HN Explorer

Ask HN: How is your company managing internal AI agents?

2 points by krsna_paulg ↗ HN
We're a small team researching how companies handle the operational side of internal AI agents -- the ones you've built for finance, ops, or marketing workflows. Not the off-the-shelf SaaS tools, but the custom agents your engineering team shipped. Specific things we're curious about:

How many agents are running internally that you know of? Who manages them day-to-day -- engineering or the business team that uses them? How do you track what they cost (LLM API fees, compute)? If the business team wants to change the agent's behavior, what's the process?

Genuinely trying to understand the landscape, not selling anything.

2 comments

[ 4.6 ms ] story [ 7.2 ms ] thread
reggz
can treat each internal agent like a small product: one owner, one budget, and one event ID that bundles retries and tool calls into the true cost per successful outcome.

If you only track provider spend, nobody knows what one useful outcome actually costs. Behavior changes should go through the same path as product changes (review/audit trail/rollback)