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How this site was built

This site is also the proof. It was designed and built solo, start to finish, with an AI coding assistant in the loop the whole way — which is how Paul builds everything now. Here is the honest version of what it is made of and the calls that shaped it.

The stack

Lean on purpose. No framework soup, no backend to babysit.

Next.js 16 (App Router)
Static case studies and writing, plus route handlers for the live AI.
React 19 + TypeScript
Typed end to end — every component and every API contract.
Tailwind CSS v4
CSS-first theming, no config file. One token set, used everywhere.
Anthropic SDK — Claude
Haiku runs the ask-bar, Sonnet runs the role matcher. Streaming over web standards.
Content pipeline
gray-matter, react-markdown, remark-gfm and rehype-raw render the posts and case studies.
next/font + next/og
Self-hosted Saira, Space Grotesk and JetBrains Mono, plus a generated share image.
Vercel
Hosting and the serverless functions behind the AI. No separate backend to run.

Built with AI, honestly

The design happened in real, rendered mockups instead of static comps. The build happened component by component, with Paul making every design and architecture call and an AI assistant doing the heavy lifting on implementation.

The split is simple. Paul owns the judgment, the taste, and the decisions. The AI accelerates the parts that used to need a team. The back end he never used to touch got handled. The front end he always built got faster. Every line was read and verified before it shipped.

The calls that mattered

  1. 01

    Two models, on purpose

    The ask-bar fields a lot of questions, so it runs on Haiku — fast and cheap per answer. The role matcher runs rarely but matters a lot, so it runs on Sonnet. Pay for intelligence only where it earns its keep.

  2. 02

    The matcher is built to be honest

    It returns structured output through forced tool use, validated against the real project list, and it is tuned to flag genuine gaps instead of overselling. A tool that lies about fit is worse than no tool.

  3. 03

    The assistant talks about Paul, never as him

    Third person on purpose. An AI pretending to be the person reads fake. A guide that presents evidence and lets you decide reads honest — and it shows the engineering instead of hiding it.

  4. 04

    The work never waits on the model

    Tap a question and the work canvas re-curates instantly, client-side, while the written answer streams in behind it. If the AI is slow or capped, the visual response still lands.

  5. 05

    A public AI endpoint needs a ceiling

    Per-IP rate limits plus a hard monthly spend cap. The site can invite anyone to use the AI without anyone being able to run up the bill.

  6. 06

    The words are human

    The copy was written and rewritten to sound like a person, not a model. This site leans on AI heavily under the hood and almost not at all in its own voice. That was the point.

Open the hood

None of this is a black box. The full source for this site goes public on GitHub when it ships. In the meantime, the rest of Paul's work is already out in the open.

github.com/somekidpaul