Using AI /
Distribution is moving from attention to evidence
Distribution, distribution, distribution.
That is the advice now. Building has become cheaper, so the advantage moves to whoever can get the product in front of people.
If two people build something comparable, the one with the audience, advertising budget or talent for social media usually gets further. The quieter builder may have the better product and still lose.
That remains true. It may not remain true in the same way.
AI will sit between the buyer and the market
A buyer once searched Google, opened ten tabs, watched a review and asked a friend.
Now they can ask an agent: ‘What is the best analytics tool for a five-person software company that uses Stripe, has no data team and wants to spend less than $200 a month?’
The agent can search, compare the options and return a shortlist. Many products will not get a chance to pitch themselves. The agent decides which ones receive the buyer's attention.
This is already beginning. ChatGPT's shopping research uses a buyer's needs, preferences and budget alongside public product information and merchant feeds. Google's AI shopping systems draw from product listings, reviews, prices and availability.
The distribution channel is no longer only a feed filled with people.
It is also a machine trying to make a decision for one person.
A machine can see past some theatre
An influencer can repeat a weak claim to a large audience. An agent can compare that claim with the documentation, price, customer reviews and competing products.
That should reduce the value of some marketing theatre.
It does not mean AI will find the most deserving builder and reward them. A model does not know who worked hardest, who has the purest motives or which quiet developer is secretly a genius.
It sees available evidence.
If the good product has no documentation, public users, benchmarks, reviews or clear explanation, hidden quality looks the same as absent quality.
Merit still needs a surface.
Marketing becomes machine legibility
The work does not disappear. It changes.
A product that wants to be recommended by an agent needs:
- clear product information
- useful documentation
- credible customer outcomes
- transparent pricing and availability
- independent reviews and comparisons
- structured feeds, APIs or pages a machine can read
Google now tells retailers that its AI shopping experiences depend on the product data they provide through Merchant Center. If that data is incomplete, customers may not find the product.
That is marketing, but it is less about manufacturing attention and more about making the truth legible.
The opportunity is not to stop communicating. It is to replace inflated claims with evidence an agent can inspect.
The gatekeeper does not disappear
There is a less comfortable side to this.
The AI does not independently decide what the market should see. The company operating it chooses the sources, ranking systems, commercial rules and safety policies around the answer.
OpenAI is building cost-per-click advertising for ChatGPT, kept separate from organic answers. Google is bringing conversational queries, merchant feeds and automated advertising into the same AI-led discovery environment.
The influencer may lose some power. The platform owner may gain more.
Distribution does not vanish. It moves to a new gatekeeper.
Do not build in silence
The answer is not to join a permanent content treadmill. It is also not to hide and trust that a future AI will recognise your work.
Build the product. Then leave evidence.
Publish the documentation. Record the customer result. Keep the changelog. Explain the trade-offs. Make the pricing clear. Let people test what you claim.
A quiet builder can compete with a loud marketer when the work leaves stronger evidence. Silence leaves nothing for the agent to evaluate.
This shift does not require AGI and it does not need to arrive on one dramatic date. It begins whenever a person lets an AI narrow the market before they look at it themselves.
The next distribution question may be simple: when an agent investigates this product, how much credible evidence can it find?
The rule
Build something good. Make the proof legible.
The next customer may arrive because an AI could verify what the loudest person could only claim.