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  • Try it
  • Examples
    • Enhanced team efficiency and productivity
    • Traceability, efficient conversation history, resumability and more
  1. Overview
  2. Build agentic apps

Build agentic apps

Patterns for agent teams that hand off work, learn together, and resume after failure

Try it

WorkbenchLM

Chat with your datapack in the portal, with nothing to install.

Labs

Guided demos on a live datapack, such as an agent reviewing a pull request against your standards.

Examples

Enhanced team efficiency and productivity

Knowledge handoff with context preserved

Agent B gets Agent A's reasoning, not just its final output. No lost context across agents.

Collective learning across runs

What worked, what didn't, and why — available on the next run when you save it.

Group/team policies and standards

Share a datapack across your team so every agent works from the same playbook.

Traceability, efficient conversation history, resumability and more

Auditable learning trail

Full chain-of-thought traceability for what agents learned and how it flowed — ready for EU AI Act compliance.

Conversation history with tiering

Recent history in-database for fast recall; older history auto-tiered to S3 to control costs.

Agent resumability

Persist full agent and sub-agent state in Meko so any run can be paused and resumed reliably.

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