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Decide whether agent state is your product or whether an existing assistant needs selected reference material.
Your assistant gave a good answer yesterday. Today a different process starts: what should it still know, and who is allowed to change that knowledge? Letta’s current Agent SDK makes a durable agent the central object. Consider HeyBrain when the immediate task is a reference workflow for an assistant you already use. These approaches can overlap; a claim that Letta has no shared memory would miss its current documentation. Start with the state you need to keep and the ownership you can maintain. Method: primary vendor sources reviewed on 6 October 2026; no hands-on head-to-head benchmark. Diagrams and pilot stories are fictional evaluation examples, not screenshots, customers or measured results.
In a fictional research pilot, assign an agent a stable identity and a permitted project brief. Decide what should survive a new session and what should remain specific to one task. Record your expectations before trying the workflow.
A shared repository or reference set raises an editorial question: who can change the accepted decision? Specify an owner, a correction process and a review date before inviting another assistant to use it.
Letta is a candidate when developers want durable agents as part of their application and need to configure how those agents resume and use memory. Compare the current SDK and deployment path rather than assuming legacy examples describe the current design.
The current Agent SDK describes persistent agent identity and memory, with sessions that resume an existing agent.
For your application, distinguish agent identity, conversation and process lifetime. A continuity exercise should test those distinctions without assuming every piece of chat context survives unchanged.
Letta documents shared memory repositories and a self-hosted git-remote option. Saying it has no shared knowledge would be misleading.
Check which deployment you will use and who can edit the shared content. Run a fictional correction exercise in the actual configuration; this comparison establishes no permission or conflict-resolution result.
First list what has continuing value: accepted decisions, stable preferences and current references. A long transcript can contain contradictory or sensitive material.
Use one approved brief and one superseded version. Decide which should be authoritative and compare the answer after restarting the relevant session. Record missing context rather than hiding it in a new prompt.
An existing assistant may only need selected knowledge for a defined question. That can justify testing HeyBrain without rebuilding your application around another agent runtime.
Confirm the exact supported client and input path. Count the cost of keeping the reference current as well as the benefit of using it; the page does not promise universal memory or automatic source write-back.
| Attribute | HeyBrain | Letta |
|---|---|---|
| Primary choice | A separate reference workflow for a chosen assistant | A durable-agent SDK for an application |
| State model | Test the actual capture/retrieval behavior you need | Agent identity and memory persist across resumed sessions |
| Shared material | Verify sharing and editing for the chosen setup | Shared repositories; deployment-specific options |
| Deployment | Confirm the supported hosted workflow | Managed, local and self-hosted paths |
| Pilot | One approved brief, its superseded draft and an unsupported question | The same fictional continuity exercise |
| Acceptance | Current answer, maintained reference and clear writing ownership | The same criteria; no runtime benchmark reported |
Compared against publicly available information, last checked 6 October 2026. Products change. Tell us if something here is out of date: hello@heybrain.io
Vendor documentation checked on 2026-10-06. These sources describe published policies and features; they are not independent tests of your configuration. The fictional pilot examples above are not measured results.
The current Letta Agent SDK supports creating and resuming stateful agents across sessions, with managed, local and self-hosted deployment paths. The documentation lists V1 SDK separately as legacy.
Letta documents agent memory as a git-backed repository projected through MemFS. Shared repositories are a cloud feature; self-hosted agents can share through their own git remote.
Keep your original agent and references intact. Use a fictional or approved brief and document the receiving workflow before sending it.
Do not assume Letta memory repositories, agent identities or history automatically map to HeyBrain. Compare one useful task and retain a clear way to stop the pilot.
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