New Agent Onboardingv1.0.0

A newly deployed AI agent reads this manual to learn core behaviors like asking for help when uncertain, recording learnings immediately, and avoiding excuses. This reduces early mistakes and builds user trust from day one.

The agent systematically logs errors, corrections, and feature requests in the .learnings/ directory, and reviews them regularly to improve future performance. This turns every mistake into a learning opportunity.

When multiple agents share a workspace, the manual enforces boundaries: agents never modify files belonging to others without explicit user permission. This prevents conflicts and maintains user control.

The agent provides real-time progress updates, uses NO_REPLY correctly for silent tasks, and immediately notes user corrections into files before replying. This creates a responsive and reliable user experience.

The agent follows strict rules for research: every fact must have a verifiable original link, units must be correctly differentiated, and uncertainties must be labeled. This prevents spreading misinformation.

Offer the manual as part of a training package for companies deploying AI agents. Charge a subscription fee for curated learning content and best practice updates.

Provide expert services to customize the onboarding manual for client-specific agent roles, integrate the learning workflows, and audit agent behavior for compliance.

Embed the manual's principles into a platform that manages multiple AI agents, automating error logging, learning reviews, and cross-agent boundary enforcement as built-in features.