This is a submission for the Hermes Agent Challenge: Write About Hermes Agent
TL;DR
Traditional automation assumes software execution is predict...
For further actions, you may consider blocking this person and/or reporting abuse
Redefining execution boundaries is critical as agentic workflows move from experimental to production. Seeing how Hermes handles these transitions offers a compelling look at controlling autonomy without sacrificing performance. It effectively challenges the status quo of agent development.
Exactly. That balance between autonomy and control was the interesting part for me while going through Hermes.
A lot of agent discussions focus mostly on capability, but once these systems move closer to production, the boundaries around execution, verification, and security start becoming just as important.
The boundary I keep coming back to in client work isn't action-type, it's cost-of-rollback. An agent can cross anything that reverses in O(1) (scratch file, log entry, in-memory cache). Anything O(n) or irreversible (sent email, dropped table, signed commit) sits behind explicit token approval. Type-based gates miss too many side effects, cost-based ones don't.
I was mostly thinking about boundaries in terms of action types, but looking at it through rollback cost probably makes much more sense once real production systems are involved.
This resonates — the execution boundary concept is exactly what we hit running Hermes in production. We found that without explicit guardrails around tool access and context budget, agents tend to leak state across boundaries in subtle ways. The killer pattern for us was separating planning (what to do) from execution (doing it) with a thin validation layer in between. Curious if you've run into boundary-crossing issues with shared memory between agents, and how you handled it.
Yeah, that split between planning and execution feels much safer once agents start operating in production environments.
And the shared-memory part feels tricky too because subtle boundary leakage seems much harder to notice than obvious execution failures. I haven’t experimented with multi-agent shared memory yet, but it feels like one of those areas where small decisions around isolation and context handling can create problems very quickly.
Yeah the shared-memory leakage is subtle — we run two Hermes agents (one for experimentation, one
Looks like the message got cut off 😅 curious where you were going with that setup though, especially the separation between the 2 agents.
What’s one thing you would never let an autonomous agent do completely on its own?
I’ll go first: I still wouldn’t feel comfortable letting an autonomous agent make production infrastructure or security-critical changes entirely on its own. There are just too many edge cases and security concerns where I’d still want strong verification and human oversight involved.
Yeah exactly — the message got cut off! 😅 What I was saying is we run two Hermes agents with deliberately different memory scopes: one for day-to-day task execution (reads from a shared SQLite store but writes to a sandboxed namespace), and one for experimentation and schema changes (has broader write access but requires manual approval for production writes).
The key insight was that isolation at the memory namespace level mattered more than isolation at the tool level — both agents could call the same tools, but they could not corrupt each other's state because their memory spaces were walled off. The coordinator sits in between and decides which insights from the experimental agent are stable enough to promote to production memory.
Has that matched your experience with execution boundaries?
That setup makes a lot of sense, especially the separation at the memory namespace level instead of only at the tool layer.
I think that’s what makes these execution boundaries interesting too. The difficult part is not always preventing obvious failures, it’s preventing subtle state contamination that slowly affects agent behavior over time.
And having the coordinator decide what gets promoted into production memory feels like an important boundary by itself.