I keep seeing this happen. An AI agent runs fine for a while, then just stops. Or it starts making mistakes it wasn't making before. Or it hits an error it can't get past.
And as a non-technical founder, it feels like you have no idea where to start. You can't just open it up and magically figure out what went wrong. You're just stuck.
Has this happened to you? What did you do?
I keep seeing this happen. An AI agent runs fine for a while, then just stops. Or it starts making mistakes it wasn't making before. Or it hits an error it can't get past.
And as a non-technical founder, it feels like you have no idea where to start. You can't just open it up and magically figure out what went wrong. You're just stuck.
Has this happened to you? What did you do?
I keep seeing this happen. An AI agent runs fine for a while, then just stops. Or it starts making mistakes it wasn't making before. Or it hits an error it can't get past.
And as a non-technical founder, it feels like you have no idea where to start. You can't just open it up and magically figure out what went wrong. You're just stuck.
Has this happened to you? What did you do?
I keep seeing this happen. An AI agent runs fine for a while, then just stops. Or it starts making mistakes it wasn't making before. Or it hits an error it can't get past.
And as a non-technical founder, it feels like you have no idea where to start. You can't just open it up and magically figure out what went wrong. You're just stuck.
Has this happened to you? What did you do?
Has anyone here deployed an AI employee (like an autonomous agent that handles sales, research, or outreach) and it just stopped working out of nowhere?
Like it was running fine and then started drifting from the original instructions, or hit an API error it couldn't recover from, or started making basic mistakes it wasn't making before.
did you figure out what went wrong? did you feel like you had any way to fix it without calling in a developer?
I'm genuinely if this is a common issue or if I'm just seeing it in my corner of the internet.
Has anyone here deployed an AI employee (like an autonomous agent that handles sales, research, or outreach) and it just stopped working out of nowhere?
Like it was running fine and then started drifting from the original instructions, or hit an API error it couldn't recover from, or started making basic mistakes it wasn't making before.
did you figure out what went wrong? did you feel like you had any way to fix it without calling in a developer?
I'm genuinely if this is a common issue or if I'm just seeing it in my corner of the internet.
Has anyone here deployed an AI employee (like an autonomous agent that handles sales, research, or outreach) and it just stopped working out of nowhere?
Like it was running fine and then started drifting from the original instructions, or hit an API error it couldn't recover from, or started making basic mistakes it wasn't making before.
did you figure out what went wrong? did you feel like you had any way to fix it without calling in a developer?
I'm genuinely if this is a common issue or if I'm just seeing it in my corner of the internet.
Has anyone here deployed an AI employee (like an autonomous agent that handles sales, research, or outreach) and it just stopped working out of nowhere?
Like it was running fine and then started drifting from the original instructions, or hit an API error it couldn't recover from, or started making basic mistakes it wasn't making before.
did you figure out what went wrong? did you feel like you had any way to fix it without calling in a developer?
I'm genuinely if this is a common issue or if I'm just seeing it in my corner of the internet.
after a few months running agents in production, I keep coming back to something nobody actually says.
it's rarely the reasoning that breaks. the model is fine. the logic is fine. what fails is everything underneath it. stale sessions, conflicting memory, half-finished tasks from three days ago, an expired token, plus everything else that can go wrong 😂
demos work because they start clean. production doesn't. I mean think about it; just a few weeks in and you already have stale context beating out fresh input, retries that compound the error instead of fixing it, browser state nobody tracked, users changing things mid-workflow.
Me personally, one time i spent weeks thinking it was a problem with a model but it wasn't. it was just state management the whole time. the fix isn't a smarter LLM, it's a better way to handle what accumulates when the agent runs unattended for days.
what have y'all found?
after a few months running agents in production, I keep coming back to something nobody actually says.
it's rarely the reasoning that breaks. the model is fine. the logic is fine. what fails is everything underneath it. stale sessions, conflicting memory, half-finished tasks from three days ago, an expired token, plus everything else that can go wrong 😂
demos work because they start clean. production doesn't. I mean think about it; just a few weeks in and you already have stale context beating out fresh input, retries that compound the error instead of fixing it, browser state nobody tracked, users changing things mid-workflow.
Me personally, one time i spent weeks thinking it was a problem with a model but it wasn't. it was just state management the whole time. the fix isn't a smarter LLM, it's a better way to handle what accumulates when the agent runs unattended for days.
what have y'all found?
My techs almost always never remember to ask for for reviews.
Do you have an actual system for this, or does it really just depend on the tech remembering?