# Zod Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/zod
> Markdown URL: https://aitinkerers.org/technologies/zod.md
> Technology record last updated: 2026-09-18T15:13:57Z
> Generated: 2026-09-21T17:48:16Z

Zod delivers TypeScript-first schema validation with zero dependencies and automatic type inference.

Zod bridges the gap between runtime input and static TypeScript types. Developers define a schema once (e.g., `z.object({ id: z.uuid() })`) to gain both validation and automatic type inference. This library processes over 12 million weekly npm downloads, securing its position as the standard for type-safe data handling. It eliminates the "any" type by parsing raw data into structured, validated objects. The 8kb footprint (minified and zipped) works across any environment: Node.js, browsers, or Edge functions. It handles complex logic like discriminated unions and transformations without requiring a separate build step.

- Official technology site: https://zod.dev
- Public AI Tinkerers demos and talks: 2
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Making local elections more transparent with AI](https://la.aitinkerers.org/talks/rsvp__2-l-YlpnxM)

Local elections decide a lot and almost nobody covers them. California city races are nonpartisan by law, so the ballot doesn't share a candidate's party, and local coverage of city hall has thinned to almost nothing. The records are public but unusable: filings as PDFs, a county voter file behind a paywall, endorsements scattered across a dozen sites. Torrance Watch is the public reference that could not exist before LLMs. Every contested race, every candidate covered the same way: background, where they stand, who endorsed them, and who is funding them, split into direct contributions, independent PAC spending, and how many donors actually live in Torrance. Every claim is footnoted to a filing you can open, and equal treatment is a compile gate, so a race covered unevenly fails to build. About 26,000 people used it, and roughly a quarter million saw the findings across Facebook groups, Reddit and Nextdoor. The busiest day was June 8, mid-count, not election night. It forecast the count and called four races itself, for a city of 145,000, because no wire service covers a city election. And it put a number on the money: $148,000 from Orange County real estate PACs across the five races, seven times what Torrance public-safety unions spent. Claude Code built it: 423 merged pull requests, one person, April to August. Six pipelines work the review queues, matching 2,543 donors against 6.4 million voter registrations, checking endorsements against their sources, and drafting candidate profiles. A deterministic scorer runs first and settles what it can. What it cannot resolve goes to LLM judges working under rules written before the run, and every decision records who made it. For the hardest cases three models judge separately, blind to the matcher's own pick, and the label only counts if all three agree. Nothing about it is specific to Torrance. The same pipeline would work for any city.

- Event context: AI Tinkerers LA — August 6: Builder Meetup & Live Demos — 2026-08-07 — Los Angeles
- Public talk page: https://la.aitinkerers.org/talks/rsvp__2-l-YlpnxM

### [Deterministic tools, Non-Deterministic orchestration — Building a production AI Agent for auto parts lookup](https://poland.aitinkerers.org/talks/rsvp_8D7UFMN443Y)

An AI agent that takes a car's registration number and returns purchasable replacement parts, solving a problem of a fragmented Polish aftermarket where no single API covers all brands. The system splits the problem into deterministic source selection (which API to call, in what order, per brand) and an LLM-orchestrated agent asks clarifying questions when data is ambiguous, and combines partial results from multiple sources.

- Event context: AI Tinkerers Poland - Meetup in Gdańsk #1 — 2026-04-23 — Poland
- Public talk page: https://poland.aitinkerers.org/talks/rsvp_8D7UFMN443Y

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