If agentic AI is a good idea and if it increases productivity we should expect to see some startup blowing everyone out of the water. I think we should be seeing it now if it makes you say ten times more productive. A lot of startups have had a year of agentic AI now to help them beat their competitors.
Imo the wave of top down 'AI mandates' from incumbent companies is a direct result of the competitive pressure, although it probably wont work as well as the execs think it will
that being said even Dario claims a 5-20% speedup from coding agents, 10x productivity only exists in microcosm prototypes, or if someone was so unskilled oneshotting a localhost web app is a 10x for them
Could you give us a few examples?
ant 10xing ARR, oai
harvey legora sierra decagon 11labs glean(ish) base10(infra) modal(infra) gamma mercor(ish) parloa cognition
regulated industries giving these companies 7/8-fig contracts less than 2 years from incorporation
Which gets back to the outsourcing argument: it’s always been cheap to make buggy code. If we were able to solve this, outsourcing would have been ubiquitous. Maybe LLMs change the calculus here too?
But coding assistance tools must themselves be evaluated by what they produce. We won't see significant economic growth through using AI tools to build other AI tools recursively unless the there are companies using these tools to make enough money to justify the whole stack.
I believe there are teams out there producing software that people are willing to pay for faster than they did before. But if we were on the verge of rapid economic growth, I would expect HN commenters to be able to rattle these off by the dozen.
Not sure how long it’ll last though. With the time I spend on reviews I could have done it myself, so if they don’t start learning…
Then? Your job is still to review their code. If they are your coworker, you can not fire them.
(Whether you think OpenClaw is good software is kind of beside the point.)
I don’t think anyone is arguing against code agents being good at prototypes, which is a great feat, but most SWE work is built on maintaining code over time.
It's very much imperfect, but the only consistently agreed upon and useful definition of "value" we have in the West is monetary value, and in that sense, we have at least a few major examples of AI generating value rapidly.
In any case, I agree with the grandparent post about the distinction between being successful and good.