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rwilinski

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Agentic Evals Pyramid

rwilinski.ai
1 points·by rwilinski·ano passado·0 comments

Show HN: AWS MCP – Talk with Your AWS from Claude Using Model Context Protocol

github.com
6 points·by rwilinski·há 2 anos·1 comments

Show HN: Claude and Apple Notes integration using MCP

github.com
1 points·by rwilinski·há 2 anos·0 comments

The Principles for Reliable, Safe and Fast AI Agents

rwilinski.ai
2 points·by rwilinski·há 2 anos·1 comments

Full-stack RAG app built on Cloudflare

github.com
36 points·by rwilinski·há 2 anos·1 comments

Generating structured data with LLMs – Beyond Basics

rwilinski.ai
3 points·by rwilinski·há 2 anos·0 comments

Benchmarking OpenAI's Structured Outputs

rwilinski.ai
2 points·by rwilinski·há 2 anos·0 comments

Show HN: Talk to Your AWS Cloud

chatwithcloud.ai
1 points·by rwilinski·há 3 anos·0 comments

Personal Concierge Using OpenAI's ChatGPT via Telegram and Voice Messages

github.com
252 points·by rwilinski·há 3 anos·100 comments

Show HN: CMD and K for AWS Console

cloudtempo.dev
1 points·by rwilinski·há 4 anos·0 comments

comments

rwilinski
·há 2 anos·discuss
Building AI agents is hard. Most attempts end up with brittle systems that break in production, cost too much to run, or worse - make costly mistakes that could have been prevented.

Fortunately, there are several core principles that I’ve learned while building agents that actually work. Hope you find it useful!
rwilinski
·há 3 anos·discuss
I made Dynobase [1], an alternative GUI for DynamoDB. Passed 2k/mo few years ago. Runs 100% automatically now, I spend ~2h/week mostly responding to customer inquiries. I could leave my full time job but I just like it (and money) too much.

[1] https://dynobase.dev