Over the last 2 weeks I've noticed that no single "A.I." product has solidified it's role in my personal or professional life.
On a given day I'll bounce between Phind, ChatGPT, Gemini, Perplexity, Lex.page, and Gemini-via-Google-Search depending on which tabs are open, what's easy, and mere whim.
Each tool is sometimes great, sometimes bad, and sometimes ridiculous. None has differentiated itself fully.
I've tried to put my finger on why I haven't fully adopted any single "A.I." specific product to the exclusion of others -- AI startups require new strategies: This time it’s actually different by Jason Cohen articulates a great answer:
The “market” is not what you think: AI is not a large, growing market
“AI will be a multi-trillion-dollar market” people say. AI is surely the definition of a large, growing market, with many orders of magnitude of growth in its future. Which means it’s perfect for startups.
Except these are nonsense statements. A “market” is a set of buyers, with sufficiently similar needs, constraints, and goals, that the same product can be sold to all of them. The “AI” market consist of companies like OpenAI and Cohere, and indeed that is a large and growing market, but unless you’re competing directly with them, you’re not “in the AI market.”
A chatbot is in the chatbot market, and an SEO tool is in the SEO market. Adding AI to those tools is obviously a good idea; indeed companies who fail to add AI will likely become irrelevant in the long run. Thus we see that “AI” is a new tool for developing within existing markets, not itself a new market (except for actual hard-tech AI companies).
AI is in the solution-space, not the problem-space, as we say in product management. The customer problem you’re solving is still the same as ever. The problem a chatbot is solving is the same as ever: Talk to customers 24/7 in any language. AI enables completely new solutions that none of us were imagining a few years ago; that’s what’s so exciting and truly transformative. However, the customer problems remain the same, even though the solutions are different.
Differentiation when everyone has the same technology
The “hard tech” in AI are the LLMs available for rent from OpenAI, Anthropic, Cohere, and others, or available as open source with Llama, Bloom, Mistral and others.
The hard-tech is a level playing field; startups do not have an advantage over incumbents.
There can be differentiation in prompt engineering, problem break-down, use of vector databases, and more. However, this isn’t something where startups have an edge, such as being willing to take more risks or be more creative. At best, it is neutral; certainly not an advantage.
In a market where everyone has access to the same core technologies, simply matching the capabilities of established players is not a winning strategy. This doesn’t mean it’s impossible for a startup to succeed; surely many will. It means that you need a strategy that creates differentiation and distribution, even more quickly and dramatically than is normally required.
So, what to do with this understanding?
It means looking at "A.I. startups" more honestly. As Jason put it, "A chatbot is in the chatbot market, and an SEO tool is in the SEO market," despite what the marketing, fundraising dollars, and hype might like you to think.
When assessing an "A.I" startup simply ask:
- How are they differentiated?
- How are they going to grow? What is their unique distribution?
- What incumbents could eat their lunch? Why won't they?
What’s critical in each of these cases is that these are not explicitly productivity improvements to existing employees for existing workflows. Instead, they take markets that were constrained by all the effort, friction, and cost of hiring and working with people, and unlock them. Exactly the type of market that gets overlooked by an incumbent.If the last couple waves of startups felt like 10x improvements, AI provides what feels like a 100x better experience than the incumbent substitute (humans!) by compressing what is almost always the significant effort of hiring and managing another person, into a near instant experience that will only get better over time.
EDIT 4/21/24: Read another point of view, Looking for AI use-cases by Benedict Evans
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