When The Agent Thinks You Are Wrong
A research-backed reflection on how agentic systems should challenge humans when they believe a decision is wrong: respectful escalation, evidence, thresholds, stop-line rules, and human override.
Writing archive
Writing - Page 5
Older essays on agentic systems, governance, operations, incentives, and the work of making AI useful in real organisations.
229 pieces
Essays and notes
Published archive
Page 5 of 10
Management Is The Missing Literacy
A follow-on to the agentic-worker education piece, arguing that management should become a general literacy: setting outcomes, judging quality, managing attention, using AI well, and taking responsibility for decisions.
We Need To Teach Children How To Manage Agentic Workers
A reflective, research-backed article arguing that the next school skill is not only AI literacy, but learning how to manage interrupting agentic workers: context switching, delegation, judgement, and knowing when to pause before accepting a recommended action.
Getting Things Done With Agentic Workers
A practical reflection on using Orchistra and agentic workers to cover the skills a small consulting business needs, while treating token spend as operating capital that has to be watched.
AI Is Not One Thing
A gentle argument for using more precise AI language: chatbot, generative AI, agentic system, local AI, foundation model, AI system, or safety-critical AI, depending on what we actually mean.
The New Product Manager May Be An Engineer Who Reskilled
AI is changing product-to-engineering ratios, but the deeper shift is capability: product managers now need engineering-grade judgement, and senior engineers may be closer to the new product role than many expect.
Before There Is No Work Left, We Have Human Debt To Pay Down
A reflection on agentic AI, productivity, and the backlog of work society has avoided because there has never been enough time.
What Agentic AI Is Teaching Me About Teaching Humans
A reflection from teaching the University of Exeter MSc Financial Technology hackathon: clearer outcomes, examples of good work, tasks, roles, mindset, and room to think help humans as much as agents.
Please Give European Companies A Safe AI Lane
A respectful request to EU policymakers: keep the safety and rights goals, but make practical AI adoption easier through sovereign options, regulatory sandboxes, and clear approval routes for ordinary companies.
When Hiring Gets Harder, AI Gets Easier
A thoughtful opinion piece on how higher employment costs can unintentionally speed up AI adoption, and why the progressive answer is not to fight automation but to make work more productive, humane, and worth hiring for.
Governance Slop
Governance slop is what happens when boards mistake policies, assumptions, and half-read papers for actual oversight. An opinion piece on the gap between governance theatre and governing.
If IT Made You Different, Start AI At The Edge
For companies whose old systems are a real differentiator, the first AI move should not be to touch the core. Start with small, separated, read-only edge POCs that earn trust before expanding.
Can Our Digital Twins Talk To Each Other?
A public invitation to people working on digital twins, A2A, MCP, and agent-to-agent communication to compare notes and run small public-safe experiments.
Your AI POC Needs Time, Not Just Technology
AI and agentic proofs of concept fail when they are treated like normal IT projects instead of onboarding a new kind of team member.
Your AI Is Guessing What You Mean
AI hallucination often starts with a bad brief: missing context, missing source links, and no safe moment to ask.
Make Your Website Agent-First
A practical note on how marketing changes when AI agents, not only humans, are researching products and making shortlists.
Start With A Safe Folder, Not A Live System
A practical operating note for introducing AI agents safely: start with a copied folder, safe material, clear project rules, no secrets, human review, and expansion only after the controls work.
What I Would Do If I Were at University in 2026
A practical, optimistic note for students and universities: AI changes the cost of knowledge work, but the backlog of human need is still enormous.
Change Management for Long-Lived Agents
Long-lived agentic threads do not just need memory and context. They need a way to absorb change, challenge old instructions, and keep a useful history of why the rules moved.
Where Is the Productivity We Were Promised?
A practical challenge to SaaS vendors, public services, and leaders: if AI has made teams more productive, where are the better features, lower costs, faster services, and visible outcomes?
When Do We Need Judgement?
A practical note on why judgement engines should be called deliberately, not sprayed across every conversation, and how agents might use them when a decision actually matters.
Sharing Is a Language
A practical note on why SaaS systems still matter for collaboration, how they create a shared language around data, and what a common-understanding MCP could give agentic teams.
Your Context Is the Next Lock-In
A practical note on why the next AI lock-in may be your context, not the model, and how to start building a useful context store for agents.
What Do Humans Do While The Agents Run?
A reflective note on the dead time that appears while capable AI agents run: how humans switch focus, supervise output, rest, talk, walk, and redesign workflows around waiting.