Build your product with AI
From a prompt to a shipped product: prototype, build, and wire AI into what you ship.
6 steps to get you moving, each with a resource worth your time and more waiting underneath
Think of this as a friendly starting line, not the last word. Each step gives you the gist, then a resource worth your time from founders who've actually done it. There's always more underneath, more questions and more resources, whenever you feel like digging in.
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1
PromptingWhy do some people get 10x better results from the same AI tools?
The gist Because the output you get depends as much on how you ask as on the model itself, an MIT study found that roughly half the quality gains from a better AI model came from users learning to communicate with it, not from the model. Power users treat AI like a smart new hire: they give it background, examples, and clear success criteria, then iterate on the answer instead of accepting the first draft. The good news is this is a learnable communication habit, not a technical skill.
Study: Generative AI results depend on user prompts as much as models MIT Sloan (Ideas Made to Matter) Hard evidence that half the 'better AI' effect is the user's prompting skill, the clearest answer to why identical tools produce wildly different results. -
2
Vibe CodingWhy can non-technical founders now build software with AI?
The gist Coding models crossed a quality threshold in late 2024, and a wave of tools (Lovable, Replit, Bolt, Cursor) now turn plain-English descriptions into working apps. Andrej Karpathy named the shift 'vibe coding' in February 2025, and it became Collins Dictionary's Word of the Year within nine months. The practical upshot: describing what you want is now enough to get a real, testable product, which is why most users of platforms like Replit and Emergent have never written a line of code.
Karpathy's original 'vibe coding' post Andrej Karpathy The founding document of the whole movement, in his own words. -
3
Design & PrototypingWhy prototype with AI before hiring a designer?
The gist Because a working prototype beats a pitch deck and a job posting: in an afternoon you can put a clickable version of your idea in front of real users, sharpen your spec, and find out what is worth building before spending a rupee on salaries. A quarter of recent YC batches ship codebases that are mostly AI-generated, and product leaders now treat prompt-built prototypes as the new PRD. A designer is still worth hiring, but later, when you have signal and need craft and consistency, not to produce your first draft.
Microsoft CPO: If you aren't prototyping with AI, you're doing it wrong (Aparna Chennapragada) Lenny's Podcast Microsoft's product chief makes the sharpest case yet that prompt-built prototypes have replaced specs. -
4
Databases & Internal ToolsWhy use AI to build databases and internal dashboards instead of buying SaaS?
The gist The math has flipped: AI coding tools have collapsed the cost of custom software, so a founder can now get a tool shaped exactly to their workflow for less than a year of SaaS subscriptions. Retool's own research found 35% of teams have already replaced at least one purchased tool with something custom-built, and small companies are quitting Salesforce for Claude-built CRMs. Buying still wins for commodity needs like email and payroll; building wins when the workflow is your edge or the SaaS forces you into its shape.
The Build vs. Buy Shift: AI, Shadow IT, and the SaaS Replacement Era Retool Hard survey data on the shift: 35% of teams already replaced a bought tool with a built one, 78% plan to build more. -
5
AI AgentsWhat actually is an AI agent, in plain language?
The gist An AI agent is software that uses an AI model as its brain to pursue a goal: it plans the steps, uses tools (your email, browser, spreadsheets, code, APIs), checks its own work, and keeps going until the job is done. A chatbot answers you; an agent acts for you. Think of it as a tireless junior teammate that can read, click, write and call other software, but still needs clear instructions and supervision.
Building Effective AI Agents Anthropic The most-cited definition of workflows vs agents, written by the team behind Claude. -
6
AI in Your ProductShould my startup add AI features, and which ones actually matter to users?
The gist Users do not care that a feature uses AI; they care whether it removes a slow, painful, judgment-heavy step from their day. Start from a specific friction point in your existing workflow, not from the technology, and be honest about whether AI is a checkbox for investors or a real 10x on time saved. The strongest AI features sell the finished work (a resolved ticket, a drafted document), not a fancier tool.
"Should we add AI?" Here is how to decide Vasil (Founder Prompts) A clear decision framework for the exact moment every founder faces: bolt on AI, ignore it, or rethink the product.
