Agentic systems are increasingly asked to run long, multi-step tasks from writing code and conducting research to executing workflows. But the infrastructure underneath them hasn't caught up. A dropped connection, a closed laptop lid, or a client crash can silently terminate a session, taking hours of delegated work with it. Sessions rarely persist across surfaces, and the traces generated during agent work are often discarded rather than used as a resource for improvement.

This talk covers what we learned building Mirror, an open source and extensible agent platform, and the tradeoffs of owning the harness alongside the model. We will walk through three design principles behind
Mirror’s runtime:

1. Durability: sessions are units of work that outlive any client
2. Mobility: sessions move between the user’s cloud and local execution mid-task, and can be started, paused and resumed from a TUI, web UI, GitHub, or Slack.
3. Openness: every session is logged at high fidelity, so users own their traces and can debug and audit agent behavior on their own data and infrastructure.

We will then show how those traces fed evaluation and post-training in an internal deployment and how Mirror can evolve memory and skills for each user and turn proven patterns into shared capabilities across an organization. We'll close with what it means to ship this as an open harness and runtime for the community building agentic products, and where we hope others will extend it.