A new working paper from The Anthropic Institute models three versions of the US economy in 2030. In the modest world, AI behaves like a normal technology. In the extreme world, GDP is 32 percent higher, total pay to workers barely moves, and nearly one in five knowledge workers is unemployed. The authors say none of the three can be ruled out today.

This episode walks through the scenarios, states plainly what the research leaves out, and offers four ideas for how leaders can prepare a workforce without knowing which world arrives. There is no verdict. Each idea ends on the question it leaves open.

Source: Working Paper 2026-02, a working paper shared for comment. The Institute is affiliated with Anthropic, which builds Claude.

In June 2026, automated traffic passed human traffic on the open web for the first time, eighteen months ahead of Cloudflare's own forecast. In Episode 14, Laurence Gill breaks down the shift from AI that informs to AI that executes, the deterministic guardrails that make agentic automation safe to deploy, and the same capabilities now driving a sharp rise in credential-based cyberattacks. The episode closes with a practical framework for structuring data, evaluating emerging commerce standards, and hardening personal and organizational defenses in a web where the majority of visitors are no longer human.

Learn more about the host Laurence Gill at: www.laurencegill.com

For twenty five years, software pricing has worked like flat-rate insurance: pay a fixed premium for the capacity you own, not for the value it delivers. AI agents just broke that model, and the fallout is bigger than a line item on your next renewal.

In this episode, Laurence Gill breaks down why AI agents are killing per-seat software pricing, and why what’s replacing it is really a risk-transfer mechanism in disguise. Drawing on principal-agent economics, a real vendor case where efficiency gains cost a company most of its recurring revenue, and two decades of federal IT audit experience, Laurence lays out exactly what leaders need to understand before signing their next AI vendor contract, including the four questions that determine who actually holds the risk when the system fails.

If you’re evaluating, renewing, or negotiating any AI agent contract this quarter, this episode gives you a framework for asking better questions than “how many seats do we need.