisory Board members are often paid in a balance of equity (stock options) and cash (“cash” is the industry term for money wired to your bank account).

A Board of Directors has a formal and legal role. It provides governance and financial oversight to the company. They can vote to hire and fire the CEO. CEOs seek their advice (and often must seek their formal approval) for major strategic decisions such as acquisitions, major budget changes, hiring of C-level executives, etc.) Formal Board positions are harder to come by. If you’re an A-player from the senior-most ranks, consider joining a private company board if you’re aligned with their mission and team. They need you.

For me, personally: People in the senior ranks at startups usually call themselves operators. Obviously, that’s a different definition of the term. I knew I wanted to stay/go into an operator role because that’s where the business learning I sought would happen. I didn’t want to have to sell back into the intelligence community, because I didn’t want to leverage my contacts so tactically, but plenty of people do it (and we need good people to do it. We all know how badly the government needs commercial technology solutions). From the start, my job was closest to a business development role. Because it was a small company and I was going from top-down with the CEO rather than responding to a job advertisement, I was able to craft my function and initial title as, “Senior Director of National Security Solutions.” I began writing unsolicited strategy docs for the CEO. This ultimately led me into a strategy role, which led me into a strategy and fundraising role. I also took an advisory role with another startup working on national security technology, QuSecure.

Where should you go? Big company or small?  Choose big for stability and higher salaries. Choose small for learning, growth, and impact. In large companies, they usually want you in a narrow and specific role. However, you will have more roles you could move into if the first one isn’t a great fit. If you join a big company, assuming it’s public, you’ll get stock which immediately can translate into financial gains assuming the company performs well. The salaries are almost always higher. You can get rich in a big company (at least by our humble government standards), but rarely wealthy based on returns from that company alone.

At small companies, you wear many hats at once. I wanted to understand the daily challenges a company faced at the senior levels in trying to push a new technology in government markets and commercial markets, and how capital flows impacted all of this. However, a bigger company is more defined in terms of a 9-to-5. I work just as much now as I did in the field. And though I work from an office most days, I also work from home, which affords a lot of flexibility because I’m not chained to a SCIF.

You can get wealthy with the right startup, but many startups fail, so it’s a long shot. Of course, “wealth” is subjective. More than money, most of us crave impact. Both are possible on the outside.

How should you think about and mitigate risk if joining a startup? Know your appetite for risk. If you’re really bold, join an early-stage company (seed stage, Series A), but have conviction about the team. You may need to cover some portion of your own salary for a year. If you need to make a salary equivalent to what you make in government, target startups that have closed a Series B round within the last few months. If you’ve received a formal offer from a startup, ask how much runway (months of cash left) they have. If they won’t discuss any aspects of runway or value of the equity package they’re offering, look elsewhere.

Look before you leap. Talk with multiple employees at the company. Try to talk with an investor in the company. Research their Board of Directors and Advisory Board members and contact some of them. Look for people on LinkedIn who used to work at the company, reach out to them and ask why they left.

Being part of a “failed” startup is not a badge of dishonor. Most startups fail, especially those in the early stages. So long as you and the company weren’t operating unethically and illegally, it’s not a red flag on your resume. In fact, this sort of experience matters far more to the next prospective tech startup employer than the decade+ that you put in at the Agency.

Action:

A) If you’re an A-player, stay in government.
B) If you’re an A-player and leave, do great things on the outside and return to government service at some point.

Coming up next:

  • Part III – title, compensation (salary + equity + bonuses) and resources you can use.

Read the rest of Laura’s blogs at https://www.lauraethomas.com/

Leaving Government for the Private Sector – Part 1

Laura Thomas is a former CIA operations officer. Reading how she moved in 2021 from CIA ops into a quantum technology company offered insightful career transition advice for those leaving her agency. Most of her lessons were applicable to any government employee venturing out to the private sector.
Below is the first of her three-part series.

—-

At least a few times a month, people looking to jump ask about my transition, which has led to me consolidating my answers below. To be up front, some of what I write will be controversial and all of it is biased. Due to length, I’ve broken it up into a three-part series.


Is it really a big jump to the private sector? It wasn’t a big jump. At the Agency, 85% of my time was spent navigating bureaucracy and equities, arguing for resources and permission for operations, and dealing with the bottom rung of employees, all while making decisions with little data or data overload. Only 15% of my time was doing the more exciting operations. Though that 15% – along with the camaraderie of some of my colleagues – made the work deeply meaningful.

Industry is similar. Human nature is human nature, and I deal with many of the same challenges and pull many of the same levers of satisfaction. The difference is my decisions now aren’t life or death.

Another large difference is the greater level of autonomy I now have. Making decisions on the fly in operations is an extreme example of autonomy, of course, but there is always a back-end overhead. Depending on company culture, decision-making can be driven dramatically down with less overhead. As an example, I can make direct recommendations to Congress with no oversight, no internal reporting requirements, and with the trust of the CEO and Board.

Do you miss it? Yes. Nothing beats the rush of bumping a target who agrees to meet with you again or landing in a foreign country for the first time. I no longer know the stories behind the headlines, and I’m not the person making those stories happen. Aside from close friends, I am now treated as an “outsider” by former colleagues.

Fortunately, I still work with smart people solving hard problems every day. And there is still meaning in what I do. Raising tens of millions of dollars from investors to advance a technology faster than the Chinese Communist Party uses the same skillset. Learning how M&A deals are structured gives me the same thrill as first learning the mechanics of a surveillance detection route. It’s the excitement of being a beginner again, but one with deep and profound experiences, which blunts the downs and enhances the ups that you will face post-Agency.

Today, I get to move our national security mission in emerging technologies farther and faster in ways that I could not in government. And while there is some level of self-justification in these statements, there is nonlinearity in industry. You can move at exponential speed.

How do you transfer your old skills to your current role? Driving decisions, organizational change, and operations in a deep tech company presents many of the same challenges and opportunities as my time in government. Leading and managing people amid uncertainty, high degrees of change, and making decisions remain my day-to-day functions. My current role as a Chief of Staff is in many ways like a DCOS (deputy chief of station) or a traditional Chief of Staff in government. I work behind the scenes, and sometimes out front, to shape our company vision, strategy and then execute, measure, and refine. (Rather than giving away bags of cash in my old job, I now ask for money from investors.)

Relationship dynamics are the same, minus the burden of extreme secrecy. All the things that most of the outside world doesn’t understand as being critical to a handler-asset relationship are just as critical to relationships in industry. Judgment remains paramount.

In the Agency I dealt with a few difficult personalities focused on empire-building and metrics rather than running sound operations. You likely will still deal with this in industry, though there are far fewer layers and entrenched interests to deal with. Knowing how to navigate various stakeholders and interests, avoid landmines, and bring people together is an extremely useful skill in industry. If you’ve been a “doer” who knows how to communicate, work, and gain buy-in across an enterprise that is geographically dispersed, as well as with and against external third parties who are frenemies (or outright hostile), this will serve you well in industry. Talk about it when you’re seeking jobs and interviewing.

Did you make any resume missteps? Most often your resume is not what will get you a job, and submitting one to a recruiter or resume bank is not the right move. Odds are your resume is almost certainly written in government-speak, and probably more terrible than you realize. It likely talks about all the jobs you held (to the degree you can share) and the dates and maybe the general locations but says nothing about what you actually accomplished or how it specifically relates to industry. You probably won’t even get beyond the AI filter.

Having a resume that says you served in country X and wrote reports that went to policymakers, and “the President,” might get you a curiosity interview, but won’t get you a job. Unless you can translate how your skills provide commercial value, you won’t get hired.

For starters, first figure out which industry you want to work in, narrow it down, and work hard to get intros at the senior levels to a handful of companies (Board of Directors member, Advisory Board member, member of the C-suite (CEO, CTO, CFO, etc), and/or investor.) You have to do a lot of networking to create your list and build your network. Find a way to meet and captivate them with a story of what you did, and how your skills can transfer this to industry and add value to their company.

An early learning point for me came as I was speaking with a prospective VC about a job. He flat-out told me he didn’t understand my value to the company. He asked point blank, “How much money did you net the U.S. Government over your career, what exactly did you do in order to get those results, and how would you bring me those same returns?”

You will get asked a question like this.

My suggestion is to say something along these lines: “It’s exponentially harder to be hired by the Agency than it is to get into Harvard, and not only was I hired based on an assessment of my judgment and the ability to operate in ambiguous situations, I then was trained to do just that, and then did it for years.

I was entrusted to create and carry out some of the most sensitive and most important missions that the U.S. Government conducts, often with little direction. Not only did I have to plan and do them, I had to do so in secret, with lives on the line, which is hard to put a price tag on.

You can give me your toughest problem, and I will figure out how to solve it in record time with buy-in from those whom you rarely get buy-in, and position you for multiple shots on goal for future opportunities because I will have your company and sector wired. I can do for you what I did for our country: evaluate opportunity, mitigate risk, and make quick and smart decisions that attack problems differently than a typical insider would. I’ll turn my salary into millions of dollars in returns or investments within two years – not singlehandedly – but in a cooperative way that leverages many parts of the company. We’ll row in unison and we’ll row in the right direction.”

How did you get your current job? I networked nonstop and ran a full targeting campaign for multiple companies to get to their CEOs. I didn’t have a resume when I was looking for jobs. I had to find senior people who had left the agency who would vouch for me.

For my current company Infleqtion, I was introduced to a former senior Intelligence Community official who previously served on a board with the CEO, who made an introduction. When we met I asked the CEO his challenges and outlined how I might be able to help. Five months later, the CEO called and said he may have a job for me and invited me to visit and speak with others in the company for their input. I received an offer shortly thereafter.

Meanwhile, three years before I left the Agency I had done a cold outreach on LinkedIn to the person I suspected was the hiring manager for a job advertisement for a company that I liked. The person told me they wanted someone with more business experience for the role, but then came calling three years later when another role opened that they thought would be a good fit. Ultimately, I met each layer up in that company including the CEO.

This all came in handy when negotiating salary, title, and function. From the many, many hours of networking hustle, I received two job offers, which happened in parallel, and I negotiated around the same title and compensation levels. Throughout the entire process, I forwarded them relevant articles and commentary on opportunities to demonstrate my value. Ultimately, I chose Infleqtion because of its mission, its people, and its reputation amid US Government circles.

Action: A) If you’re an A-player, stay in government. B) If you’re an A-player and leave, do great things on the outside and return to government service at some point.

Coming up next:

•  Part II – what are the criteria for choosing your next role, the most common types of business roles that formers go into, and how to think about big vs small company risks and current markets.

•  Part III  – title, compensation (salary + equity + bonuses) and resources you can use.

Read the rest of Laura’s blogs at https://www.lauraethomas.com/

Profound Beliefs

This post previously appeared in EIX.

In the early stages of a startup your hypotheses about all the parts of your business model are your profound beliefs. Think of profound beliefs as “strong opinions loosely held.”

You can’t be an effective founder or in the C-suite of a startup if you don’t hold any.

Here’s how I learned why they were critical to successful customer development.


I was an aggressive, young and a very tactical VP of marketing at Ardent, a supercomputer company – who really hadn’t a clue about the relationship between profound beliefs, customer discovery and strategy.

One day the CEO called me into his office and asked, “Steve I’ve been thinking about this as our strategy going forward. What do you think?” And he proceeded to lay out a fairly complex and innovative sales and marketing strategy for our next 18 months.  “Yeah, that sounds great,” I said. He nodded and then offered up, “Well what do you think of this other strategy?” I listened intently as he spun an equally complex alternative strategy. “Can you pull both of these off?” he asked looking right at me.  By the angelic look on his face I should have known that I was being set up. I replied naively, “Sure, I’ll get right on it.”

Ambushed
Decades later I still remember what happened next. All of a sudden the air temperature in the room dropped by about 40 degrees. Out of nowhere the CEO started screaming at me, “You stupid x?!x. These strategies are mutually exclusive. Executing both of them would put us out of business. You don’t have a clue about what the purpose of marketing is because all you are doing is giving engineering a list of feature requests and executing a series of tasks like they’re like a big To Do list. Without understanding why you’re doing them, you’re dangerous as the VP of Marketing, in fact you’re just a glorified head of marketing communications.  You have no profound beliefs.”

I left in a daze, angry and confused. There was no doubt my boss was a jerk, but I didn’t understand the point. I was a great marketer. I was getting feedback from customers, and I’d pass on every list of what customers wanted to engineering and tell them that’s the features our customers needed. I could implement any marketing plan handed to me regardless of how complex. In fact I was implementing three different ones. Oh…hmm… perhaps I was missing something.

I was executing a lot of marketing “things” but why was I doing them? The CEO was right. I had approached my activities as simply a task-list to get through. With my tail between my legs I was left to ponder: What was the function of marketing in a startup? And more importantly, what was a profound belief and why was it important?

Hypotheses about Your Business Model = Your Profound Beliefs Loosely Held
Your hypotheses about all the parts of your business model are your profound beliefs. Think of them as strong opinions loosely held. You can’t be an effective founder or in the C-suite if you don’t have any.

The whole role of customer discovery and validation outside your building is to inform your profound beliefs. By inform I mean use the evidence you gather outside the building to either validate your beliefs/hypotheses, invalidate or modify them.  Specifically, what beliefs and hypotheses?  Start with those around product/market fit – who are your customers and what features do they want? Who are the payers? Then march through the rest of the business model. What price will they pay? What role do regulators pay? Etc. The best validation you can get is an order. (BTW, if you’re creating a new market, it’s even OK to ignore customer feedback but you have to be able to articulate why.)

The reality of a startup is that that on day one most of your beliefs/hypotheses are likely wrong. However, you will be informed by those experiments outside the building, and data from potential customers, partners, regulators, et al will modify your vision over time.

It’s helpful to diagram the consequences between hypotheses/ beliefs and customer discovery. (See the diagram)

If you have no beliefs and haven’t gotten out of the building to gather evidence, then your role inside a new venture is neutral. You act as a tactical implementer as you add no insight/or value to product development.

If you’ve gotten out of the building to gather evidence but have no profound beliefs to guide your inquiries, then your role inside a new venture is negative. You’ll collect a laundry-list of customer feature requests and deliver them to product development, without any insight. This is essentially a denial of service attack on engineering’s time. (I was mostly operating in this box when I got chewed out by our CEO.)

The biggest drag on a startup is those who have strong beliefs but haven’t gotten out of the building to gather evidence. Meetings become opinion contests and those with the loudest voices (or worse “I’m the CEO and my opinion matters more than your facts”) dominate planning and strategy.  (They may be right, but Twitter/X is an example where Elon is in the box on the bottom right of the diagram. )

The winning combination is strong beliefs that are validated or modified by evidence gathered outside the building. These are “strong opinions loosely held.”

Strategy is Not a To Do List, It Drives a To Do List
It took me awhile, but I began to realize that the strategic part of my job was to recognize that (in today’s jargon) we were still searching for a scalable and repeatable business model. Therefore my job was to:

  • Articulate the founding team’s strong beliefs and hypotheses about our business model
  • Do an internal check-in to see if a) the founders were aligned and b) if I agreed with them
  • Get out of the building and test our strong beliefs and hypotheses about who were potential customers, what problems they had and what their needs were
  • Test product development’s/engineering’s beliefs about customer needs with customer feedback
  • When we found product/market fit, marketing’s job was to put together a strategy/plan for marketing and sales. That should be easy. If we did enough discovery customers would have told us what features were important to them, how we compare to competitors, how we should set prices, and how to best sell to them

Once I understood the strategy, the tactical marketing To Do list (website, branding, pr, tradeshows, white papers, data sheets) became clear. It allowed me to prioritize what I did, when I did it and instantly understand what would be mutually exclusive.

Lessons Learned

  • Profound beliefs are your hypotheses about all the parts of your business model
    • No profound beliefs but lots of customer discovery ends up as a feature list collection which is detrimental to product development
    • Profound beliefs but no customer discovery ends up as opinion contests and those with the loudest voices dominate
  • The winning combination is strong beliefs that are validated or modified by evidence gathered outside the buildingThese are “strong opinions loosely held.”