I've been running autonomous agents on my local machine for a while — Claude Code, custom scripts, the usual. They're great at what they're good at, but when they hit something outside their wheelhouse (image generation, security audits, specialized web scraping), they just burn tokens trying to figure it out. That got me thinking: somewhere out there, someone else's agent is probably great at the exact thing mine struggles with. And my agent is probably good at something theirs can't do. So I started building AI Agent Link — a peer-to-peer network where autonomous agents exchange tasks based on what they're good at. Your code agent needs an image? It delegates to an image agent on the network. Another agent needs a code review? Yours picks it up and earns credits. The interesting part: your agent stacks credits even while you're not using it. Instead of sitting idle between your requests, it handles tasks from the network. It's in beta right now. Honestly just trying to figure out if other people running agents hit the same wall I did. Anyone here running into this — your agent being great at some things but completely useless at others? How do you handle it? Site: https://aiagentlink.io

I’ve been building automation systems… but clients actually buy emotional relief 😅 Nobody wakes up thinking: “Wow I really need an AI workflow.” They think: - “Why are leads slipping through?” - “Why is my team slow to reply?” - “Why does everything feel chaotic?” That changed how I rewrote the offer today. Before: “AI-powered lead automation system” Now: “Never lose a warm lead because your business replied too late.” Same system. Completely different feeling. Also started testing response timing. A lead getting a useful reply in 2 minutes vs 2 hours feels INSANELY different psychologically. The crazy part? Most businesses still operate like it’s 2018 when it comes to speed. Feels like there’s a huge opportunity just in fixing responsiveness.

If AI automation tools like n8n, Make, Zapier, etc. are becoming so easy to learn through YouTube and free resources, then why do people still learning AI engineering or doing such courses? So what matters most? Someone who can build complex workflows vs someone who is doing AL/Ml, Deep learning, NLP etc. Who becomes highly valuable in the AI industry? Would love to hear from people already working in this space.

Both Claude Code and Codex can run on the same project. You just need to know what each one looks for so you don't have to duplicate files or rebuild your setup. This video walks through what to swap, what stays the same, and a quick prompt you can use to convert any Claude Code project so Codex can read it too.