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Spent an hour with @gregisenberg on the agent economy.
The thing I keep saying out loud that people don't yet believe: a fleet of agents on the right platform can run a real company. Not a hobby. A real one.
We did 3 live builds on Hyperagent during the pod:
→ A hyperlocal
I sat down with Howie Liu, the CEO of Airtable ($500M+ revenue, 1 billion in the bank) and asked him: is there really 1 trillion up for grabs in AI agents?
His answer: it's way more than that. It's the entire GDP of white collar labor. Tens of trillions.
Here's what stood out:
This.
We're seeing it in early Hyperagent usage. And it's not just SWEs. There are frontier operators in every sector doing in a day with agents what a team of humans would spend weeks on.
→ Entire OOH campaign for a YC company. Brand study, 18 target accounts, 8 real
Judging by my tl there is a growing gap in understanding of AI capability.
The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is
If you're rethinking your agent setup after the Claude subscription changes — we're opening @Hyperagent today.
First 1,000 signups get $1,000 in bonus inference credits + a 2.5x cost subsidy on frontier models including Opus 4.6 (up to $15K/mo) for a year.
If OpenClaw is Linux,
As agents become more capable of long running work, we need more ambitious and realistic benchmarks. Congrats @adarsh_exe@BrendanFoody on releasing APEX-SWE!
Traditional coding benchmarks do not reflect how software is actually built and maintained.
That's why we built a new benchmark, APEX-SWE, in partnership with @cognition. It measures whether AI models can perform complex, real-world software engineering work to ship systems
