The biggest flex is having fun at work. If you’re genuinely excited by the challenge and want the thing you’re building to exist, then work starts feeling suspiciously like play.
@thenanyu@WillManidis I feel like it’s easier for me to learn what I want in a topic but it’s also just as easy to be lazy in that learning. Similar to what was probably the same argument when Google came about vs going to the library
Everyone building AI agents is focusing on building the prefrontal cortex. Planning. Reasoning. Multi-step chains. There's value here. CEO-stuff.
But also, a reframe: there is value in building the cerebellum. It's offloading boring tasks into reflex so the complex thought can focus.
Your mortgage gets paid by a standing order, not a committee. The things that are not fun, not interesting, but have to be done? Done. Most agent frameworks will fail because they treat all cognition as high cognition.
The winners will nail the boring stuff first.
Elon Musk on why the Model S and Model X succeeded:
“Those cars were designed with love. Every part of it, inside and outside, even things people couldn’t see - we put there because we love the product”
“It’s at the heart of any great product. If the people making it genuinely love that product… it’s not a spreadsheet thing. You do things to make the product amazing because you love it
Even if people don’t see all of those things, they feel a lot of those things. And that’s what translates to people wanting the product”
YC teaches you that distribution beats cleverness. AI is making that harsher, not softer. The cost to build is collapsing, which means the premium moves to taste, trust, and knowing which problem is worth years of your life.
Breaking News: Tim Cook is stepping down as Apple’s chief executive and will be replaced by John Ternus, the head of hardware engineering. https://t.co/roDQdKL1cz
Agents are going to use software 100X more than people will in the future. As a result, enterprise platforms will become headless and be able to work with any agent on or off platform. If you don’t do that you’re DOA.
What some have missed is that this creates vastly more use-cases for these platforms than even existed pre-AI. This isn’t zero sum. Software value props have traditionally been capped at the number of users you have in a company. Agents have no upper limit.
We’re going to run agents to process data at a scale humans never could, they’re going to be running 24/7 in parallel doing work for us, and they can integrate workflows across systems to generate all new value propositions.
Once you embrace this approach, it becomes obvious how much more upside there is.