Category: Technology

“Only the Paranoid Survive”
Andy Grove – Intel CEO 1987-1998

I just had an urgent “can we meet today?” coffee with Rohan, an ex-student. His three-year-old startup had been slapped with a notice of patent infringement from a Fortune 500 company. “My lawyers said defending this suit could cost $500,000 just for discovery, and potentially millions of dollars if it goes to trial. Do you have any ideas?”

The same day, I got a text from Jared, a friend who’s running a disruptive innovation organization inside the Department of Defense. He just learned that their incumbent R&D organization has convinced leadership they don’t need any outside help from startups or scaleups.

Sigh….

Rohan and Jared have learned three valuable lessons:

• Only the paranoid survive (as Andy Grove put it)
• If you’re not losing sleep over who wants to kill you, you’re going to die.
• The best fight is the one you can avoid.

It’s a reminder that innovators need to be better prepared about all the possible ways incumbents sabotage innovation.

Innovators often assume that their organizations and industry will welcome new ideas, operating concepts and new companies. Unfortunately, the world does not unfold like business school textbooks.

Whether you’re a new entrant taking on an established competitor or you’re trying to stay scrappy while operating within a bigger company here’s what you need to know about how incumbents will try to stand in your way – and what you can do about it.

Entrepreneurs versus Saboteurs
Startups and scaleups outside of companies or government agencies want to take share of an existing market, or displace existing vendors. Or if they have a disruptive technology or business model, they want to create a new capability or operating concept – even creating a new market.

As my student Rohan just painfully learned, the incumbent suppliers and existing contractors want to kill these new entrants. They have no intention of giving up revenue, profits and jobs. (In the government, additional saboteurs can include Congressional staffers, Congressman and lobbyists, as these new entrants threaten campaign contributions and jobs in local districts.)

Intrapreneurs versus Saboteurs
Innovators inside of companies or government agencies want to make their existing organization better, faster, more effective, more profitable, more responsive to competitive threats or to adversaries. They might be creating or advocating for a better version of something that exists. Or perhaps they are trying to create something disruptive that never existed before.

Inside these commercial or government organizations there are people who want to kill innovation (as my friend Jared just discovered). These can be managers of existing programs, or heads of engineering or R&D organizations who are feeling threatened by potential loss of budget and authority. Most often, budgets and headcount are zero-sum games so new initiatives threaten the status quo.

Leaders of existing organizations often focus on the success of their department or program rather than the overall good of the organization. And at times there are perverse incentives as some individuals are aligned with the interests of incumbent vendors rather than the overall good of the company or government agency.

How Do incumbents Kill Innovation?
Rohan and Jared were each dealing with one form of innovation sabotage. Incumbents use a variety of ways to sabotage and kill innovative ideas inside of organizations and outside new companies. And most of the time innovators have no idea what just hit them. And those that do – like Rohan and Jared – have no game plan in place to respond.

Here are the most common methods of sabotage that I’ve seen, followed by a few suggestions on how to prepare and defend against them.

Founders and Innovators should expect that existing organizations and companies will defend their turf – ferociously.

Common ways incumbents kill innovation in both commercial markets and government agencies.

• Create career FUD (fear, uncertainty and doubt). Positioning the innovative idea, product or service as risk to the career of whoever adopts or champions it.
• Emphasize the risk to existing legacy investments, like the cost of switching to the new product or service or highlighting the users who would object to it.
• Claim that an existing R&D or engineering organization is already doing it (0r can do it better/cheaper.)
• Create innovation theater by starting internal innovation programs with the existing staff and processes.
• Set up committees and advisory boards to “study” the problem. Appoint well respected members of the status quo.
• Poison funding for internal initiatives. Claiming that you’ll have to kill important program x or y to pay for the new initiative. Or funding the demo of the new idea and then “slow-walk” the budget for scale.
• Poison startup financing sources. Telling VCs the incumbents already own the market. Tell Government funders the company is out of cash.
• File Lawsuits/Protests against winners of contracts.
• Use patents as a weapon. Filing patent infringement lawsuits – whether true or not. Try to invalidate existing patents – whether true or not.
• Claim that employees have stolen IP from their previous employer.
• File HR Complaints against internal intrapreneurs for cutting corners or breaking rules.
• Isolate senior leadership from the innovators inside the organization via reporting hierarchy and controlling information about alternatives.
• Object to structures and processes for the rapid adoption of new technologies. Treat innovation and execution as the same processes. Lack tolerance for failure at innovation. Do not cultivate a culture of urgency. Don’t offer a a structured career path for innovators.
• Lock-up critical resources, like materials, components, people, law firms, distribution channels, partners and make them unavailable to innovation groups/startups.
• Control industry/government standards to ensure that they are lock-in’s for incumbents.
• Acquire a startup and shut it down or bury its product
• Poach talent from an innovation organization or company by convincing talent that the innovation effort won’t go anywhere.
• Influence “independent” analysts, market research firms with “research” contracts to prove that the market is too small.
• Confuse buyers and senior leadership by preannouncing products or products that never ship – vaporware.
• Bundle products (Microsoft Office)
• Long term lock-in contracts for commercial customers or sole-source for government programs (e.g. F-35).

How incumbents kill startups in government markets

• File contract appeals or protests, creating delays that burn cash for new entrants.
• File Inspector General (IG) complaints, claiming innovators are cutting corners, breaking rules or engaging in illegal hiring and spending. If possible, capture these IG offices and weaponize them against innovators.
• Hijack the acquisition system by creating requirements written for incumbents, while setting unnecessary standards, barriers and paperwork for new entrants. Ignore requirements to investigate alternate suppliers and issue contracts to the incumbents.
• Revolving door. The implicit promise of jobs to government program executives and managers and the implicit promise of jobs to congressional staffers and congressmen.
• Lobbying. Incumbents have dedicated staffs to shape requirements and budgets for their products, as well as dedicated staff for continual facetime in Washington. They are experts at managing the POM, PPBE, House and Senate Armed Services Committees  and appropriations committees.
• Create career risks for innovators attempting to gain support outside of official government channels, penalizing unofficial contacts with members of Congress or their staffs.
• Create Proprietary interfaces
• Weaponize security clearances, delaying or denying access to needed secure information, or even pulling your, or your company’s clearance.

How incumbents kill startups in commercial markets.

• Rent Seeking via regulatory bodies (e.g. FCC, SEC, FTC, FAA, Public Utility, Taxi/Insurance Commissions, School Boards, etc, …) Use government regulation to keep out new entrants who have more innovative business models (or delay them so the incumbents can catch up).
• Rent Seeking via local, state and federal laws (e.g. occupational licensing, car dealership laws, grants, subsidies, or tariff protection). Use arguments – from public safety, to lack of quality, or loss of jobs –  to lobby against the new entrants.
• Rent Seeking via courts to tie up and exhaust a startup’s limited financial resources.
• Rent Seeking via proprietary interfaces (e.g. John Deere tractor interfaces…)
• Legal kickbacks, like discounts, SPIFs, Co-advertising (e.g. Intel and Microsoft for x86 processors/Windows).
• State Attorney General complaints to tie up startup resources
• Create fake benchmark groups or greenwash groups to prove existing solution is better or that new solution is worse.

Innovators Survival Checklist

There is no magic bullet I could have offered Rohan or Jared to defend against every possible move an incumbent might make. However, if they had realized that incumbents wouldn’t welcome them, they (and you) might have considered the suggestions below on how to prepare for innovation saboteurs.

In both government and commercial markets:

• Map the order of battle. Understand how the money flows and who controls budget, headcount and organizational design. Understand who has political, regulator, leadership influence and where they operate.
• Understand saboteurs and their motivation. Co-opt them. Turn them into advocates – (this works with skeptics). Isolate them – with facts. Get them removed from their job (preferably by promoting them to another area.)
• Build an insurgent team. A technologist, visionary, champion, allies, proxies, etc. The insurgency grows over time.
• Avoid publicly belittling incumbents. Do not say, “They don’t get it.” That will embarrass, infuriate and ultimately motivate them to put you out of business.
• Avoid early slideware. Instead focus on delivering successful minimal viable products which demonstrate feasibility and a validated requirement.
• Build evidence of your technical, managerial and operational excellence. Build Minimal Viable Products (MVPs) that illustrate that you understand a customer or stakeholders problem, have the resources to solve it, and a path to deployment.
• If possible, communicate and differentiate your innovation as incremental innovation. Point out that over time it’s disruptive.
• Go after rapid scale of a passionate customer who values the disruption e.g. INDOPACOM; or Uber and Airbnb, Tesla in the commercial world
• Ally with larger partners who see you as a way to break the incumbents’ lock on the market. i.e. Palantir and the intelligence agencies versus the Army and in industry, IBM’s i2, / Textron Systems Overwatch.

In commercial markets:

• Figure out an “under the radar” strategy that doesn’t attract incumbents’ lawsuits, regulations or laws when you have limited resources to fight back.
• Patent strategy. Build a defensive patent portfolio and strategy? And consider an offensive one, buying patents you think incumbents may infringe.
• Pick early markets where the rent seekers are weakest and scale. For example, pick target markets with no national or state lobbying influence. i.e. Craigslist versus newspapers, Netflix versus video rental chains, Amazon versus bookstores, etc.
• When you get scale and raise a large financing round, take the battle to the incumbents. Strategies at this stage include hiring your own lobbyists, or working with peers in your industry to build your own influence and political action groups.

Jared is still trying to get senior leadership to understand that the clock is ticking, and internal R&D efforts and current budget allocation won’t be sufficient or timely. He’s building a larger coalition for change, but the inertia for the status quo is overwhelming.

Rohan’s company was lucky. After months of scrambling (and tens of thousands of dollars), they ended up buying a patent portfolio from a defunct startup and were able to use it to convince the Fortune 500 company to drop their lawsuit.

I hope they both succeed.

What have you found to be effective in taking on incumbents?

Gordon Bell passed on this month.

I was a latecomer in Gordon Bell’s life.  But he made a lasting impact on mine.

The first time I laid eyes on Gordon Bell was in 1984 outside a restaurant in a Boston suburb when he pulled up in a Porsche. I was the head of Marketing for MIPS Computer, a RISC chip startup. The entire company (all of five of us) were out visiting the east coast to meet Prime Computer who would become our first major customer. (When Gordon was CTO of Encore Computer he encouraged the MIPS founders to start the company, thinking they could provide the next processor for his Multimax computer.)

My West Coast centric world of computing had been limited to custom bit-sliced computers, HP 2100 and 21MX, Interdata 8/32 minicomputers and Zilog microprocessors. Gordon was already a legend – as VP of Research and Development at Digital Equipment Corporation (DEC) he designed some of the early minicomputers and oversaw the creation of the VAX 11-780. His work at DEC revolutionized the computing industry, making powerful computing accessible.

Even so, as we talked over dinner at first I couldn’t understand a word he was saying, until I realized that he had three or four levels of conversation going simultaneously, all interleaved. If you could keep them sorted it was fun to keep up with each thread. By dessert I became another member of the Gordon Bell fan club.

Two years later, on a lunch break in downtown Palo Alto I ran into Gordon again. He was out to attend a Teknowledge board meeting. I invited him over to meet the founding team of Ardent, our new startup, whose founders he knew from DEC. By the end of the day Gordon had joined our team as founding VP of Engineering and another phase in my education was about to begin.

As an entrepreneur in my 20’s and 30’s, I was lucky to have four extraordinary mentors, each brilliant in his own field and each a decade or two older than me. While others taught me how to think, it was Gordon Bell who taught me what to think about. He could see the destination clearer than anyone I’ve ever met. The best part of my day was hearing him tell me about 3 ideas at a time and me do the same back to him. He had an extraordinary instinct for guiding me away from the purely dumb paths that would lead nowhere and nudge me on to the more productive roads. (He had this warm laugh, a kind of a chuckle when he was listening to some of more dumber ideas.)

At Digital Equipment Gordon had developed a heuristic that attempted to predict the evolution of the next class of computers. And when he left DEC he created the Bell-Mason diagnostic to help predict patterns in successful startups. The idea that there was a pattern about startup success and failure would stick in the back of my head for decades and shape the second half of my career. And as he was brainstorming about some of the early ideas about what became his MyLifeBits project I was inspired to start a small version of my own.

For the next 15 years Gordon would help me understand how to think critically about the possibilities over the horizon. Yet at the same time Gordon was looking forward, he was teaching us to respect and learn from the past.

Gordon and his wife Gwen started a computer history museum and by 1983 moved it into renovated warehouse next to the Boston Children’s Museum. In 1986 I spent two weeks making a short movie about the history of high-performance computing at the museum. Gordon and Gwen put me up in their guest bedroom overlooking Boston Harbor and a short walk across the Congress Street bridge to the museum. This not only began my long-term love affair with the museum but also made me realize that computer history and the history of innovation clusters were missing the story of how the military and intelligence community had shaped the trajectory of post WWII technology.

Seven years later, in my next startup, I would end up in their apartment again, this time with my wife and two young daughters, to attend the MacWorld trade show. I vividly remember the girls running around their living room decorated with many of the artifacts the museum didn’t have room to display (with Gwen patiently telling them that the Arithmometer and  Napier’s Bones weren’t toys.) For the next few years, we’d return (with the artifacts safely hidden away.)

By the time I started my final startup Epiphany, Gordon was at Microsoft, and he became my most valuable advisor.

Gordon was not only a mentor and inspiration to me, but to countless engineers and computer scientists. It was a privilege to know him.

2004

I’ll miss him.

The world is very different now. For man holds in his mortal hands the power to abolish all forms of human poverty and all forms of human life.

John F. Kennedy

Humans have mastered lots of things that have transformed our lives, created our civilizations, and might ultimately kill us all. This year we’ve invented one more.

Artificial Intelligence has been the technology right around the corner for at least 50 years. Last year a set of specific AI apps caught everyone’s attention as AI finally crossed from the era of niche applications to the delivery of transformative and useful tools – Dall-E for creating images from text prompts, Github Copilot as a pair programming assistant, AlphaFold to calculate the shape of proteins, and ChatGPT 3.5 as an intelligent chatbot. These applications were seen as the beginning of what most assumed would be domain-specific tools. Most people (including me) believed that the next versions of these and other AI applications and tools would be incremental improvements.

We were very, very wrong.

This year with the introduction of ChatGPT-4 we may have seen the invention of something with the equivalent impact on society of explosives, mass communication, computers, recombinant DNA/CRISPR and nuclear weapons – all rolled into one application. If you haven’t played with ChatGPT-4, stop and spend a few minutes to do so here. Seriously.

At first blush ChatGPT is an extremely smart conversationalist (and homework writer and test taker). However, this the first time ever that a software program has become human-competitive at multiple general tasks. (Look at the links and realize there’s no going back.) This level of performance was completely unexpected. Even by its creators.

In addition to its outstanding performance on what it was designed to do, what has surprised researchers about ChatGPT is its emergent behaviors. That’s a fancy term that means “we didn’t build it to do that and have no idea how it knows how to do that.” These are behaviors that weren’t present in the small AI models that came before but are now appearing in large models like GPT-4. (Researchers believe this tipping point is result of the complex interactions between the neural network architecture and the massive amounts of training data it has been exposed to – essentially everything that was on the Internet as of September 2021.)

(Another troubling potential of ChatGPT is its ability to manipulate people into beliefs that aren’t true. While ChatGPT “sounds really smart,” at times it simply makes up things and it can convince you of something even when the facts aren’t correct. We’ve seen this effect in social media when it was people who were manipulating beliefs. We can’t predict where an AI with emergent behaviors may decide to take these conservations.)

But that’s not all.

Opening Pandora’s Box
Until now ChatGPT was confined to a chat box that a user interacted with. But OpenAI (the company that developed ChatGPT) is letting ChatGPT reach out and interact with other applications through an API (an Application Programming Interface.)  On the business side that turns the product from an incredibly powerful application into an even more incredibly powerful platform that other software developers can plug into and build upon.

By exposing ChatGPT to a wider range of input and feedback through an API, developers and users are almost guaranteed to uncover new capabilities or applications for the model that were not initially anticipated. (The notion of an app being able to request more data and write code itself to do that is a bit sobering. This will almost certainly lead to even more new unexpected and emergent behaviors.) Some of these applications will create new industries and new jobs. Some will obsolete existing industries and jobs. And much like the invention of fire, explosives, mass communication, computing, recombinant DNA/CRISPR and nuclear weapons, the actual consequences are unknown.

Should you care? Should you worry?
First, you should definitely care.

Over the last 50 years I’ve been lucky enough to have been present at the creation of the first microprocessors, the first personal computers, and the first enterprise web applications. I’ve lived through the revolutions in telecom, life sciences, social media, etc., and watched as new industries, markets and customers created literally overnight. With ChatGPT I might be seeing one more.

One of the problems about disruptive technology is that disruption doesn’t come with a memo. History is replete with journalists writing about it and not recognizing it (e.g. the NY Times putting the invention of the transistor on page 46) or others not understanding what they were seeing (e.g. Xerox executives ignoring the invention of the modern personal computer with a graphical user interface and networking in their own Palo Alto Research Center). Most people have stared into the face of massive disruption and failed to recognize it because to them, it looked like a toy.

Others look at the same technology and recognize at that instant the world will no longer be the same (e.g. Steve Jobs at Xerox). It might be a toy today, but they grasp what inevitably will happen when that technology scales, gets further refined and has tens of thousands of creative people building applications on top of it – they realize right then that the world has changed.

It’s likely we are seeing this here. Some will get ChatGPT’s importance instantly. Others will not.

Perhaps We Should Take A Deep Breath And Think About This?
A few people are concerned about the consequences of ChatGPT and other AGI-like applications and believe we are about to cross the Rubicon – a point of no return. They’ve suggested a 6-month moratorium on training AI systems more powerful than ChatGPT-4. Others find that idea laughable.

There is a long history of scientists concerned about what they’ve unleashed. In the U.S. scientists who worked on the development of the atomic bomb proposed civilian control of nuclear weapons. Post WWII in 1946 the U.S. government seriously considered international control over the development of nuclear weapons. And until recently most nations agreed to a treaty on the nonproliferation of nuclear weapons.

In 1974, molecular biologists were alarmed when they realized that newly discovered genetic editing tools (recombinant DNA technology) could put tumor-causing genes inside of E. Coli bacteria. There was concern that without any recognition of biohazards and without agreed-upon best practices for biosafety, there was a real danger of accidentally creating and unleashing something with dire consequences. They asked for a voluntary moratorium on recombinant DNA experiments until they could agree on best practices in labs. In 1975, the U.S. National Academy of Science sponsored what is known as the Asilomar Conference. Here biologists came up with guidelines for lab safety containment levels depending on the type of experiments, as well as a list of prohibited experiments (cloning things that could be harmful to humans, plants and animals).

Until recently these rules have kept most biological lab accidents under control.

Nuclear weapons and genetic engineering had advocates for unlimited experimentation and unfettered controls. “Let the science go where it will.”  Yet even these minimal controls have kept the world safe for 75 years from potential catastrophes.

Goldman Sachs economists predict that 300 million jobs could be affected by the latest wave of AI. Other economists are just realizing the ripple effect that this technology will have. Simultaneously, new startups are forming, and venture capital is already pouring money into the field at an outstanding rate that will only accelerate the impact of this generation of AI. Intellectual property lawyers are already arguing who owns the data these AI models are built on. Governments and military organizations are coming to grips with the impact that this technology will have across Diplomatic, Information, Military and Economic spheres.

Now that the genie is out of the bottle, it’s not unreasonable to ask that AI researchers take 6 months and follow the model that other thoughtful and concerned scientists did in the past. (Stanford took down its version of ChatGPT over safety concerns.) Guidelines for use of this tech should be drawn up, perhaps paralleling the ones for genetic editing experiments – with Risk Assessments for the type of experiments and Biosafety Containment Levels that match the risk.

Unlike moratoriums of atomic weapons and genetic engineering that were driven by the concern of research scientists without a profit motive, the continued expansion and funding of generative AI is driven by for-profit companies and venture capital.

Welcome to our brave new world.

Lessons Learned

• Pay attention and hang on
• We’re in for a bumpy ride
• We need an Asilomar Conference for AI
• For-profit companies and VC’s are interested in accelerating the pace