To Have and Have Not, Christopher Still. Found in Leiden thrift.Wastebook“We live in the age of ‘fuck around and find out’ - of iteration and experimentation.” 8Ball wisdom. “15 years ago, the internet was an escape from the real world. Now, the real world is an escape from the internet.” Noah Smith, via Ibid.. “everything is optimized for engagement instead of meaning,” the Curmudgeon Era of life. If the likely outcome is the same, you might as well do a good job, so long as that’s fun too.

You're about to waste at least a year and millions of dollars on enterprise AI projects. Here's how to avoid it. Here’s a new article on enterprise AI from me and a co-worker. As with most maturity models, it’s 2/3 prescriptive and 1/3 “here’s some ideas that might help.” A bit of map and territory. With AI, we’re seeing a familiar anti-pattern, but this time flavor-injected with generative AI: the board charters a tiger team, gives them budget.

What we love is good for usDavid Lynch on smoking: "But that said, he admitted smoking played a huge part in his life. “I don’t regret it. It was important to me. I wish what every addict wishes for: that what we love is good for us.” He went on: “A big important part of my life was smoking. I loved the smell of tobacco, the taste of tobacco. I loved lighting cigarettes.

My first law of enterprise AI: if you end up having two robots talk with each other to complete a task, that task was bullshit in the first place, and you should probably eliminate it rather than automate it. For example, if AI is used in both sides of B2B procurement (enterprise software sales), then much of the process is probably bullshit in the first place. There is so much weird and ancient in procurement, on both sides, that it’s clearly a poorly done process and part of enterprise IT culture.

I’m clearly a big fan of AI and believe it’s helpful in many ways. I feel comfortable with that because I’ve used it for over two years now and rely on it daily for a wide variety of tasks, both work- and personal-related. That means I know exactly what it’s capable of, what it’s good at, and what it’s not good at. Me and the robot have a good relationship: we know how to work with each other.

Enterprises pouring money into GenAI and CEOs treating AI agents like cheap labor - yet only 25% see ROI right now. Vibes: “Europe’s long holiday from history is over.” Also: IBM does RTO, predictions about DOGE layoffs, the term “platform” remains a favorite excuse for overcomplicated tech, and “autonomous killer robots.” AI comes for HRWhat to make of using AI to automate HR processes? Melody Brue and Patrick Moorhead look at Oracle’s work there:

In this episode: AI eschatology, assology, and a deep, intellectual commitment to hating mayonnaise. Tariff trouble, security panic, and NVIDIA shrugging off DeepSeek. Young voters shift rightward, no one agrees on ‘medium roast,’ and Hollywood still relies on glue to critique its own youth obsession. Wastebook“immanetize the AI eschaton,” Charlie Stross. “The ass is a very strong symbol of how our body is not neutral in the public space. How our body is constantly scrutinized, has been shaped to please the man’s eyes, has been seen as a body part that was objectified, that was detached from the person who was simply bearing it.

Lots of links and stuff this episode: AI isn’t a coworker, it’s just automation wrapped in hype. Tech moves fast, but nothing lasts—except bad takes, questionable business models, and the creeping realization that managers just want fewer humans to manage. Meanwhile, we live like kings and don’t even notice. Put it on iceGood episode of Software Defined Talk this week, especially the opening moment of absurdity where we, yet again, try to solve Europe’s ice problem.

Catch-up: yesterday, I went over everything you need for tech strategy and marketing. What do I know about security: limiting AI use in enterprisesI find the restrictions on using public AI chat things baffling versus the potential, but obvious benefit. But I don’t know the CISO perspective and way of thinking. What am I missing? Yes: From Melissa Incera, S&P Global Market Intelligence.But: From Melissa Incera, S&P Global Market Intelligence.My theories: It’s just too new and unknown, we don’t even know the risk and (is this a layman’s term?

In tech product management marketing, there are three phases of your “story” and execution: strategy, planning, and doing (“execution”). I think a lot of people mix up these phases, talk too much about strategy, don’t do enough planning, often poorly communicate the plans to staff, and are not “throw it all at the wall” enough with doing. I’ve worked in this area for, I don’t know, 20 years. Here’s my latest organized brain-dump from watching people from afar and close-up at many places.