Matt thinks out loud here about technology, mostly how teams decide what to build, fix and protect.

The first series argues that security gets better fastest when the teams that each hold part of the answer share it earlier. Part 2 says most critical findings aren't: seven questions tell you which, and the answers live with other teams. Clay first, chisel later is about roughing out the whole thing before polishing the parts.

Every piece says how much AI helped, and the site changes in the open. The discussion happens on LinkedIn.

Dad writes about computers at big companies.

His big idea: when Mom and Dad yell about the messy room and leave, it doesn't get clean. It works better when everyone agrees on the goal and helps each other. Grown-up teams are the same.

He uses a robot helper to write, and he tells you how much. There's a comic just for you.

Matt writes about how people at big companies work together on technology.

His main point is simple: problems get solved faster when the people who each know a piece of the answer talk early, instead of passing notes.

He's honest about using AI to help him write, and he keeps a record of every change. Your own version is coming, and he's writing that one himself.

AI is speeding up how fast software problems are found and exploited. The biggest lever isn't another tool. It's how much the teams that hold the answers share, and how early: security, the business, and the teams that build and run the systems.

Three paths, from least change to most: get smarter in your own space, give security a one-way mirror, or put doors in the walls. Decide how far you'll go first. Everything else is optimization within that choice.

Look, we know you're allergic to tech and operations. You're busy. Rates won't move themselves, and that pivot table isn't going to admire itself.

So here it is, in one cell: the scanners flag tens of thousands of problems as critical. Most aren't. The few that are get fixed faster when the people who actually understand your systems (yes, the tech people you roll your eyes at) share what they know early.

You'll love this part: it all runs on spreadsheets. Your spreadsheets. Turns out you've been holding the common thread the whole time. Try not to let it go to your head.

If you're the one closing findings: the scan says a flaw might exist. It rarely knows whether it's already fixed, whether anyone can reach it, or what changing the system would risk. That context lives with other teams.

Series 1 maps what a good decision needs and who holds it. Series 2 covers how far to open the walls, and where agents fit.

The newest piece, Seven questions, is the practical one: qualify with prejudice, get the whole picture early, and be picky, not careless.

One person writing honestly, in plain words, about how work gets done in technology, mostly why teams that keep information to themselves solve problems more slowly.

No jargon needed. Each piece says how much AI helped write it, some come in versions for kids and parents, and there's a public list of every change.