Topic
AI strategy
Not whether a company has an AI plan — most now do, in the loose sense of licences and a policy email — but whether it would survive a bad week. These pieces are about the difference between a plan that exists and one that changes what the company does: what to require before relying on an app someone built, what a real AI plan actually contains, and the questions worth asking before you buy or believe anything sold to you as AI strategy.
Oct 28, 2026NoteFor companiesDraft
Check the data before you sell the map
I pulled three public data portals for my own region into one AI-coding session to find products local businesses would pay for. Joining the data was the easy part. The checks afterwards killed two of the best-sounding ideas, moved a third, and showed that "nobody does this here" was wrong. The four checks to run before you build anything on someone else's data.
Oct 28, 2026NoteFor companiesDraft
The report that lists its own gaps
I built a property due-diligence report from public data: one address in, nine sections out, about forty queries in thirty seconds. I picked the test site blind, and it turned out to have a live application for more than 1,300 homes. The report held up. The most useful page was the list of eight things it couldn't answer. What that taught me about any report an AI tool helps you produce.
Oct 21, 2026NoteFor companiesDraft
My website said "security" sixty times and "revenue" eight. Owners buy the other way round.
A services site written by a technical person sells protection. An owner buys gains first: hours back, costs down, work won. I counted the outcome words on my own owner-facing pages and found the imbalance. What I changed, and how to run the same count on any AI proposal put in front of you.
Oct 21, 2026NoteFor companiesDraft
"Are we aiming too high?" The sentences were fine. The shelf was wrong.
When I asked whether my own site sounded too expert for the owners it's for, the instinct was to rewrite. The plain-English pass had already been done. The problem was which subjects dominated, which pieces were labelled for everyone, and which expert words had leaked onto the introductory pages. A five-step audit to run before touching a sentence.
Oct 14, 2026NoteFor companiesDraft
The page that lets a software project end
Every "could it also" raised during a build needs a home, or the phase never closes. One page holds everything raised but not in scope, in ordered waves with the ordering rules written at the top, and every item on it is a change request.
Oct 9, 2026Start hereFor both
I've become the AI person. Now what?
You rewrote a few emails with ChatGPT, showed a colleague, and now the boss wants to know what the company should do about AI. You did not sign up for this, and you are the right person anyway. What the boss is really asking, the three levels of using AI, and your first thirty days.
Oct 9, 2026Start hereFor companies
Is your business ready for AI?
Most small businesses are not, and not because they are behind: it is nobody's job. What ready actually means in plain English, whether you even need an IT team, the three levels of "using AI", and the twelve questions to test yourself against a bad week.
Oct 9, 2026Start hereFor companies
You're the fractional exec. Your client just asked about AI.
Fractional CFOs, COOs, CEOs and CIOs are getting the AI question from every client at once, and most did not sign up to be the AI expert. You do not have to be. What your clients are actually asking, the answer you can give this week, and how to bring in someone who has done it, on your terms.
Oct 9, 2026PlaybookFor companies
What an AI plan actually contains
Five short things with owners, not a fifty-page strategy. The plan for a company of ten to two hundred people, what each part is, how long it takes, and the order to do them in.
Oct 7, 2026NoteFor companiesDraft
Five companies that got AI wrong, with the receipts
Real companies, their own words, and the one decision each of them skipped. A coding agent that deleted production and its backups, an email bot that confirmed a typo, 45 jobs cut and reinstated, a chatbot a Canadian tribunal said was the company, and $31,150 in costs for invented case law.
Oct 7, 2026NoteFor companiesDraft
I nearly built an AI assistant that reports your staff to you
An AI chat for employers that tells management when someone pastes client data in or goes looking at things they shouldn't. I did the homework before building it. The big vendors already sell it, it watches the wrong place, and the reporting is the part lawyers push back on. What a small firm should want instead.
Oct 3, 2026PlaybookFor companies
Before you hire someone to build with AI
The questions to ask an AI-assisted developer or agency before work starts, what a good answer sounds like, and the red flags. About the people building your software, not the AI product you might buy.
Oct 3, 2026PlaybookFor companies
Before your staff build with AI
The fifteen-minute conversation to have before an employee builds something with an AI coding tool: nine questions for the manager, the matching line the builder checks first, and three tiers so saying yes stays cheap.
Sep 24, 2026NoteFor companies
Canada's privacy finding on ChatGPT isn't about your business. These rules are.
The May 2026 finding against OpenAI is about how OpenAI trained its models. The rules for a business whose staff use AI were published by the same regulators in 2023, and most small firms have never read them. What they say, in plain English, and how they fit on one page.
Sep 11, 2026NoteFor companies
AI writes instant legacy code
Code written with AI is being thrown away or rewritten within weeks at twice the old rate, and the share of code being refactored is falling. The draft is faster. Owning it is not.
Sep 11, 2026NoteFor companies
Fast food architecture
AI is a very good drafter and a poor architect. Treating its output as finished engineering is like living on fast food: it works today and costs you later. The fix is a place the reasoning lives that the model can read back.
Sep 11, 2026NoteFor companies
The build is the cheap part
A tool built in 48 hours feels free until the first API change. The initial build was always the small share of the cost of owning software, and AI just made that share smaller.
Sep 11, 2026NoteFor companies
The tool nobody in IT knows about
Shadow IT used to be a spreadsheet. Now it is a working app that runs part of the business, built by one person with an AI tool, and that person is the only one who can change it.
Sep 5, 2026NoteFor companies
A chatbot for everyone is not an AI strategy
It is the most common AI decision a company makes, and the most common place it stops. What the licence buys, what it does not, and the four things it quietly leaves undone.
Sep 5, 2026NoteFor companies
Seven questions to ask anyone selling you AI
The vendor has a demo. You need answers. Seven questions that separate an AI feature from an AI liability, and what a good answer sounds like.
Sep 5, 2026NoteFor companies
The app is the visible part
Companies that build or buy an AI feature usually stop at the feature. Three invisible parts decide whether it is an asset or a liability, and none of them is optional.
Sep 5, 2026NoteFor companies
The coding standard is a file the tool reads
Three people building with AI produce three different codebases unless the standard lives somewhere the tool reads it every time. Not a wiki page. A file in the repo.
Sep 5, 2026NoteFor companies
The employee who can now build apps
Someone in your company who is not an engineer has built something the business now relies on. It is an opportunity and the biggest new risk in most small firms. What to require before you rely on it.
Sep 5, 2026NoteFor companies
What a company keeps when the coder leaves
Git keeps the code. It does not keep the reasoning, the gotcha that cost a day, or why the last approach was abandoned. That is a different kind of backup, and most companies do not have it.
Sep 5, 2026NoteFor companies
Your staff already have an AI plan. You just have not read it.
In most companies without a policy, AI is already in daily use on whatever data is to hand. That is not a discipline problem. It is the plan you get by not writing one.
Sep 5, 2026PlaybookFor companies
An AI policy in one page
A template for the rules part of an AI plan, written to be followed rather than filed. Fill in the named tools and the named person and it is done.
Sep 5, 2026PlaybookFor both
The infrastructure around the app
A homework checklist for anyone building an application a business will rely on, and for the leader deciding whether to let them. The app is the easy part; this is everything else.
Sep 5, 2026PlaybookFor AI-coders
Standards and continuity for a small AI-coding team
The repo files that make AI-written code consistent, how a shared vault survives more than one author, the automated handoff that catches unfinished work, and the drill that proves any of it actually works.