Memory, context and training are different levers
Locate where information is stored and how it reaches the model before choosing a memory feature, retrieval system or training job.
SELF-PACED READING PATH
Design an agent you can stop
Understand information flow, choose a simple control structure and specify human review before connecting real actions.
WHAT YOU’RE WORKING TOWARD
A proposed state diagram, data-boundary map and failure checklist—not an automatically deployed agent.
You mark your own progress. It stays in this browser; this is not a performance assessment.
Your local AI assistant may still use the internet
Draw the model, retrieval, tool and logging boundaries before assuming that a local application is fully offline.
An agent loop needs an exit
Choose between a fixed workflow and an agent by specifying feedback, budgets, terminal states and the point of human handoff.
Approval is a gate. Recovery is a separate design.
Plan what happens before, during and after human approval, including rejection, changed payloads, restarts and duplicate actions.