Real-time voice AI + reference-implementation engineering
RecipeWalk
A voice-native cooking assistant that reads a recipe aloud and guides you hands-free, step by step, in real time.
- Role
- Sole engineer, designer, and operator
- Year
- 2026
- Status
- In Development
- Site
- recipewalk.com
- React 19 / Vite / TypeScript
- Python / FastAPI
- Gemini 2.5 Flash (extraction)
- Gemini Live API (real-time voice)
- Neon PostgreSQL
- Stripe (subscriptions + gift codes)
- AWS CDK / Caddy on EC2
277 backend + 120 frontend
Automated tests passing
2026-07-02 · CI (pytest + vitest)
Challenge
Cooking from a phone is hands-busy work, and recipe blogs bury each step under ads, life stories, and walls of text. RecipeWalk structures the recipe, then a real-time voice assistant guides the cook hands-free, without “ChatGPT forgetfulness” (losing track of the current step).
Process
Gemini 2.5 Flash parses a pasted or photographed recipe into ingredients, steps, and timers. Voice connects client-direct to the Gemini Live API over WebSocket, skipping a backend proxy to cut latency and cost. A server-side state machine sends step-scoped system instructions and issues single-use, scoped, ephemeral session tokens, so the assistant always knows the current step.
Other projects copy RecipeWalk’s reference implementations: secrets loaded from AWS at service start into a locked-down env file, IAM deployer scoping, and gift-code security (high-entropy codes encrypted at rest, atomic single-use redemption, IDOR hardening, auto-revocation on refund or dispute). My voice-eval harness runs synthesized audio through the exact production voice config to catch tool-calling regressions; it caught one before release.
Result
Deployed to production at recipewalk.com, all tests green (277 backend, 120 frontend). A real-money buy, redeem, refund, and revoke cycle proved the gift flow end-to-end. Not yet open to customers; a paid beta waits only on a go-live decision I am holding on purpose.