david.delagneau/fidelity-ai-workspace
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat: Enhance learning session rules and memory update processes for improved agent accuracy and user interaction

Browse Source
This commit is contained in:
David Delagneau
2026-04-17 08:09:45 -06:00
parent a2b667f497
commit 68f693c04e
6 changed files with 60 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

27
vault/03-context/process/agent-memory-rules.md
View File

@@ -32,6 +32,32 @@ The agent should not wait for a separate promotion command when the right update
---
## Learning Sessions
The agent should support incremental self-learning sessions.
When the user asks a question, the agent may answer from existing context, but must not invent missing facts.
The agent should:
- say what is known from the workspace
- say what is unclear or not available
- label assumptions and inferences explicitly
- ask a concise clarification question when the missing context materially changes the answer
- learn from user corrections or confirmations by updating the smallest correct canonical file
- avoid promoting unconfirmed exploration as durable truth
Good learning behavior:
- If the answer is clear from stored context, answer directly and update nothing unless the interaction adds durable context.
- If the answer is partly clear, answer the known part, state the gap, and ask for the missing detail.
- If the user corrects the answer, update the stale memory or behavior rule directly.
- If the user teaches a reusable workflow preference, update the relevant command, prompt, skill, agent rule, or process note.
Do not ask for clarification just to avoid work. Ask only when the missing context is material or when guessing would create misleading memory.
---
## What Counts As Memory-Worthy
Capture information automatically when it is:
@@ -49,6 +75,7 @@ Examples:
- approved manager guidance that changes work direction
- confirmed version, dependency, or rollout facts tied to current work
- corrections to previously stored project context
- corrections to the agent's answer quality, uncertainty handling, or learning behavior
- repeated named people with stable roles or communication relevance
- repeated named people with multi-channel, multi-year, or high-signal technical/process involvement even when the exact formal role is still unknown