AI + a16z

Benchmarking AI Agents on Full-Stack Coding

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Mar 28, 2025
Sujay Jayakar, co-founder and Chief Scientist at Convex, dives into the future of autonomous coding. He discusses the challenges AI agents face with full-stack development and the significance of robust evaluation methods like Fullstack Bench. Jayakar emphasizes how type safety can reduce errors and improve consistency. He shares insights on which AI models excel in real-world app-building, and why treating your toolchain as part of the prompt could transform development workflows. Perfect for developers looking to enhance their projects with AI!
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INSIGHT

AI Full-Stack Coding Challenges

  • Building full-stack apps with AI isn't easy.
  • Strong guardrails, good libraries, and understanding model limitations are key.
ANECDOTE

Claude 3.7 Too Clever

  • Martin Casado found Claude 3.7 too clever, causing coding issues.
  • He reverted to 3.5 for simpler development.
INSIGHT

Benchmarks vs. Evals

  • Benchmarks offer general platform insights.
  • Evals are crucial for individual developers but are underappreciated and require expertise.
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