Agents are taking on more and more of the work we do as software engineers. We still need to handhold quite a bit of what agents do. Agents can be unreliable and often forget what we have told them before. Engineering better context and verification process can make our software development process more reliable.

One of the underutilized sources of data to improve our process is sitting right there on our laptop. It's the session logs from coding agents. Most agent harnesses (such as Claude, Codex, OpenCode, Cursor) have this.

You can mine these sessions to understand:

* How you are using your agents
* What instructions do you keep on repeating
* Where does your process fail
* What context can you add for your agent to act better next time
* Did your update to the context actually work

The context can be defined in:

* AGENTS.md (or CLAUDE.md)
* In-repo documentation 
* Skills
* Others

I created a skill that runs directly in your agent session. It analyzes your recent sessions, surfaces what you keep repeating, and proposes concrete updates to your context files.

If you want to go deeper, Dreamer has a dashboard that lets you browse your session history and understand how you're working over time: how you're splitting your time between planning, debugging, and implementation, what patterns show up across sessions, and whether your context updates are actually working.

Check it out here on Github: [https://github.com/whistler/dreamer](https://github.com/whistler/dreamer)

What do you think? What instructions are you repeating the most?



Dreamer: Use coding agent session data for context improvement