Ai-Strategy
Always-on AI agents are here. The agent is now the easy part
OpenAI, Microsoft and Meta all launched always-on AI agents in September 2026. For small businesses and the mid-market the agent is now cheap and easy. What decides whether it helps is your records, your rules and who checks the work.
What I look at in a knowledge audit
Before any AI build, I audit a company's knowledge, not its tech stack. The five kinds of mess I look for, what a good audit should hand you at the end, and how to buy one without paying for a report that sits on a shelf.
Why grounded AI agents are cheaper to run
AI is now billed by use, not by seat, and token prices are falling while AI budgets overrun. Why the cost of an agent is really a knowledge problem, where the tokens go, and how grounding and deterministic tools cut the bill.
Your AI does not need a bigger model. It needs to know your business
Model capability is no longer what holds business AI back. What is missing is a structured, current, trustworthy picture of your own business: a knowledge layer. What it is, why it matters now, and where to start.
Company brain products are useful. Most are not a brain yet
Company brain tools are good at finding documents and knowing where knowledge lives. Most stop short of reasoning across your entities, relationships and systems. What they do well, where they stop, and how to buy one without overpaying for a promise.
Email is your most underrated data source
Your systems of record hold what someone remembered to type in. Your email holds what actually happened: the commitments, decisions and exceptions. Why AI projects skip it, how to turn it into trustworthy knowledge, and how to do it lawfully.
Is your software AI-resistant? How to tell if your product survives the next model
The threat to your SaaS isn't another vendor, it's how thin the product was to begin with. Four tests for whether your product is AI-resistant, and why now is the best time to build deep.
If I were a junior developer today, I would use AI to outpace the broken ladder
Junior hiring is paused and everyone is betting on seniors. But the same AI that broke the old apprenticeship hands juniors a faster one, if they build.
Human in the loop is still the best AI model. But only when you design it
Human plus AI beats either alone, but only when the collaboration is designed. The trial where doctors plus GPT-4 gained nothing was a skills gap.
When your best AI model can vanish overnight
In June 2026 a US government directive forced Anthropic to disable its two best models worldwide, days after launch. The lesson outlasts the news: single-vendor AI dependence is now a live continuity risk. How to build optionality and model portability into your stack.
How to build an AI strategy without a CTO
You can build a sound AI strategy without a CTO, and without being technical. What you cannot do is hand the question to whoever is selling you the technology. Here is the method for non-technical founders and SME leaders.
You don't need to build a brewery to drink a pint of beer
The most expensive software decision a founder makes is often the first one: deciding to build. Here is how to choose between building, buying, no-code, and an agency, and how AI changed the answer in 2026.
AI is about to split the job market in two
AI will not just automate jobs. It will rebuild the entire market that matches people to work: personal career agents, employers who hunt talent before roles exist, and a bifurcation that rewards the top tier. Here is what is coming, and where you want to be standing.
If your AI strategy is just ChatGPT, you don't have one
Most leaders now equate AI with large language models. But the frontier models are available to everyone at the same price, and they are often the wrong tool. The real advantage is not the model. It is everything you wrap around it.
From AI that talks to AI that works: the autonomous leap of 2026
2025 gave us AI that talks. 2026 is the year of AI that works: autonomous agents that pursue your goals around the clock. Here is what is happening, starting with an open source project that grew out of nowhere.
What to do when your AI pilot fails
Most AI pilots fail, and most failures are recoverable. Here is how to diagnose what actually went wrong, decide whether to salvage or restart, and why the people who built it are usually the wrong ones to fix it.
The people making the biggest AI decisions understand it the least
Understanding of where AI is heading concentrates at the frontier, while the budgets and decisions sit far from anyone who has built with the tools. Why that gap matters, and how to question the advice you are given.
Stop counting AI use cases. Redesign three value streams instead
Pilot purgatory has a sequel: use-case purgatory. 47 deployed AI assistants is not a strategy. Here's how to pick three value streams and rebuild them end-to-end, the way the operating model needs to change.
Headless is the new mobile-first. Agents are about to become your biggest user
Box, Zapier, Salesforce and Stripe all said the same thing in April: agents will become the dominant users of software. If your product can only be used through a UI, it cannot be used by them. Here's what to do about it.
Uber burned through its token budget by April. Your business will be next
AI FinOps is following cloud FinOps by about a decade, and the curve is steeper. Token spend is becoming a board issue. Here's why your CFO needs a token budget now, and what one looks like.
AI is not just for engineering. Every function in your business can use it today
Finance, marketing, sales, legal, customer support, project management. AI tools can improve every business function right now. Here's what actually works in each, and what doesn't yet.
Traditional moats are dissolving. Size and capital no longer protect you
Scale, capital, and headcount used to guarantee dominance. AI is changing the equation. Competitive advantage now flows to the companies that move fastest and adapt smartest, regardless of size.
The dual-stream strategy. Protect your current business while building what replaces it
Every profitable company faces the same question: how do you invest in AI without cannibalising your own product? The answer is a dual-stream approach that protects today's revenue while building tomorrow's advantage.
Most companies are adopting AI. Few are adopting it well
84% of developers now use AI tools. A handful of organisations are getting transformative results. The difference isn't the technology. It's how it's deployed. Here's what the best teams are doing differently.
The training ladder is broken. And nobody has a plan to fix it
AI is reshaping the junior developer role, and with it, how the next generation of senior engineers gets built. The companies solving this now will have the strongest engineering teams in five years.
Why your AI spend isn't showing up in the numbers
Most AI spend isn't showing up on the P&L yet, but some organisations are seeing transformative returns. The difference isn't the technology. It's the deployment approach, and it's fixable.
Turning AI theatre into AI that moves the numbers
Innovation labs and pilot programmes look impressive in quarterly updates, but theatre is a choice, not a fate. Here's how to move from performative adoption to real, measurable production impact.
How to unlock AI ROI: what the 20% do differently
80% of AI projects return little because the return was never engineered in. It's fixable. The projects that deliver share specific, repeatable patterns in how they are scoped, measured, and governed from day one.