Jev: 8 real use cases for the fastest, cheapest model I’ve ever used | John Lindquist

John Lindquist created egghead.io, a developer education platform used by hundreds of thousands of working engineers. These days he’s building mega.dev, a hands-on program specifically for developers who want to do real work with AI agents, not just prototype them.

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What you’ll learn:

1. Why Jev is a decision engine, not a chatbot, and what that distinction actually changes about how you build
2. How John built a real-time voice to-do app that classifies and executes commands with no visible
3. The data deduplication pattern that merges messy records in milliseconds using confidence scores
4. Why Jev works best as a router, and how a single text input can navigate users deep into an app
5. What a chess match between Jev and a low-reasoning LLM reveals about speed, cost, and when to use which
6. The multi-step classification pattern John reaches for when one Jev pass isn’t enough
7. Where Jev falls short, and when you should still reach for a full generative model

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In this episode, we cover:

([00:00](https://www.youtube.com/watch?v=dAIIaepNhQM)) John Lindquist returns for Jev week

([04:32](https://www.youtube.com/watch?v=dAIIaepNhQM&t=272s)) What Jev actually outputs

([06:15](https://www.youtube.com/watch?v=dAIIaepNhQM&t=375s)) Demo: real-time voice to-do app

([08:17](https://www.youtube.com/watch?v=dAIIaepNhQM&t=497s)) How sequential Jev calls chain together

([10:38](https://www.youtube.com/watch?v=dAIIaepNhQM&t=638s)) Demo: plain English to function name (grocery cart)

([11:50](https://www.youtube.com/watch?v=dAIIaepNhQM&t=710s)) Demo: data deduplication and record merging

([13:45](https://www.youtube.com/watch?v=dAIIaepNhQM&t=825s)) Confidence scores and multi-model validation

([15:06](https://www.youtube.com/watch?v=dAIIaepNhQM&t=906s)) Demo: Jev as a multi-level app router

([18:23](https://www.youtube.com/watch?v=dAIIaepNhQM&t=1103s)) Architecting around Jev

([19:35](https://www.youtube.com/watch?v=dAIIaepNhQM&t=1175s)) Demo: Jev vs. traditional LLM at chess (speed and cost benchmarks)

([24:29](https://www.youtube.com/watch?v=dAIIaepNhQM&t=1469s)) DOM interactions as a decision set, not an infinite canvas

([28:21](https://www.youtube.com/watch?v=dAIIaepNhQM&t=1701s&pp=0gcJCWMAwfN6Pr3D)) Demo: Wikipedia “path to philosophy” route mapper

([30:28](https://www.youtube.com/watch?v=dAIIaepNhQM&t=1828s)) Demo: multi-agent coordination and collision avoidance

([33:36](https://www.youtube.com/watch?v=dAIIaepNhQM&t=2016s&pp=0gcJCWMAwfN6Pr3D)) Demo: real-time presentation coach

([36:56](https://www.youtube.com/watch?v=dAIIaepNhQM&t=2216s)) Quick recap

([39:54](https://www.youtube.com/watch?v=dAIIaepNhQM&t=2394s)) Lightning round and final thoughts

Tools referenced:

• Jev (TypeSafe AI decision model): [https://typesafe.ai/blog/introducing-system-one-models-and-jev](https://typesafe.ai/blog/introducing-system-one-models-and-jev)

• Vercel AI Gateway: [https://vercel.com/docs/ai-gateway](https://vercel.com/docs/ai-gateway)

• OpenRouter: [https://openrouter.ai](https://openrouter.ai)

• Opus 5.5 (mentioned in context of iterative demo building): [https://www.anthropic.com/claude-opus-5-5](https://www.anthropic.com/claude-opus-5-5)

Where to find John Lindquist:

LinkedIn: [linkedin.com/in/john-lindquist-84230766](http://linkedin.com/in/john-lindquist-84230766)

X: [https://x.com/johnlindquist](https://x.com/johnlindquist)

Mega.dev: [https://mega.dev/](https://mega.dev/)

Egghead.io: [https://egghead.io/](https://egghead.io/)

Where to find Claire Vo:

ChatPRD: [https://www.chatprd.ai/](https://www.chatprd.ai/)

Website: [https://clairevo.com/](https://clairevo.com/)

LinkedIn: [https://www.linkedin.com/in/clairevo/](https://www.linkedin.com/in/clairevo/)

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].