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rwilinski

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Agentic Evals Pyramid

rwilinski.ai
1 points·by rwilinski·tahun lalu·0 comments

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

github.com
6 points·by rwilinski·2 tahun yang lalu·1 comments

Show HN: Claude and Apple Notes integration using MCP

github.com
1 points·by rwilinski·2 tahun yang lalu·0 comments

The Principles for Reliable, Safe and Fast AI Agents

rwilinski.ai
2 points·by rwilinski·2 tahun yang lalu·1 comments

Full-stack RAG app built on Cloudflare

github.com
36 points·by rwilinski·2 tahun yang lalu·1 comments

Generating structured data with LLMs – Beyond Basics

rwilinski.ai
3 points·by rwilinski·2 tahun yang lalu·0 comments

Benchmarking OpenAI's Structured Outputs

rwilinski.ai
2 points·by rwilinski·2 tahun yang lalu·0 comments

Show HN: Talk to Your AWS Cloud

chatwithcloud.ai
1 points·by rwilinski·3 tahun yang lalu·0 comments

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

github.com
252 points·by rwilinski·3 tahun yang lalu·100 comments

Show HN: CMD and K for AWS Console

cloudtempo.dev
1 points·by rwilinski·4 tahun yang lalu·0 comments

comments

rwilinski
·2 tahun yang lalu·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
·3 tahun yang lalu·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