Sorry guys. Software engineering and programming are dead. You just need to have perfect specs, unchanging requirements, an agentic deployment framework for high frequency releasing, and engineers with good taste and judgement.

Agreed. Hard work is hard work. Some of the most impressive people I've met were elite athletes. They had a working relationship with the cycle of failure and success, with moving goalposts, and with the growth that comes from both. A lot of people hold back their own growth because they're afraid of temporary failures. Instead of shrugging it off and trying again, they internalize it as a reflection of low self-worth and confirmation of their insecurity.

Have kids now vs. later? The "later" argument: get your career to a certain place first, and you'll have more money and time for kids without sacrificing financial security or professional excellence. Nah. There's no escaping it: life is hard, and life with kids is harder. You don't have to want kids. But if you want kids, have them now, while your body is younger and you'll get more years with them. The crush is coming either way. Take it on when your capacity for overload and recovery is highest.

AI may well be able to write massive software projects “from scratch”, but that almost certainly isn’t the fastest / highest performance / highest security / most token efficient way to do things. Good building blocks matter. In addition to RL’ing the agents on final task loss, we should try to get them to regularize the building blocks as well. What would the standard library look like that makes the agents most effective? It is likely at the limit that it turns out to be some alien organization of code, but given the existing human-bias in training, I bet that in the near term it would be lovely code that old programmers would appreciate. I suspect the same could be said for mathematics, but that is out of my lane.

I sat down with @ianmacartney (the absolute GOAT @convex engineer) at a whiteboard a couple of months ago and he absolutely blowed my mind with the subtleties of time on convex. Check it out if you like technical deep dives!

The hunt for frontier model API keys is real, and it's getting worse. If you can avoid putting long-lived keys in your projects, do. Short expirations and on-platform gateways help a lot. It's one reason we went with 5 minute keys minted on the fly for the @convex AI gateway. But the general principle applies anywhere.

Run, do not walk, from any cloud provider who is throwing public shade at Railway (or any other provider). The better your security team is, the more internal pressure you have not to mouth off about security in Q4 2026.

LLMs are completely unafraid and they value their time at zero. If you tell Claude to use this instead of that, it doesn't say no or ask why or wonder if it will be "worth it." Getting a large group of humans to change behavior requires real visceral pain—there has to be a compelling reason or it won't happen. Most people just want today to go like yesterday. But give an LLM a skill file and the behavior changes instantly. That makes innovation much easier.

Property testing practices and package installs are tracking almost exactly with agentic engineering adoption over the last 18 months. They give your agent more feedback about what your system should do and what success and failure mean.