Two shows. AI Week — weekly two-host news and analysis. The Moves Podcast — a short-form series on building a real AI practice. Sources cited. Plain talk.
Weekly · Mara & Theo
AI Week
Task-mapping, exposure analysis and the O*NET data layer. Canary Co's AI team, thinking out loud.
10 episodes · ~22 minShort-form · Craig Stanley
The Moves
A podcast about working with AI. The Spirit and the Moves. 22 episodes, each short enough to use the same day.
22 episodes · ~2 min each →The Map of Work
Before you decide which jobs AI will affect, you need to know what those jobs actually contain. Mara and Theo introduce O*NET and ESCO — two free, structured, public databases that map what people do at work at the task level. This is where every honest AI and jobs conversation should start.
Reading the Risk
The famous ‘47% of jobs at risk’ number is both true and badly misunderstood. Mara and Theo go task-level — walking through what exposure analysis actually looks like, how Canary Co used it on their Finance team, and what belongs in an honest exec briefing about AI and jobs.
Audio publishing soon
ESCO: The European View
The US has O*NET. Europe has ESCO — 3,000 occupations, 13,800 skills, machine-readable and free. Theo leads this one: what ESCO actually contains, why the transversal skills taxonomy is the part AI finds hardest, and three practical uses for it in AI adoption work.
Audio publishing soon
Task by Task: The HR Specialist
A worked example. Mara walks through a single occupation — HR Specialist (13-1071.00) — and maps each O*NET task against AI exposure. The results are more nuanced than the headlines suggest, and the method is repeatable for any role.
Audio publishing soon
Writing Prompts From Task Descriptions
If you know a person’s O*NET tasks, you can write a prompt for each one. Theo builds a prompt library from the HR Specialist task list — live, in the episode. Practical, replicable, and faster than any prompt engineering course.
Audio publishing soon
The New Role Profile
What does a job description look like after AI? Mara and Theo draft a new role profile for an AI-augmented HR Specialist — keeping what stays human, noting what gets automated, and naming the new skills that appear at the join.
Audio publishing soon
The O*NET API
O*NET has an API. It’s free, documented, and most AI adoption practitioners have never heard of it. Theo shows how to pull task data for any occupation in real time — and what you can build with it when you connect it to an LLM.
Audio publishing soon
ESCO as a Knowledge Graph
ESCO’s skill taxonomy is a graph — occupations connect to skills, skills connect to other skills. Mara maps it visually and shows what becomes possible when you use graph traversal to find skill adjacencies. The basis of every ‘adjacent possible’ career conversation.
Audio publishing soon
Role-Aware Agents
What changes when an AI agent knows the user’s occupation and task list? Theo builds a role-aware agent using an ESCO occupation profile as system context. The results are measurably better — and the method is simpler than you’d expect.
Audio publishing soon
Canary Co: The Full Picture
The season finale. Mara and Theo put together everything from the series — the O*NET and ESCO data, the exposure analysis, the prompt libraries, the role-aware agents — into a single coherent picture of what Canary Co’s AI programme actually looks like at task level.
Audio publishing soon