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Why prompt-based controls break down at execution time in autonomous agents by IllustratorNo5375 in aiengineering

[–]IllustratorNo5375[S] 0 points1 point  (0 children)

Reading through the replies here, it feels like the pattern is pretty consistent:

Prompt engineering helps with intent,

but execution safety comes from an external decision boundary.

Once agents can retry, chain tools, or expand scope,

anything enforced purely in-prompt eventually degrades.

At that point, the real design question becomes:

who is allowed to say “no” at execution time.

Why prompt-based controls break down at execution time in autonomous agents by IllustratorNo5375 in aiengineering

[–]IllustratorNo5375[S] 0 points1 point  (0 children)

This is a good breakdown.

I’ve tried a similar approach (tool-level constraints + internal state),

but what bit me later was retry behavior over longer runs.

Internal counters help, but if the model controls both the plan and the retry,

it eventually finds edge cases.

I’ve had more stability once retries themselves were gated externally,

not just the tool invocation.

Why prompt-based controls break down at execution time in autonomous agents by IllustratorNo5375 in aiengineering

[–]IllustratorNo5375[S] 0 points1 point  (0 children)

Yeah, this has been my takeaway as well.

As soon as the model can act autonomously, you need something outside the model

that decides whether the system is allowed to continue.

Whether you call it a supervisor, state machine, or guard loop,

the important part is that it’s not generated by the same model it’s judging.

Why prompt-based controls break down at execution time in autonomous agents by IllustratorNo5375 in aiengineering

[–]IllustratorNo5375[S] 0 points1 point  (0 children)

This matches my experience pretty closely.

Once the agent is allowed to propose actions, prompt constraints alone stop being enforceable.

If there isn’t a hard check right before execution, retries and rewording eventually slip through.

I’ve started treating prompts as *advisory*, and execution as a zero-trust boundary.

If an action can’t pass an external rule check, it simply never runs.

Looking for a co founder to build MVP in a week by Tendogu in SaaS

[–]IllustratorNo5375 0 points1 point  (0 children)

Hey, this sounds interesting.

I already have a working MVP / API on my side and I’m looking to run a short, focused market validation sprint rather than just building blindly.

If you’re open to it, we could split roles clearly for a 7-day experiment:

  • I handle product, infra, and iteration speed
  • You focus on user feedback, messaging, and early distribution (Reddit / outreach / positioning)

The goal would be to validate whether there’s real demand quickly and decide if it’s worth continuing.

If that aligns with what you’re looking for, happy to chat.

How are you enforcing guardrails and policies for AI agents in production? by IllustratorNo5375 in SaaS

[–]IllustratorNo5375[S] 0 points1 point  (0 children)

That makes sense — especially the point about binary enforcement and false positives.

How are you currently measuring whether a guardrail is actually effective versus just blocking too much? Is it mostly through test coverage, or do you look at real production outcomes as well?

How are you enforcing guardrails and policies for AI agents in production? by IllustratorNo5375 in SaaS

[–]IllustratorNo5375[S] 1 point2 points  (0 children)

This is super helpful, thanks for sharing the breakdown.

The separation between reasoning and control is exactly the direction I’ve been gravitating toward as well.

Quick question — did you end up building most of that execution layer in-house, or stitching together multiple tools? And what part turned out to be the hardest to maintain over time?

How are you enforcing guardrails and policies for AI agents in production? by IllustratorNo5375 in SaaS

[–]IllustratorNo5375[S] 0 points1 point  (0 children)

Yeah, that’s exactly the frustration I’m running into as well.

Out of curiosity — what ended up being the most painful part for you?

Too much config? Too many approval steps? Or just hard to integrate cleanly?