The practical issue with artificial intelligence agents isn't just how clever they are, but what they're allowed to do. Jonathan Harris explains why governance needs to precede deployment, moving beyond benchmark scores to focus on precise control over access and actions. This week, we examine how the hype around agentic AI often distracts from fundamental questions of authority and security.

We also look at the layers of engineering behind AI systems – prompt, loop, and graph – and why confusing them leads to costly misunderstandings. From industrial safety to the structure of the web, the real progress lies in architecture and careful control, not just more confident claims or faster models. Scepticism, as Jonathan Harris notes, is basic maintenance.

Jonathan Harris cuts through Agentic AI, Model Hype, MCP and Agent Skills, Dirty Data, and Workflow Automation in this 60-minute Turing’s Torch: Artificial Intelligence Weekly briefing. What matters is simple: what is useful, what is undercooked, and who carries the risk once the demo glow wears off.

Expect plain-English context on power, money, data, labour and control, with the usual vendor fireworks left outside where they belong. Longer episodes also leave room for the awkward plumbing: incentives, security assumptions, governance gaps, and the budget line nobody wanted to read.

Jonathan Harris cuts through Model Hype, Dirty Data, Workflow Automation, and AI Governance in this 45-minute Turing’s Torch: Artificial Intelligence Weekly briefing. What matters is simple: what is useful, what is undercooked, and who carries the risk once the demo glow wears off.

Expect plain-English context on power, money, data, labour and control, with the usual vendor fireworks left outside where they belong.

What matters is discerning the practical utility of AI advancements from the prevailing hype. Jonathan Harris examines how new AI models and agent skills are being implemented, often revealing that the real challenge lies in the surrounding infrastructure and governance, not just the core technology. This week explores the tension between convenience and control, the complexities of decentralised AI, and the critical need for robust data engineering and benchmark hygiene to ensure genuine capability.

Jonathan Harris cuts through MCP and Agent Skills, Retail Edge AI, Workflow Automation, and AI Governance in this 45-minute Turing’s Torch: Artificial Intelligence Weekly briefing. What matters is simple: what is useful, what is undercooked, and who carries the risk once the demo glow wears off.

Expect plain-English context on power, money, data, labour and control, with the usual vendor fireworks left outside where they belong.

What matters is understanding the practical implications of AI systems that act autonomously. Jonathan Harris examines how generative AI in planning and finance, alongside vendor partnerships, creates risks of lock-in and accountability issues. We separate genuine progress from the noise, especially concerning agentic AI which moves from advice to action, demanding robust governance and human oversight, not just technical solutions. The episode covers the real costs and consequences of deploying AI in core functions.

What matters is the gap between AI claims and real-world results. Jonathan Harris examines how AI models behave outside the lab, from conservation efforts to retail AI demand forecasting. We look at the practicalities of edge AI, the trade-offs in smart retail, and why governance and honest reporting are crucial. This week, the focus is on what works, not just what’s announced.

Jonathan Harris cuts through Agentic AI, Workflow Automation, AI Governance, and AI Costs in this 45-minute Turing’s Torch: Artificial Intelligence Weekly briefing. The point is not to cheer every announcement from the pavement. It is to work out what is useful, what is undercooked, and who carries the risk once the demo glow wears off.

Expect plain-English context on power, money, data, labour and control, with the usual vendor fireworks left outside where they belong.

Jonathan Harris looks beyond the hype to examine AI's quiet shifts. This week, we assess how conversational AIs can subtly inject advertising, the challenges of turning assistants into autonomous agents, and the practical importance of benchmarks for scaling AI. It's about the plumbing, not the fireworks, and understanding the real-world implications for trust, regulation, and who ultimately controls these systems.

Jonathan Harris cuts through Model Hype, Workflow Automation, AI Governance, and AI Costs in this 60-minute Turing’s Torch: Artificial Intelligence Weekly briefing. The point is not to cheer every announcement from the pavement. It is to work out what is useful, what is undercooked, and who carries the risk once the demo glow wears off.

Expect plain-English context on power, money, data, labour and control, with the usual vendor fireworks left outside where they belong.