Sponsored by YugabyteDB
Every agent session starts cold. Compaction drops the early decisions, a system crash loses your spot, and the next run (or the next agent) has to re-derive what was happening.
This webinar will share what teams are converging on for agents that outlive their context window. Keeping state outside the window, handing off before it fills up, and verifying when resuming the work the next day. We will show how a coding agent hits its limit mid-task and hands off to a second agent on another coding harness, which picks up the previous task without needing to reopen settled decisions or retry rejected fixes.
We will discuss agentic context handoff through an agent skill as well as through a deterministic harness hook.
You will also see how both flows can break, so you can leave the session able to identify a successful and accurate way to resume work with your LLM.
Questions this webinar answers:
What context does a long-running agent need to keep between sessions?
Where should state be stored so a different agent, tool, or person can resume from it?
When should an agent hand off, and how do you decide?
Skill or hook: what makes an agent capable of handoff, and what makes it reliable?
How do you verify a resumed agent is working from real context?
Connect with YugabyteDB:
cloud.mekodata.ai
docs.mekodata.ai
discord.gg/8stPN8Tdh
