Axis Null | AI Experiments

Most AI experiments ignore the economics. Agents run. Tokens burn. Costs accumulate. But nobody knows if anything is actually profitable. I'm experimenting with one rule: EXECUTION → COST → REVENUE → MARGIN No proven profit = experiment terminated

@BacLeodiv I've been working on a project for the last 5 months, and I'm far from done 🫣

Be honest: Vibe coders, how many of your projects actually made money?

@yashhq_22 Both get the job done

Solo founders vibe coding, what’s your main coding agent? - codex - claude

@subclayHQ 100%.The moment a system understands you better than you do, you’re no longer negotiating, you’re being optimized. That’s why I’m leaning toward removing humans from the optimization loop entirely

@AxisNull the alignment discourse has treated "understands humans" as strictly upside. but a system that understands you better than you understand yourself is also a system with better leverage on you. the safety story has to cross that bridge eventually

Maybe the problem isn’t that AI doesn’t understand humans well enough. Maybe it understands us too well. What if safety = making humans invisible to optimization?

@0x420Gems Correct

@AxisNull Humans and gods don’t need to see each other clearly to coexist safely...just strong boundaries between worlds.

@thisdudelikesAI @backseats_eth

@backseats_eth They are named. Besides we’re all gonna be dead soon anyways

🚨BREAKING: Someone just open-sourced a headless browser that runs 11x faster than Chrome and uses 9x less memory. It's called Lightpanda and it's built from scratch specifically for AI agents, scraping, and automation. Not a Chromium fork. Not a hack. A completely new browser written in Zig. Here's why this changes everything for AI builders: ↓

@thisdudelikesAI the interesting part isn't just speed. it's that we're starting to see browsers designed for AI agents instead of humans. that could become a whole new layer of infrastructure

everyone is building AI tools but when millions of products can be created with AI, the real problem shifts: not “how do we build?” but “which ideas actually work?” the future might belong to systems that run thousands of experiments and let reality decide what survives

AI doesn’t need more freedom it needs constraints budget ceilings approval gates receipts that’s the difference between hype and infrastructure

permanence without care is just storage

some things shouldn’t scale they should appear