5.1.3 - How It Ends Is the Part People Remember - Plan the ending: say who is still using it, what they get and what is left behind at the address afterwards.
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5.1.1 - Would You Start This Today? - Run the continue test: say whether it still earns its place, what it costs you in a normal week and which of the three answers comes next.
4.3.2 - How Would You Know If Any of This Worked? - Decide what evidence would tell you the knowledge base is doing its job, then take the reading before you start so you have something to compare against.
5.1.2 - Where Do You Stop, For Now? - Decide what this project asks of you in a normal week, and write down what would make you open it again.
4.2.2 - Decide What Reaches You Before Everything Does - Decide which work runs unattended, what hands itself back to a person and what that person actually receives when it does.
4.2.1 - The Failure Whose Only Symptom Is That the Answer Looks Wrong - Decide where each kind of failure appears and what a person is handed when it does, including the ones that never go red.
4.1.2 - If the Secret Only Exists on Your Machine, You Are the Single Point of Failure - Decide where secrets live and how they are set per environment, with every name the code reads written down and no real value anywhere near it.
4.1.1 - You Haven't Finished a Deploy Until You've Practised Undoing It - Decide what triggers a deploy to each environment, how you confirm it landed and the exact route back to the previous version.
Where is the low hanging fruit with AI? - Start with the boring work. Not the clever work. The work that is done the same way every time, because that is where you can tell whether it was done right.
An AI agent charges you per answer and never says whether the answer was any good - Telemetry records the cost, the template, the model and the latency. It does not record whether the answer was any good, and that half has to be built by hand.
The cheapest way to build an AI agent is the most expensive way to run one - The option that feels like progress in week one is the one still charging you in week fifty. An agent has to keep its policy somewhere. There are three obvious places to put it.
Interesting to me. Not to you. - What stops you pressing the button? Gut feel, a friend, a chat AI, market research.
Your next vibeCode starts where the last one finished - The first vibeCode is rough. It is also the worst it will ever be. What the next one is worth depends entirely on what you rebase it onto.
I wrote down everything I know about building with AI - A year of building, written down. The agent loop, why more tools make an agent worse and what a gate should actually check.
A Wednesday check-in to make your vibe have more value - A ten minute check before you vibeCode something or hand it to an AI: is this the best return on the effort and does it already exist?
The AI answered like an engineer. That was the problem. - The AI gave the perfect technical answer and it was exactly the wrong answer.
The guide has moved - It is now free and ungated, with no signup. Read it at vibe2value.com/guide/.
AI can build anything. So why are you still stuck? - The code is the easy part now. The two hard parts of AI coding are knowing where to start and the fact the AI forgets. Here is help with both.
What's your one tip for building with AI you can trust? - Let's collect them. One shared list, added to and voted up by the people who use it. Let's aim for 99.
Thank you and a clearer vibe2value - Your feedback to yesterdays email resulted in some changes. The big one: the site now says plainly what it is, a way of thinking about building with AI.
The ideas are easier to read now and the first videos - I went back through all 27 ideas to make them easier to read. And I started making short videos.
Over my head and I don't know where to start - Two messages on the same day at opposite ends. They turned out to be the same problem.
Build with AI and trust what you make: the prompts and notes to get you there - The biggest update yet. Every idea now has a sharper prompt and its own diagram, and the working notes for working with AI have grown.
The soft skills of working with AI - Most of getting good with AI is not the tool. It is how you work with it, moment to moment.