I’m coining the word ‘disruptobloat’ to describe a distinct season that any major technology goes through:
Disruptobloat is a phenomenon of overproduction: [some new tech]-driven products flood the market, diluting the perception of value in the short term.
It’s a race towards the same thing: discovering a sticky use case that shapes new customer behaviors and accrues value. It’s not a bug; it’s a necessary step in the evolution, and a good thing! The bigger the disruptobloat, the faster we get to breakthroughs, because we iterate through ideas faster.
Azeem Azhar from Exponential View breaks it down this way:
Level 1: Do what we do cheaper: (…) automate routine tasks.
Level 2: Do what we do, just do it better: (…) opportunities for qualitative improvements. A major investment bank, for instance, recently used AI to automate much of its unit test coverage. This reduced costs and allowed for more comprehensive testing, improving overall software quality.
Level 3: Do entirely new things. This is where the true potential of AI begins to show (…) But here’s the rub: most businesses are stuck at Level 1 or Level 2. They’re using AI to shave costs or incrementally improve processes, missing the opportunity to strategically rethink what their business could look like (…)
The thing is, everyone is trying to “strategically rethink what their business could look like”, but it’s tough. We’re all conditioned to think through the implicit constraints of our day-to-day lives, and rethinking only happens when we ignore those constraints. For existing businesses, they’re also the constraints of the ossified ecosystems of customers, partners, revenue, and profit.
There’s a saying that originated during the Gold Rush: "When people dig for gold, sell shovels”, used often to describe a business strategy: instead of directly participating in a competitive and speculative market, provide the essential tools and services for that market. The problem with shovels, though, is that they’re fungible, and
Let’s assume that no provider releases a model that is orders of magnitude better than the competition for a long enough time for it to strategically matter__2__. Where does the value accrue, then? In other words, what kinds of products will be able to build a moat?
The application layer__3__ - the surfaces, apps, sites through which users will interact are:
No surprise, then, that it’s worth to compete with hundreds (if not thousands) of startups for the same use cases.
This quote from
- AI tools that run on top of existing software (think: automatic meeting notes for Zoom meetings)
- AI tools that run on top of existing software that have a shot of displacing that existing software (think: meeting notes for Zoom Meetings…where said company then builds video conferencing and pitches you to ditch Zoom)
- AI tools that turn into labor — a net-new category, completely untouched by software until this point (think: the software conducts the meeting for you!)
Hence, disruptobloat.
This race between existing companies and 0→1 startups is a pure Product Discovery Challenge. In theory, model providers should have an advantage, a result of having collected 2 years of usage data. Looking for insight from OpenAI’s marketplace of GPTs returns
It's reminiscent the
Last week, Not Boring by Packy McCormick published
Vertical Integrators are companies that:
- Integrate multiple cutting-edge-but-proven technologies.
- Develop significant in-house capabilities across their stack.
- Modularize commoditized components while controlling overall system integration.
- Compete directly with incumbents.
- Offer products that are better, faster, or cheaper (often all three).
NVIDIA is an example of this strategy on steroids, building ecosystems around the core technologies to control the entire technology stack, especially as base models become commoditized:
Not all incumbents are or will be competing in every layer now, but the point is that they have the capability to do so, whether by building or acquisitions. As
“This is the flaw with looking at Square and Stripe and calling them commodity players. They have the distribution. They have the engineering talent. They can build their own TiVo. It doesn’t mean they will, but their success hinges on their own product and engineering prowess, not on an improbable deal with an oligopoly or utility. ”
One of the early goals I had for this post was to pinpoint the killer use cases, which, in retrospect, is a tall order for a few hours of research. Still, as the hype slows down, there are a few corners of disruptobloat that I’m paying attention to:
The killer use case is somewhere out there, unrefined and drowning in noise. Whether - or when - the
PS: I post at https://hypegeist.substack.com/ about emerging tech and would love to send these to you directly.
PS2: Thank you Claude for brainstorming and edit assist.