Harley Davey

More AI agent observations below (I keep adding to the list): 1. Hermes agents write to their own memory after every task. Which means starting today versus starting in 6 months is an unfair advantage for you. 2. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now 3. The real reason local models matter for founders: you can ship a product where the AI runs entirely on the customer's device and you never touch their data. Zero privacy concerns. Zero server costs. Zero compliance headaches. That changes which industries you can sell to overnight. Healthcare, legal, finance, all the regulated verticals that won't send data to the cloud just opened up. 4. Every company needs to be rebuilt as a "second brain" before agents can be useful. That means every process, every decision, every piece of institutional knowledge has to exist in a format an agent can read. Most companies have none of this. 5. Agent costs are the new headcount. Won't be crazy for companies to spend 50%+ of their total headcount cost on tokens. 6. Agents are accidentally creating internal competition at companies. The marketing agent and the sales agent are optimizing for different metrics and working against each other without anyone realizing it. It took humans decades to develop cross-functional alignment. Nobody thought about it for agents. 7. The YAML config file is becoming the new org chart. Who reports to who, what permissions they have, what tools they access, all defined in a config file. The company's structure is literally a file you can version control, fork, and deploy. That's new. 8. The first agents that can smell a scam are going to be worth billions. Right now agents will happily wire money to a fake invoice because it matched the format. The trust layer is completely missing. 9. We're about to find out that most "expertise" was actually just memory. Knowing the tax code. Knowing the case law. Knowing which supplier charges what. When an agent holds all of that in context, the expert's value shifts from "I know things" to "I know which things matter." Much smaller group of people. 10. We're all running the same models. The differentiation is in what you feed them. Two founders with the same agent, same model, same tools will get wildly different results based purely on the quality of their knowledge base. Garbage context in, garbage output out. Forever. 11. The most underbuilt category in AI right now: agents for old people. 70 million boomers who need help with medical forms, insurance claims, and appointment scheduling. 12. Agent latency is the new page load speed. If your agent takes 45 seconds to respond, your customer already switched to one that takes 13. Skills files are the new apps. A SKILL.md that tells an agent how to do one thing well is more valuable than a SaaS subscription that does the same thing behind a login screen. 14. AI hardware... how do you create devices that are good businesses that people want? It'll be a $30 dongle you plug into existing dumb devices to give them an agent brain. Smart toaster doesn't need to be built from scratch. It needs a $30 brain attached to a $15 toaster. 15. Your agent can read faster than you can think. The bottleneck in every agent workflow is now the human approval step. We're the slow part. That's a strange thing to sit with. 16. Agents made the 80/20 rule violent. The 20% of work that matters is now the only work humans do. The 80% just disappeared. Entire job descriptions were hiding inside that 80%. 17. The thing I keep coming back to: the best businesses right now are being built by people who are just slightly ahead of their customers. Not 10 years ahead. 6 months ahead. That's the sweet spot. Far enough to lead. Close enough to be understood.

Four years ago I was bidding on $500 Zapier projects on Upwork. Spending connects I could barely afford hoping someone would pick me. Yesterday I was standing on the floor of the New York Stock Exchange. I didn't have a network or a portfolio when I started. All I had was an Upwork profile and a willingness to take work nobody else wanted. Small automations, tedious builds, clients who weren't sure this whole thing even worked. The $500 jobs taught me the basics. How to talk to a business owner without sounding like I was reading a script and how to actually deliver something that worked. Then I started charging more. $1,500 projects. $5,000 projects. And the bigger the project, the more I realized the build was never the hard part. Scoping was, mapping the process before touching a tool was, managing change orders was, hiring the right way was, etc.. And most of all, knowing which problems were worth solving and which ones the client just thought they had. Every jump in price forced me to get better at the part that actually mattered. The thinking, not the building. 80+ companies later, the work is the same. Bigger systems, bigger numbers, same job. Map the operation, find the friction, build the thing that fixes it. If you're early and it feels small, build anyway. The first version of everything is supposed to feel small. And you don't have to be aiming for something like the NYSE floor to make this worth it. Maybe you just want a handful of good clients and a nice salary. That's a great outcome too. I got lucky. I picked automation years ago because I liked it and I was good at it. That's the only reason I chose it. Then AI showed up and it turned out AI is just automation with a brain. The thing I'd already spent years getting good at became the biggest opportunity of the decade. I didn't see that coming. I was just doing the work. You don't get to control that kind of timing. But you do get to control whether you start. And if you're reading this thinking about it, there has never been a better time than right now. If you're already started with a couple of clients under you, keep going. That's the part most people quit right before it compounds.