AI making developers faster doesn’t automatically mean companies will need fewer developers.
If a team becomes 5x or 10x more productive, the smarter move is not always “fire most of them and stay where we are.”
The smarter move is often:
build more
ship faster
try more ideas
catch up to competitors
or get ahead of them
Software demand is not fixed.
There are still too many ideas, features, bugs, internal tools, workflows, and products waiting to be built.
AI may reduce some roles, but for good developers, it is also a multiplier.
The job market being bad right now doesn’t mean AI has already replaced everyone.
A lot of it is also overhiring, the economy, and companies cutting costs after the 2020–2022 boom.
AI has changed what progress feels like when building.
Earlier, even small things felt like a win.
Writing a feature, fixing some UI, or getting a piece of logic to finally work.
Now, since AI can help with a lot of the coding part, the satisfaction has shifted.
It is not just about whether the code works anymore.
It feels good only when the thing I imagined actually starts looking and working the way I had in mind.
genuinely curious how this is working out so far for you guys
like what’s the success rate of agents actually fixing issues vs introducing new ones somewhere else in the process
People freaking out over my AI spend. What nobody sees: Part of what excites me so much about working on OpenClaw is that I'm trying to answer the question:
How would we build software in the future if tokens don't matter?
We constant run ~100 codex in the cloud, reviewing every PR, every issue. If a fix on main lands, @clawsweeper will eventually find that 6 month old issue and close it with an exact reference.
We run codex on every commit to review for security issues (as it's far too easy to miss).
We run codex to de-duplicate issues and find clusters and send reports for the most pressing issues.
We have agents that can recreate complex setups, spin up ephemeral https://t.co/Q1NRXLemEy machines, log into e.g. Telegram, make a video and post before/after fix on the PR.
There's codex that watch new issues and - if it fits our documented vision well, automatically create a PR of it. (that then another codex reviews)
We have codex running that scans comments for spam and blocks people.
We have codex instances running that verify performance benchmarks and report regressions into Discord.
We have agents that listen on our meetings and proactively start work, e.g. create PRs when we discuss new features while we discuss them.
We build https://t.co/bmA1XnoB7P to split all our projects into functional units to review and find bugs and regresssions.
We do the same split for security with Vercel's deepsec and Codex Security to find regressions and vulnerabilities.
All that automation allows us to run this project extremely lean.
@steipete genuinely curious how this is working out so far for you guys
like what’s the success rate of agents actually fixing issues vs introducing new ones somewhere else in the process
Introducing Zero
The programming language for agents.
I wanted a systems language that was faster, smaller, and easier for agents to use and repair.
Explicit capabilities. JSON diagnostics. Typed safe fixes.
Made for agents on day zero.
@ctatedev why build an entirely new language for agents instead of improving tooling around existing languages?
feels like the ecosystem and adoption problem would be way harder than the agent problem itself
people keep saying “AI prevents u from learning”
i mean bro do u even read, process and understand what u r getting from it?
if you just copy paste everything, that’s on you
AI doesn’t stop you from learning. your laziness does.
interesting idea tbh
a token tax this small probably wouldn’t hurt the big labs much, but it would force them to care more about efficiency instead of brute forcing everything with more compute
the hard part is making sure it doesn’t kill smaller startups while the giants barely notice it
We should federally tax Tokens at the Provider level.
Not a lot. Less than 50c per million tokens.
It will accomplish 4 things (at least )
1. It will push the big AI players to optimize tokenization, caching , routing and localization
Which will
2. Reduce energy usage. Saving them in energy costs more than what they paid in tax and reducing strain created by the growth in energy consumption
Which will
3. Generate maybe 10 billion dollars a year to start, but over the next ten years could grow 30x to 100x
Which will
4. Create a source of funding to pay down the federal debt or deploy, in response to the things AI brings that we don’t expect or don’t like
At some point the models will pass it on to customers. Of course. That’s ok. Customers will have the ability to choose between providers. Or to do everything using open source models locally.
Thoughts ?
interesting idea tbh
a token tax this small probably wouldn’t hurt the big labs much, but it would force them to care more about efficiency instead of brute forcing everything with more compute
the hard part is making sure it doesn’t kill smaller startups while the giants barely notice it
AI-generated code can manipulate you into thinking it is correct just because it looks clean.
That is why developers need a rough idea of what the code should do before generating it.
If you cannot review the logic, you are not speeding up development.