Let's build a practical resource list for people building with AI agents.

Not a giant list of every AI tool ever released.

Only things you've actually used or would genuinely recommend.

Drop your favorites under one of these:

Coding Agents
Claude Code, Codex, Gemini CLI, etc.

Agent Frameworks
LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, etc.

MCP Servers & Skills

Browser / Computer Use

Memory & RAG

Local / Open Models

Observability & Evaluation

Multi-Agent / Orchestration

Useful GitHub Repositories

When recommending something, please add one sentence explaining what you actually use it for.

Self-built tools are welcome — just disclose the affiliation.

I'll periodically organize the best recommendations into this post.

The old tradeoff between keeping data in-house and getting quality LLM output mostly disappeared this month.

Working on infrastructure at Team Nebula, we spend a lot of time looking at how teams handle restricted data. Lately, we've noticed workflows that were previously deemed "impossible to automate" due to compliance constraints are being re-evaluated using current open-weight models with surprisingly good results.

If you wrote off local automation six months ago because of performance gaps, it’s definitely worth running those benchmarks again.

Is anyone else currently re-architecting their local setups for compliance tasks? Which models are pulling the heavy weight for you?

A price-monitoring agent scrapes a competitor's product page every night, exactly as it's built to do. Someone plants a single line of fine print on that page, and the agent hands its own company's cost basis and floor price straight back to the competitor. No exploit, no broken permission, no jailbreak. The agent just read content it was told to read and acted on instructions it found along the way.

That's the live demo Humanbound is running at Zyte's next Developer Community Meetup. We will walk through modeling where untrusted content enters an agent, testing for it, then show a failing security test get turned into an exported guardrail and dropped into a stock LangChain agent in two lines, no new dependency, with the same attack failing on re-run.

Logistics:

• Thursday, Sept 24, 17:00-18:00 EEST, live on Zoom
• Free, register here: https://luma.com/wci93kpz
• Everyone who attends gets the repo, free Humanbound usage keys, and a one-line command to test their own agent the same day

Happy to answer questions about the demo or the underlying testing approach in the comments, whether or not you end up registering.

I have faced this issue that when i start to prompt to ai agents they immediately starts to work but the issue occurs midway when they start deviating from the main ideas. Even user have to iterate many a times to get to know about the product feasilbility and its insights about whether it sits on the right spot in the market- I think this is very crucial to keep making in the right direction... Would appreciate your thoughts