Persist customer context between Make AI agent runs
At a glance
Make's memory guide provides a concrete read-normalize-reason-route-write pattern keyed to a customer or case, with module-level inspection and recovery paths for missing or malformed state. This workflow is listed under builder, make-ai-agents, agent-memory, data-store, state-management.
OpenAI's data-analyst example combines schema discovery, metric context, read-only SQL, and explicitly saved corrections in one persistent investigation; database execution stays in the application.
A Technically writer documents a month-long Claude Code experiment managing a Meta Ads account: fresh sessions read prior logs, pull performance data, decide, act or abstain, and commit the updated history.
A founder describes a working beta that scans a repository, asks product questions, and writes a behavior contract distinguishing confirmed decisions from unsettled assumptions.
Make's Post-Call Hero case study describes a transcript-driven agent that drafts follow-up email, prepares CRM changes, and can create stakeholder Slack channels, supported by fixed context files and a limited tool set.