Feature Guide

AI Memory

AI Memory keeps GTMship from behaving like every session is day one. It helps the agents reuse verified knowledge about your providers, workflow history, and operating rules so future work starts with context instead of re-discovery.

Persistent context Verified knowledge Workflow continuity Less repetition

What memory is for

Workflows are rarely one-shot projects. Teams refine them over time, connect new systems, adjust business rules, and revisit failed or partial drafts. Memory lets GTMship retain that verified context so the next session can start from what is already known.

What can carry forward

Provider setup

Connected systems, auth expectations, and reusable provider knowledge can be recalled instead of rediscovered.

Workflow history

Saved workflow source and sidecar metadata keep drafts and prior decisions attached to the same workflow identity.

Business rules

Repeated constraints like lead routing thresholds or approval rules can be reused across future revisions.

Session continuity

Future conversations can start from a verified summary instead of relying on the operator to restate every detail.

How later sessions get better

Faster grounding

Agents can begin from known provider and workflow context instead of spending the first part of each session rediscovering your stack.

More consistent revisions

Saved context helps later drafts preserve the same business rules, provider assumptions, and workflow intent across multiple edits.

Less auth re-explaining

When connection patterns and provider setup are already known, the system can focus on the new change instead of restating integration basics.

Better troubleshooting context

Preview outcomes, deploy history, and prior workflow decisions give later debugging sessions a more reliable starting point.

How it works in practice

  1. You connect providers and build or revise workflows.
  2. GTMship stores workflow source, metadata, and useful session context.
  3. The next time you open the project, the agents can recall that prior state before generating or troubleshooting.
  4. The result is fewer repeated explanations and more consistent draft revisions.
Memory improves continuity, but it does not replace live checks. GTMship still validates connections, docs, and runtime safety before acting.

What still gets checked live

  • Connection health: active credentials, token refresh, and auth reachability still need real runtime verification.
  • Grounded API details: GTMship can remember what mattered last time, but it still benefits from current docs or API references when generating new code.
  • Validation and safety rules: checkpoint coverage, runtime constraints, and code shape are checked against the current draft, not blindly inherited.
  • Deployment state: bindings, cloud resources, and runtime status are refreshed from the live project before operators act on them.

Where it helps most

  • Long-lived workflows that evolve over multiple sessions.
  • Teams with repeated provider combinations and approval rules.
  • Projects where a human operator wants less prompt repetition and more consistent revisions.

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