Agents
Sharing some notes from OpenAI DevDay in parts. The first part matters, since it's on everyone's mind. How do you optimize for cost and perf…
Sharing some notes from OpenAI DevDay in parts. The first part matters, since it's on everyone's mind. How do you optimize for cost and performance? If you are building agentic applications today, the
Sharing some notes from OpenAI DevDay in parts. The first part matters, since it's on everyone's mind. How do you optimize for cost and performance? If you are building agentic applications today, these are 4 of the most important levers you absolutely must try: - prompt caching - reasoning effort - programmatic tool calling - batch request The OpenAI dev docs have plenty of information, but these alone are good starting points for optimizing your agentic applications. Familiarize yourself with these and measure them with evals.
Related
- NEW paper worth reading. A full agentic workflow can be distilled into model weights and run at roughly 100x lower inference cost while pres…
- Agents API is a bigger deal than it seems. OpenAI's bet on making the Codex harness open-source could pay off big time here. This harness-as…
- Small models are cheap to run, but expensive to adapt. The hard part is not only fine-tuning. It is the surrounding loop that involves colle…
Source: DAIR.AI (X) | 2026-10-02