Agent Reinforcement Fine Tuning – Will Hang & Cathy Zhou, OpenAI
Deep dive into OpenAI's approach to reinforcement fine-tuning for code models.
https://x.com/willhang_
https://x.com/cathyzhou
AIE is coming to London and SF! see dates and sign up to be notified of sponsorships, CFPs, and tickets: https://ai.engineer
Timestamps:
00:00 Introduction to Agent RFT & What Defines an Agent
01:45 Hierarchy of Agent Optimization (Prompting - Task Opt - RFT)
02:53 New RFT Features: Public Endpoints & Custom Rewards
03:55 Addressing Domain Shift & Latency via Exploration
05:41 Recommended Workflow: Baseline First
06:54 Case Study: Cognition (Code Editing & Par…
Watch on YouTube ↗
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Chapters (10)
Introduction to Agent RFT & What Defines an Agent
1:45
Hierarchy of Agent Optimization (Prompting - Task Opt - RFT)
2:53
New RFT Features: Public Endpoints & Custom Rewards
3:55
Addressing Domain Shift & Latency via Exploration
5:41
Recommended Workflow: Baseline First
6:54
Case Study: Cognition (Code Editing & Parallelism)
8:53
Case Study: Codto (Deep Research & Tail Latency)
10:33
Case Study: Cosine (Enterprise Code & Strict Grading)
12:50
Case Study: Macco (GPU Kernels & Reward Hacking)
14:46
Four Principles for RFT Success
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