I don’t think we’ve reached AGI but what we have is functionally indistinguishable from AGI.
Because we have a relentless programmer that doesn’t get bored or tired.
So any problem that can be casted as a coding problem is virtually solved.
Good post on how to think about process redesign in an enterprise with AI Agents.
Unfortunately for most workflows, there’s no “easy” button. The best way to get real efficiency gains is you have to actually reengineer the process to take advantage of what agents are actually good at and can do differently and faster than people.
One of the challenges of course is that the most important workflows actually space many functions at once, so someone needs to be able to go in and retool how work happens.
“Nobody in that chain is empowered to walk into finance, for example, and say that their 14 step process should actually only be 5 steps. So nobody does it. Instead, you 'apply AI' on what you currently have, and you end up with faster sh*t.”
This is the road ahead for AI diffusion in enterprises. This also presents the clear opportunity for companies - both at the applied AI layer (regardless of the article’s title) and teams or companies that can go and implement transformation into the enterprises. And all roads lead to FDEs one way or another.
good engineers used to catch vague specs at the keyboard. They'd push back, ask about existing customers, surface the weird cases. Agents don't do that. They fill in the gaps and build. So we should spend more time refining product slices before passing them on.
One real issue with Chinese independence of flop-based compute is that their open source contributions will shift to a stack we can’t / won’t use in the US and that will hurt because our current AI research / infra is currently very closed.
Prediction: In the AI age, taste will become even more important. When anyone can make anything, the big differentiator is what you choose to make.
https://t.co/3GQUlfH58t