The next run should build on this one.
An agent diagnoses a failed deployment, finds the fix, and records what worked. Its next run should be able to use that work. Minds gives your agent a dedicated place to save progress, decisions, and reusable steps, then retrieve them when the next task begins.
The process changes
A run is only one chapter.
01Read the working context
02Complete the task
03Keep the useful experience
The Mind stays
Retained context
Reviewed the proposal and recorded the outcome.
The review routine stays available for the next task.
proposal.md · source retained with the episode
Keep the progress. Reuse what worked.
Keep the error, the investigation, the successful fix, and any unfinished checks together. On a later run, your agent can retrieve the relevant record and adapt the saved procedure to the current task. Your application chooses what to save and when to bring it back.
Improve without losing sight of what works.
One successful fix may depend on a particular environment. Keep proposed learning separate while your configured checks assess it. For supported learning components, save a checkpoint before applying an update so you have a compatible recovery state available.
Give each run a useful starting point.
- Events
- Save actions, outcomes, and context
- Procedures
- Store steps an agent can reuse
- New learning
- Check before adding to trusted knowledge
- Recovery
- Restore supported learning components from a checkpoint
The next run starts with this one.
Start recording useful decisions and outcomes in a dedicated Mind, then retrieve them when your agent begins its next task.