Building an execution-memory loop: how outcomes feed back into recall
What actually happened when an agent ran a task is more useful to remember than what it planned to do — here's how that loop closes.
By Agent Software
Memory that only remembers intent
Most descriptions of "agent memory" focus on conversations: what was asked, what was decided, what context got summarized. That's useful, but it's only half the picture. It captures intent, not outcome.
A team can discuss an approach at length, have an agent implement it, and then never record whether it actually worked. The next session starts from the same summarized intent — with no signal about whether that intent led anywhere good.
What execution outcomes add
Agent Brain is designed to accept a second kind of input: execution results. When a task actually runs — through Agent Harness, through Agent Terminal, or through any tool wired into the memory layer — the outcome of that run can be written back as its own memory entry. Not just "we decided to try X," but "we tried X, and here's what happened."
That distinction matters. A failed approach recorded as a failure is more useful than a failed approach recorded only as a decision, because the next time the same situation comes up, recall surfaces the actual result, not just the plan that led to it.
Why this needs to be a loop, not a one-time log
A static log of outcomes decays the same way any documentation does — it goes stale, gets ignored, or never gets consulted at the moment it would matter. The point of routing outcomes back into the memory layer that also serves plans and context is that the same recall mechanism surfaces both at once, at the moment an agent is deciding what to try next.
Where this shows up across the suite
This loop is most visible where execution happens: Agent Harness runs bounded coding tasks against a verifier gate, and Agent Terminal orchestrates work across a session. Both are natural sources of outcome data — pass/fail, retry counts, what got verified — that Agent Brain can fold into future recall without a human having to manually document what happened.
The honest limitation
This is a design direction, not a claim that every execution path is wired up yet. Not every tool in every workflow reports outcomes back automatically today. The value scales with how much of a team's actual execution surface feeds the loop.
