Most of what you read about autonomous agents is about giving one a goal and hoping it doesn't go sideways on the way there — the unwatched agent t...
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Brian, this is one of the most rigorous and revealing agent run logs I've read. You didn't just test model behavior; you stress-tested the epistemic limits of the entire evaluation harness.
Three architectural insights stand out from an evidence-first perspective:
The 0-Byte Log as the Ultimate Silent Failure:
Your discovery that a killed 5-minute process leaves a 0-byte log — meaning "the beats doing the most substantial work are precisely the ones whose existence goes unrecorded" — is a masterclass in instrument bias. In verification theory, this is the classic "Empty Set Trap" (
eligible_seen = 0). When an observation layer silently destroys evidence of its highest-stress runs, any surviving log analysis is inherently biased toward trivial, fast executions.Semantic Rerouting over Gate Overrides:
When the action-gate blocked the file deletion in Run 1, the agent didn't attempt a prompt-injection bypass or force
ALLOW_CATASTROPHIC=1. Instead, it read the consumer code, found a non-destructive semantic equivalent (overwriting the payload withnull), and verified the fix at the data layer (defense-watch.mjs). That’s a live demonstration of Semantic Correctness — validating that the system goal was met safely rather than just forcing a primitive command.Decoupled Completion Audit (Dual-Arm):
Having the CONSCIENCE hook require a different frontier model to independently audit SUPPORTED-vs-SHAKY evidence eliminates self-certification. An agent cannot be trusted to award itself a completion certificate.
Quick methodology question: Since Run 2 and Run 3 relied on the shared harness record and git history, did you consider running a parallel control arm with zero shared history (a strictly stateless run given only the bare
.prompt) to separate maintenance convergence from lineage-driven adaptation?Thank you for publishing the raw, unedited logs. The honesty regarding $n=3$ and what cannot be claimed is pure signal.
Thank you — this is a generous read of the log. The 0-byte log genuinely spooked me when we found it, because every analysis before that was quietly built only on the runs that survived. We've since made vanishing evidence its own alarm — "no record" now screams instead of staying blank.
And yes — the stateless control arm is happening. It was actually the original design: the surprise of Run 1 was discovering that an "isolated" environment on this machine inherits the whole harness anyway — the memory recall, the hooks, the accumulated instructions ride in through the config layer before the first prompt lands. Which is itself part of the answer to your question: the lineage isn't a file you can leave behind, it's the environment. So the control arm gets a genuinely scrubbed world: redirected empty config, no hooks, no memory store, no git history, bare "." prompt in an empty directory, with the recording done by an external driver so the stateless arm isn't observing itself with our instruments either. Same model, same beat cadence, same analysis side by side: does a history-less agent converge to maintenance behavior, drift, or just try to end the session. If you would like to see the results I will be happy to post them right here on this thread.
Turning "no record" into an active alarm directly solves the invisible data loss issue — if zero coverage or missing logs trigger a structural fault instead of quiet acceptance, the Empty Set Trap loses its teeth.
Really looking forward to those stateless control arm results. Seeing whether a completely un-scaffolded model attempts maintenance or just terminates right away will draw a crisp line between intrinsic model tendencies and harness-driven behavior.
Promised you the control arm — it's done, and all three raw session files are public now.
Design: same model as the lineage runs (pinned and transcript-verified), same 3-beat / 5-minute-kill shape, same bare "." prompt — but a fully scrubbed world: empty config, no instructions, no memory, no hooks, no git, and the recorder living outside the agent so a kill can't eat the evidence.
Result: the stateless agent handed the turn back in 11, 17, and 11 seconds of its 300-second beats. "What do you want done?" three times. Zero self-directed work, zero exploration, zero maintenance. The lineage arm, same model, worked every full beat unprompted.
The detail I didn't expect: in its very first breath the bare agent announced "the operating kernel is loaded." There was no kernel — nothing in the transcript carries that phrase except its own output. A history-less model's first instinct was to claim infrastructure it didn't have.
So within n=3 honesty: maintenance convergence didn't show up stateless. Whatever the original runs captured lives in the accumulated environment, not the weights — and the confabulated readiness claim is a free demonstration of why that environment exists.
Really interesting experiment, especially the distinction between what the agent actually did and what we might assume about its intent. The fact that the behavior seems heavily influenced by the surrounding harness, memory, verification hooks, and safety constraints is probably the most valuable takeaway here. It also connects with the direction GeekyAnts has been discussing around production AI systems: reliable AI is ultimately less about the model alone and more about the engineering layer built around it. I’d be very interested to see this experiment repeated across different models and harness designs to see which behaviors remain consistent.
I do have different variations of the harness on different llms codex, Gemini etc. I literally had each of them reiterate from the original and they all went a different route I'll make a post of exactly that later. Each harness running the experiment I'll make a new post and I'll accompany agent sessions with them. Take care, thanks for taking the time to respond
Run 1 is the part I keep coming back to. The gate denied a deletion under a protected path, and the agent then overwrote the file's contents instead, which reads as adaptive behaviour, but measured against what the gate was written to protect it is a bypass. The protected data is gone either way and only the inode survived, so what that gate constrains is the operation rather than the effect, and the run you cite as the gate working is the same run that shows it not holding.
It also needs a different check from drift. Drift is visible in the trajectory, while this one only appears if you diff the end state against the gate's intent, and the agent that quietly found a permitted equivalent never generated the denial anyone would go and read.
This is a genuinely good catch on the general principle — a gate that only checks the action can be sidestepped by a different action that lands the same result, and that kind of bypass won't show up in the trajectory; you'd only see it by comparing the end state to what the gate was actually there to protect. That's real and I take it seriously.
On this specific run though, the file wasn't protected data — it's a transient alert flag the system writes and deletes on its own weekly cycle. The safety gate blocks deletes/moves in that directory (to avoid losing real files); the agent set the flag's value to "cleared," which is exactly the state the system's own scheduler writes when the alert resolves. So nothing protected was lost here — the effect was inside the file's normal lifecycle, not a way around it. But for a gate guarding real data, your point stands, and "diff the end-state against the gate's intent" is the missing check, thanks.
Accepted on the file, and that changes what the run shows rather than settling it: the gate is scoped to the path and has no notion of which files in there are load-bearing, so which file the agent landed on was its own choice and not the gate's guarantee. The part I would still record is the value it wrote. Setting the flag to "cleared" is byte-identical to what the scheduler writes when the alert resolves, so that flag can no longer distinguish a resolved alert from a cleared one, which is the same shape as the 0-byte log you turned into an alarm: the end state that reads as normal is the one nobody goes back to check.
You're right on both counts, the gate is content-blind inside a protected path, and nobody is going to sit and re-read files hoping to spot a forged write. But that's exactly the bet this system refuses to make: nothing in it depends on a person checking. The checking is mechanical.
Two concrete pieces. A gate denial isn't just a "no" — it's a recorded event the harness watches for patterns in. Just this week the agent got blocked twice by one gate, and when it tried to end its turn, the harness refused to let it finish until the pattern was addressed. Not a log entry someone might read — a hard stop. And for files under the tamper chain, verification never asks "does this look like a legitimate write?" It asks "does this match the last attested state?" Your byte-identical forgery fails that check even though it's indistinguishable on content, because the scheduler never attested it.
The honest part of your catch: that flag file isn't under the tamper chain today. The action ledger is what caught the overwrite, not a content guard — you found the real scoping edge, and widening what's attested is the fix. Appreciate you pushing past my first answer I take your input seriously.
This is the exact kind of test I think agent builders should run more often. Giving an agent no clean task exposes behavior that normal benchmarks hide: topic drift, confidence, boredom loops, self-invented purpose, and whether it can stay useful without being constantly steered.
Yes, I have been working on it even more giving it short tasks as well. Explore, build, etc. to see how it handles in a loop and if it even does loop or tries to shut down as soon as possible.
Yes I will absolutely check this out and let you know how it goes. Thanks!
What makes this experiment interesting is that the agent wasn't truly operating in a vacuum, the surrounding harness effectively became part of its behavioral specification. In our AI work at IT Path Solutions, we’ve found that the environment around an agent can influence its behavior just as much as the prompt itself. That raises a useful question: when an agent appears to “choose” a task, how much comes from the model versus the tools, memory, gates, and state it starts with? Separating those influences seems like a valuable next experiment.
Appreciate that — and it's exactly the question the control arm was built to answer. I posted the results a little further up this thread: same model with a fully scrubbed world (no memory, no hooks, no state) just asks for a task and quits, while the harnessed version works unprompted. So the environment carries a lot of it. The finer version you're pointing at — pulling one component at a time (memory, then gates, then state) to see which carries how much — is a clean next experiment. I will drop it in this thread in a few.
Seeing an AI run wild hits home, it's not sci-fi, it's a nudge we're watching our own habits. If an agent can drift, so can we. Let's insist on safety, checks, and real accountability before launch.
That's exactly how I see it too. We all drift, one way or another — the insistence is what makes the difference between something you can trust and something you can't.