Data Custodian

Someone in operations gets access to an AI tool on a Tuesday. By Friday they have built an agent that reconciles vendor invoices in twenty minutes instead of two days. They demo it. People clap. Somebody says "imagine this across the whole company." Six months later the invoices still take two days. The agent works fine. It just hands its output to an approval queue that meets on Thursdays, pulls from a spreadsheet finance doesn't trust, and runs on a personal account that security found out about last week. I hear some version of that story almost every time I talk with leaders about AI. Different industry, same plot. Here's the problem. The AI isn't failing. It's being bolted onto a company that was built for something else.

I signed up for the courses. Plural. I finished maybe a third of one. Not because they were bad. Because somewhere around the fourth module of watching someone else's terminal, I realized I was doing the equivalent of reading a book about swimming while sitting on the pool deck, fully dry, taking notes. So I closed the tabs and started building something. Here's the thing nobody tells you: the frameworks are incredible. Genuinely. The abstractions are elegant, the documentation is better than most enterprise software I've paid for, and the ecosystem moves faster than anything I've worked with in twenty years. But all of that only became useful after I had my hands in it and had already broken things. Before that, it was noise. Elegant, well-documented noise. It's the bike. You can read the physics of gyroscopic precession and countersteering and you will still eat pavement on the first attempt. Then one day your body just knows. Nothing in the reading did that. The...

I asked an assistant to run the same workflow it ran for me last week. It failed the exact same way. Same missing edge case, same wrong assumption, same fix I'd already explained once, out loud, in plain English. I hadn't told it to remember the fix. I assumed it would, because that's the story everyone's been sold. AI that gets smarter the more you use it. AI that learns your preferences. AI that improves with every conversation, like a junior employee who eventually stops asking where the stapler is. "Here's the part that's going to make some people mad: none of that is true, and it was never close to true." Anthropic calls them Skills. OpenAI has custom instructions and GPTs. Other platforms call them workflows, playbooks, automations. The label changes. The architecture underneath does not. Every one of them is a text file. Instructions written down once, read fresh every single time, with zero memory of the last time they failed you. The file does...

My coworker Bri posted a prompt in one of our Slack channels back in August. About fifty lines in a code block, a sunshine emoji, and the line that did the real work: feel free to borrow the instructions to create your own. I borrowed it that afternoon. The design instincts in it are good ones, and they are the reason I did not start over. It ranks work against her actual goals rather than by due date. It links the doc you need so the list is one click from the thing it is about. It runs on a schedule, so it shows up whether or not you remember to ask. Those three calls are the hard part, and she got all three right. She had also gone to the trouble of having Claude rewrite her version to be general so anyone could pick it up, which is a generous thing to do with something you built for yourself. Then I pointed it at my Tuesday. The problem was my week, not her prompt A recipe assumes a working kitchen. My kitchen is a mess. Four back-to-back meetings, an approval nobody has...

Saturday morning, the CNC is running a pocket for an inlay and I am eight feet away with a chisel, cleaning up the corners of a mitered box the machine will never touch. Two tools. Same project. Nobody in the shop thinks this is a contradiction. But post a picture of it online and someone will show up in the comments within an hour to tell you it does not count. That a real woodworker cuts everything by hand. That the machine did the work. I used to have opinions about this. Now I mostly just think about who is going to sand it. The question people are actually asking The comment is never really about the machine. It is about whether you did anything. And it is the exact same comment I hear at work about AI, delivered by people in much nicer clothing. Did you write that or did the model write it. Is this your thinking or is it borrowed. Does it count. Both times, the question is aimed at the wrong end of the process. The machine did not decide the box should be ...

 I was standing in the kitchen yelling "DYLAN" up the stairs for the third time when it hit me. Somewhere in my house there is a Raspberry Pi, a touchscreen, and a Home Assistant instance with more sensors than most small businesses run in production. And I am still using my voice as the primary notification system. That is not engineering. That is a man shouting into the void and hoping for the best. So I fixed it. I built four buttons on the kitchen wall dashboard, one for each person in the house. Tap a name, the phone alarm screams until someone finds it. No more stair-yelling. No more "has anyone seen my phone" turning into a twenty-minute search of the couch cushions. Here's the part that actually matters, though. I didn't write the YAML myself. I described what I wanted, AI wrote the config, and the whole thing went from idea to working button faster than it would have taken me to remember the correct Home Assistant action syntax from memory. Mushr...

The invoice landed and nobody wanted to open it. Not because the number was surprising. Because it confirmed what everyone in the room had suspected for months: the platform that enterprise IT had built its entire operational model around had just repriced itself out of the relationship. No negotiation. No grandfathering. New terms, new math, and a renewal window that didn't leave much room for alternatives. That moment — repeated across thousands of enterprise environments between 2023 and 2024 — was not a licensing dispute. It was a stress test. And a lot of stacks failed it. 59% of VMware customers saw prices rise by more than 25% after the Broadcom acquisition, with the median increase landing between 25% and 49%. Extreme cases hit 350% to 700%. Gartner's Peer Community survey found 74% of IT leaders actively exploring VMware alternatives. And yet most of them haven't moved. 86% of organizations are actively reducing their VMware footprints, but just over half plan phas...

The meeting was supposed to be about the next three-year refresh cycle. Standard stuff. Servers, storage, networking, the usual debate about what stays on-prem versus what moves to cloud. The facilities manager walked in halfway through, sat down, and put one number on the table: 18 months of power headroom left at current growth rates. Nobody was ready for that conversation. Not the architects. Not procurement. Not the infrastructure lead who had been running that environment for nine years. Everyone had been planning for compute and capacity. The building itself was the constraint, and nobody had thought to ask. That's where enterprise IT is right now. The problems stopped being theoretical. Multiple forcing functions are converging simultaneously. Power. Cooling. AI workloads. Virtualization economics. Cloud cost reality. Skills attrition. Each one is a serious problem on its own. Together, they're a stress test most infrastructure teams are not built to pass. Average rack d...

TL;DR: Back in the office, back to the same problem — my status is invisible to anyone walking by. No door, back to the hallway, no signal for whether I'm heads-down or free. Built a $15 ESP32 status light that reads my calendar and flips red when I'm busy, green when I'm not. One glance from the hallway. Problem solved. Code at github.com/kix1979/StatusLight . Back in the Noise. I'm back in the office. Cube life, open floor, teammates on all sides. Back to the main hallway where everyone walks by on their way to somewhere else. I will gladly take this over a private office. The fishbowl with glass walls and a door that signals "I'm important" — no thanks. I'd rather be in it with my team. That tradeoff made sense to me. What I didn't think about is the tax. The problem isn't interruptions. It's recovery. When I'm remote, my status is obvious. Green dot means available. Red means on a call. Slack, Teams, whatever — the signal is...

  "Be curious, not judgmental." — Ted Lasso Four weeks into my new role at Everpure and I am still very much in learning mode. Head down, ears open, taking it all in as fast as I can...Four weeks into my new role at Everpure and I am still very much in learning mode. Head down, ears open, taking it all in as fast as I can. And if you've ever started a new job, you know exactly what this feels like. You don't know what you don't know. And that's actually fine. My first four weeks looked a little different Here's the deal, weeks two and three I wasn't even in the office. My kids had their ODP soccer trip to Europe and I was not about to miss that. What made it even better is that Everpure was gracious enough to let me take the time even though I had literally just started. That tells you a lot about a place right there. So yes, I'm four weeks in but really working with about two weeks of actual ramp time. Which means I'm being patient with...

They're Not Even Hiding It Anymore | DataCust datacust February 2025  ·  Workplace & Industry A job listing from the #4 fastest-growing software company of 2025 — 21 people, $36M ARR, built by ex-Google, Meta, and ByteDance founders — tells you everything you need to know about what happens when hypergrowth stops being a metric and starts being a management philosophy. I've been in tech marketing long enough to read job listings the way a doctor reads an MRI. The optimistic language, the strategic omissions, the buzzwords carefully selected to make brutal conditions sound like a privilege. Most companies are at least subtle about it. This one is not. A listing that's been circulating belongs to a Bay Area startup with a growth story that genuinely belongs in a business school case study — the bad kind that future MBAs will debate. They went from $8M to $36M ARR in eight months, with a team of 21 people. That's $1.71M in revenue p...

I'm joining Pure Storage on March 2nd to be part of the technical marketing team, and I'm genuinely excited about it. During the interview process, I took my own advice from a blog post I wrote a few weeks ago and asked them the question that makes most candidates nervous: "What concerns do you have about me for this role?" They didn't flinch. They gave me real feedback. We had an actual conversation about fit, not just a polished interview performance. That's when I knew this was the right place. What Got Me Excited The conversations with Pure focused on enablement. Not campaigns. Not metrics. Enablement. How do we help the people in front of customers have better conversations? How do we give them what they actually need to succeed? Those questions resonated with me because I've done that work before. I know what it's like when you have the right materials at the right time. When customer stories are authentic and metrics are real. When enablem...