The 13 decisions that separated AI companies worth billions from the ones that shut down. Learn them before you make yours.
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Built on what happened to Cursor, ElevenLabs, Harvey, Jasper and IBM Watson.
You have users, maybe some revenue, and a competitor who shipped the same feature a week later with the same tools you used.
Amazon, Google and Microsoft already sold realistic AI voices. ElevenLabs went after the creators none of them were measuring, and was worth $22B by September 2026.
When your product is a wrapper around someone else’s model, their roadmap decides your future, and you find out on release day with everyone else.
Zoom, Google and Microsoft all built AI meeting notes into their products in 2023. Airgram, one of the first in the category, was gone by March 2024. Otter had already moved past transcription and passed $100M a year in revenue.
Moving faster isn’t an answer. Better design isn’t either. You need one sentence about what you have that a competitor with more money still can’t buy.
Valued at $1.5B with 70,000 paying subscribers, all of it running on OpenAI’s models. Then OpenAI shipped ChatGPT for free, then brand voice, templates and a full writing environment, one release at a time.
The executive approved it and the contract is booked. The people who have to use it every day get nothing out of it, so they don’t.
MD Anderson spent $62.1M on Watson before pausing it in 2016. Anterior, in the same industry, automated the prior-authorization paperwork insurers’ nurses hated, and covered 50M lives by 2026.
It has the users, the distribution and first access to the best models. Everyone you ask says there’s no room.
Microsoft owned the code editor, GitHub and Copilot. Cursor built on Microsoft’s own open-source editor and on models it didn’t train, and moved weekly. SpaceX bought it for $60B in 2026.
A live product, early users, maybe a waitlist. What you don't have is an answer to why it survives the first good copy, or a plan for what to build so it does.
A long roadmap and a short answer to why this won't get copied.
You need to decide what AI changes in your firm before your clients make that decision by leaving.
Clients asking why they still pay for first drafts.
Not forPrompt tips, tool roundups, or ways to ship faster. You already have that part.
Same tools, same market, often the same year, and a different ending. Every date and figure was checked in October 2026, through to how each story ended.
Built a legal model with OpenAI on public case law. By May 2025 seven general models beat it on its own benchmark. It moved its edge to how each firm configures it, and was valued at $15.5B in September 2026.
No proprietary dataset, and grammar anyone can buy in a bookshop. Ten years of data on when each learner forgets held off ChatGPT’s voice mode and Google’s language tools.
Won the 2023 race for AI compute with a software standard it released in 2006. By the time rivals had competitive chips, switching meant rewriting the pipelines and retraining the teams.
Its search quality improved substantially between 2010 and 2023. Its share went from 3.6% to 5.2%, against Google’s 90%. A better product did not change who people asked.
Instagram had the feed, the algorithm and the network. TikTok built its own way for people to find videos, the For You page, and beat Reels anyway.
Positioned itself against Facebook and got a clear identity and an IPO. Facebook copied its features into Instagram, Messenger and WhatsApp and delivered them to billions.
Did what the course recommends: free, on every meeting platform, deep in HubSpot. Superhuman still bought it in September 2026, on terms it did not disclose.
Raised more than $700M at a $9B valuation, with former Secretaries of State on the board, for a device that did not work. Holmes was convicted in 2022.
Both had promised safe AI. When the Pentagon demanded “any lawful use”, one refused and lost an award worth up to $200M. The other signed within hours. Claude reached #1 in the US App Store that weekend.
Make the call before you see the answer.
Dates, figures, and who was left standing.
What to do, and how to apply it to your business.
The company that followed it and still lost.
Find out in five minutes if you’re making it.
70% of venture-backed startups that shut down since 2023 ran out of money (CB Insights, March 2026). Each lecture ends with one of these, and a test for it.
Summarize, review, draft: the first product is usually the generic one, and it is exactly what the model vendor ships next.
The test. Open your platform’s release notes for the last six months. Mark every feature you charge for that it has shipped any version of.
Being early feels like a lead. To the platform it is free proof that the feature is worth building.
The test. Write down the one step your user can’t skip that happens in your product rather than the platform. If the honest answer is none, you are exposed.
You raise, hire and price as if you own something the next model release gives everyone.
The test. Name the data doing the work. If a lab could get it from the public web or license it, so can your competitors.
Users return and usage climbs, so it feels like leverage. But whatever capped your customer’s volume is still there.
The test. Name what limited how much your customer could do before your tool. If removing it changes neither how often they work nor what they can sell, you built a feature.
The contract is real and the runway needs it. The renewal is where you find out nobody adopted it.
The test. List everyone the product needs to cooperate, and what each personally gains and risks. Decide in advance which result would make you walk away.
The expected value looks good, so you quit, spend the savings and lock in one model provider. Lose once and there is no second try.
The test. Before any big move, write down what you would do the week after it fails. If there is no week after, no upside justifies it.
A working product used to be the hard part. Now it is the starting point. This course is about everything after it.
Watch the whole course. If it wasn’t worth it, get a full refund. Guarantee terms
Not ready to join? Read the free brief first.
Every lecture starts with the decision as it looked at the time. Every law also shows a company that followed the rule and still lost.
Yes. None of it is about writing code. It is about how a company keeps customers and gets paid once anyone can build the product.
Not for long. When anyone can build in a week, a better product is a head start, and head starts end.
Customers who would have to rebuild months of work to leave you. Data that only your users produce. A place in their workflow a platform can’t reach by adding a feature. Things a competitor with more money still can’t buy.
Yes. Every company, date and figure in the course is real and was checked in October 2026, including how each story ended. Where a number is an illustration, the slide says so.
About 15 minutes per lecture. The reference decks are there when you want the full case and tools.
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