agenteo

6 ms·

1.
by agenteo 5mo ago
I wrote this after seeing the same pattern a few times: AI makes it easy to generate tickets that are better formatted, but not better justified. I call them “Zombie Barbies” — tickets that look finished on the surface, but don’t clearly co
2.
by agenteo 6mo ago
A PM actually used that very flow at my client :D Input: I just hacked claude code soutions for 4 hours withoutany local testing and pushed a PR and the CI build broke. Now I need actual devs helping figuring out what's wrong. Output:
3.
LLM and MCP: A simple introduction to the brain and hands of modern AI(teotti.com)
1 points by agenteo 7mo ago|1 comments
4.
by agenteo 7mo ago
An LLM without MCP is a brain thinking with its eyes closed. LLMs are trained on static data, then frozen. Ask one to query your production database or pull yesterday's error logs, and it can't. It's like Mr. Anderson living
5.
Standards for Shipping Production LLM Features(teotti.com)
1 points by agenteo 7mo ago|1 comments
6.
by agenteo 7mo ago
Product can't tell if prompts improved. Engineering optimizes prompts without clear performance thresholds. The CEO discovers runaway costs too late. A practical checklist for integrating LLMs into your application: test datasets, eval
7.
Generate product insights by giving your AI agent DB access and app source code(teotti.com)
1 points by agenteo 7mo ago|1 comments
8.
by agenteo 7mo ago
I've been connecting AI agents to production databases via MCP (Model Context Protocol) for product analytics. The problem: when you ask "how many records are running?" the agent sees status values 0, 1, 2, 3 — and guesses wh
9.
Simulate order by field with Mongo DB aggregates(teotti.com)
1 points by agenteo 12y ago|0 comments