Just spoke to the Head of AI at a huge company. The #1 thing they're struggling with is... what do I do with the AI laggards at our company? Like most companies, they’ve found that a Super Pareto Principle is true within their org. 10% of their employees are responsible for 90% of the uplift in productivity/token usage from software engineering to non-technical knowledge work. They’ve spent a lot of time & resources on AI enablement from LLM foundations to function-specific trainings and skill building. And yet, the power law of productivity increases hasn’t budged. So now they’re left with a few sobering thoughts and hard questions: 1) 90% of people are overpaid and 10% are underpaid 2) We’d be better off allocating tokens proportionally to the power law, but how do we do that without killing culture? 3) Significant layoffs are likely warranted and wouldn’t impact overall output, but cultural backlash is a big concern? 4) How do we hire more power law people as a non technology company? 5) Is all of our efforts on training and enablement ACTUALLY worth it? 6) How do we not experience a brain drain where the top 10% all leave because they want to be surrounded by other AI-native 10x’ers?

AI means a big team can’t possibly keep track of all the daily changes. So, I suspect the ideal team size for 2027 is 1-2 people. Any more than that and people can't keep up with the changes, so they don't understand the system they're building.

Can I ask a dumb question? 😭 Why do some npm packages start with "@" while others don't? What does it actually mean?

Using Claude Code in the terminal is mostly an ego thing. The desktop app looks better and does the job. Prove me wrong. What does the CLI do that the app can’t?

these pickles are bland dill issue

literal hardest role to hire for rn and every ai startup wants someone > chronically online (knows trends) > has taste & can create (new media) > understands ai & technical > can execute with quality (operator) such a small niche of folks who can do this

Software engineering was supposed to go away when low-code/no-code hit the shelves. It was supposed to go away when WYSIWYG IDEs hit the shelves. And it didn't. And now, with AI coding agents, it's still the same. It lowers the barrier to entry. You can get started faster than ever. You can even build small personal projects and productivity tools with little or no SWE experience. But as soon as you want to build software in earnest, you need to know the fundamentals: Security, maintainability, scale, reliability, etc. They do not go away regardless of how advanced the software-building technology becomes.