Fullstack-Bench

3 statements across 1 episodes · 2 bullish · 1 bearish · 1 people on the record · first statement Mar 19, 2025 by Sujay Jayakar · said 1 times in 1 episodes since 2025 · across every show →

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Mar 19, 2025 positive
Insight
End-to-end type safety and tight feedback loops improve AI agent performance
“It's like, you know, having just really tight feedback loops and having strong guardrails, like in convex, that's like end to end type safety, but that's like, you know, could take it in many, many different forms, right? Like making it so code is very cheap a…”
Sujay Jayakar Mar 19, 2025 ▶ 29:12 Fullstack-Bench: The Eval for Coding Agents — with Sujay Jayakar, Chief Scientist, Convex
Mar 19, 2025 negative
Assertion Supported
AI models struggle debugging Supabase RLS recursion compared to procedural code
“The particular example was like RLS rules and Supabase where debugging like an infinite loop for infinite recursion for the RLS rules was something that the models just really struggled with in a way that we didn't see for procedural code.”
Sujay Jayakar Mar 19, 2025 ▶ 29:57 Fullstack-Bench: The Eval for Coding Agents — with Sujay Jayakar, Chief Scientist, Convex
Mar 19, 2025 bullish
Assertion Supported
Cursor Composer solves Convex benchmarks but fails on alternative backends
“We did notice that I mean, with convex, it pretty much autonomously just solves the first two tasks. It has a few round trips on like some errors that are only show up and playing with the front end. And then it's able to complete this files task and kind of g…”
Sujay Jayakar Mar 19, 2025 ▶ 9:36 Fullstack-Bench: The Eval for Coding Agents — with Sujay Jayakar, Chief Scientist, Convex
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