If You Had to Change What You Charge For, Could You?
An Ode to (Choosing to Be) Busy
Working hours halved, and the complaint never moved. Busyness was doing another job.
TL;DR: Everyone is still slammed, though we work far fewer hours than our great-great-grandparents, and AI now turns out a first draft in minutes. Busyness is a choice, and a rewarded one: a full calendar makes its owner look scarce and in demand, no matter what got finished. The hours AI saves go straight back into other work, plus new work nobody owns. The exchange rate is cultural: Americans reward the overloaded week, Italians mark it down. My own model of a fully loaded leader’s week leaves two days open. Check next week against your prioritized list and what an agent could do; empty one recurring block.
Continue reading “An Ode to (Choosing to Be) Busy”Building Got Cheap. Waiting Never Went on Sale.
Your customers are rebuilding your product to find out what replacing you would cost. They’re measuring the part of your business that runs on a calendar.
TL;DR: Your customers can now rebuild enough of your product to see what replacing you would cost, then throw the result away. What they cannot reproduce is the part of your business that runs on a calendar. A SOC 2 window has to actually pass; a reference account needs a year. The buildable list keeps growing, and the waiting list does not move. And if an exit is in your future, your acquirer prices you on a wait that outlives your own horizon. Count it in months, on a vendor before you count yourself.
Continue reading “Building Got Cheap. Waiting Never Went on Sale.”Everyone Bought the Computers. Six Sectors Got the Gains. Will AI Be Different?
The computer revolution was in the 1990s. The AI transformation is playing out now, and hardly anyone has kept evidence showing which side they are on.
TL;DR: Your board will ask what the AI spending bought, and most companies can no longer answer, because nobody measured the work the deployments were about to change. The lag in returns is real, and it sorts the buyers from the beneficiaries. Six sectors out of sixty took 99% of the 1990s gain, and the heaviest spenders missed it. You cannot locate yourself in a distribution without a “before”, and almost nobody took one. Engineering and support kept timestamps, so those baselines can still be recovered.
Continue reading “Everyone Bought the Computers. Six Sectors Got the Gains. Will AI Be Different?”The Oldest Skill in Your AI Budget
Briefing a person and briefing an agent are the same act. Most people were never taught to do either, and the second one shows up in minutes.
TL;DR: Mid-market companies now put more investment into AI than into anything else, and most organizations credit it with under 5% of EBIT. What sits between the spend and the result is an ordinary management skill: stating the outcome, supplying the context, defining what done looks like. Only one in three workers has received any employer-provided AI training in the past six months. The existing training covers prompting and stops where the work gets useful. Nobody in your company has read anybody else’s prompt, so nothing compounds. Ask three people for the prompt each used on one task.
Continue reading “The Oldest Skill in Your AI Budget”Authority Delegates. Accountability Doesn’t.
Hand work to a person, and part of the risk goes with them. Hand it to an agent, and none of it does. The fix everyone reaches for targets the wrong variable.
TL;DR: A human delegate absorbs part of your risk because they have assets, a career, and legal standing of their own on the line. An agent has none of that, so authorizing one concentrates your exposure at the moment it feels like you are sharing it. Liability attaches regardless of how closely anyone was watching the work. People correct AI errors less when correcting costs effort, and money does not help. Skipping every approval prompt is itself the decision, taken once, by one person. Write down what it can reach and what it could destroy before you authorize the next one.
Continue reading “Authority Delegates. Accountability Doesn’t.”Directionally Correct, Specifically Utterly Wrong
The errors in a generated research report are not spread evenly. They cluster where the decision is, and the rule you already use to catch them is aimed at the wrong variable.
TL;DR: A generated research report is right only if every link in it holds, so accuracy falls away as the steps pile up. In one benchmark’s public filings, the same models score 83% on answering what a document says and 35% on answering what follows from it. Verifying the recent and the obscure misses it; decisions rest on public material. The mode that most resembles diligence fabricates the most citations. Mark every claim retrieved or composed, and re-source only the composed ones before money moves.
Continue reading “Directionally Correct, Specifically Utterly Wrong”An Ode to Electronic Communication (Now That Words Are Free)
Writing got free, reading did not, which makes every message you send a withdrawal from somebody else’s day.
TL;DR: AI made writing free and left reading as expensive as it always was, so every inflated message moves work from the person sending it to the person receiving it. The meter is bolted to the side that got cheaper, and nothing counts what lands on the other. The padding a model adds is billed twice, once in tokens and once in attention. Five daily AI users voting together now spot machine prose 299 times out of 300. Change what you ask the tool for: cut the draft in half every time. Send nothing that came back on the first prompt.
Continue reading “An Ode to Electronic Communication (Now That Words Are Free)”The Diagnostic You Already Ran
How much of your work an agent can take depends on how completely you can specify it, and you are paying for the gap on every single run.
TL;DR: Everyone has the same models, and nobody has the same space around them, which is where the real variable sits. The framework for measuring that gap ran in a management journal back in 2005, written for an entirely different purpose. Two questions decide it: can you codify the work, can you measure the result. What ruled work out then, untransferable team knowledge, is exactly what you can now supply. A colleague is onboarded once; an agent without memory is onboarded every time. Specify once, where the agent reads by default; unclear thinking now runs a meter.
Continue reading “The Diagnostic You Already Ran”An Ode to (Valuable) Meetings
