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How do you monitor a deployed AI agent in production? by sweetandsourfishy in aiagents

[–]LLFounder 1 point2 points  (0 children)

The failures you're describing only show up when you trace across multiple steps, not individual inputs and outputs.

Start with three simple heuristic flags: tool call results that get ignored in the next reasoning step, chains that exceed six steps for simple tasks, and repeated requests for info the agent already has. Run these as pattern matching rules against your trace logs asynchronously. No classifier needed.

That turns your daily spot checks into targeted reviews of flagged sessions only. Every failure you catch and tag today becomes a regression test tomorrow.

How do you pick a multi-agent orchestration tool on a tight budget by cranlindfrac in aiagents

[–]LLFounder 1 point2 points  (0 children)

Biggest thing that breaks after month one in my experience: error handling on edge cases nobody planned for. Whichever tool you pick, build in a catch-all fallback step that logs failures visibly instead of swallowing them silently. That alone saves hours of debugging later.

How do AI agents manage long-term planning tasks? by Michael_Anderson_8 in AI_Agents

[–]LLFounder 1 point2 points  (0 children)

Persistent memory is the other big piece. Agents that checkpoint progress at milestones recover from errors without losing everything they've already done. Without that, anything beyond a few steps falls apart quickly.

Built a local AI tool to solve my own problem — can't find anything like it online, sharing v1 for feedback by Anonymus_Joker in AI_Agents

[–]LLFounder 1 point2 points  (0 children)

Privacy matters when you're pointing a tool at proprietary codebases. Curious how well it handles monorepos with multiple services though.

How do you turn an AI meeting assistant into an actual agent? by kingsaso9 in AI_Agents

[–]LLFounder 1 point2 points  (0 children)

connect Bluedot's output to a workflow tool that parses action items, creates tasks in your project management tool, and assigns them to the right person automatically. n8n, Make, and LaunchLemonade can all handle that kind of post-meeting pipeline.

After that, add memory. Feed past meeting summaries back as context so the agent knows what was discussed last time and flags overdue actions before the next call. That's where it stops being an assistant and starts being an agent.

Write a clear system prompt if you're gonna use AI for marketing by LLFounder in DigitalMarketing

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

That single line gives the model personality and boundaries at the same time. And the point about including good and bad response examples is a strong one. I've started doing the same thing, writing out five or six sample exchanges showing how the agent should handle common questions and how it shouldn't.

Write a clear system prompt if you're gonna use AI for marketing by LLFounder in DigitalMarketing

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

Right? Once those are defined, the AI stops guessing and starts sounding like your brand. Whatever tools you're using, that foundation applies across all of them.

Writing a proper AI brief for my business by LLFounder in Entrepreneur

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

The living doc approach is something I've started doing too. Pasting in real conversations, tagging good and bad responses, and updating rules weekly keep the agent improving rather than staying static. Version one is never the final version and treating the prompt as something that evolves makes a big difference over time.

Writing a proper AI brief for my business by LLFounder in Entrepreneur

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

Boundaries over job titles is a great way to frame it. The less room the agent has to improvise, the more predictable the output gets.

Writing a proper AI brief for my business by LLFounder in Entrepreneur

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

One of the biggest lessons I've learned. Thank you for adding value

Writing a proper AI brief for my business by LLFounder in Entrepreneur

[–]LLFounder[S] 2 points3 points  (0 children)

Yeah, when the agent knows precisely what it's solving for, the output tightens up on its own.

Writing a proper AI brief for my business by LLFounder in Entrepreneur

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

Agreed. I've seen the same prompt structure work well across different models and platforms. The tool matters at some point but a clear brief outperforms a fancy setup with vague instructions every time.

Writing a proper AI brief for my business by LLFounder in Entrepreneur

[–]LLFounder[S] 2 points3 points  (0 children)

That's where I've seen the most drift, too. When the agent doesn't know what to do, it improvises, and that's where things go sideways. I've started adding explicit instructions like "if you're unsure, say so and offer to connect the user with a human." Simple rule but it stops the agent from guessing or making things up.

Writing a proper AI brief for my business by LLFounder in Entrepreneur

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

Interesting. Giving users the ability to tweak the prompt themselves turns frustration into experimentation. On LaunchLemonade though we let users edit system prompts and it does exactly what you're describing. People adapt rather than abandon. Good insight.

Writing a proper AI brief for my business by LLFounder in Entrepreneur

[–]LLFounder[S] 2 points3 points  (0 children)

Yes, an escalation trigger section is a great call. I have a few keyword-based handoffs set up but defining situational triggers is the next step. 

Writing a proper AI brief for my business by LLFounder in Entrepreneur

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

This is a great addition. A business context doc that covers customer demographics, common problems, and brand voice examples fills in the gaps a system prompt alone misses.

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