Anthropic has announced a $100 million commitment to Claude Frontier Academy, aiming to train 10,000 engineers by the end of 2027. The programme focuses on deploying AI inside businesses, with Commonwealth Bank of Australia and Morgan Stanley among the organisations named in its first cohorts.

The company describes an initial practical training and assessment stage followed by a 12-week residency. Participants lead a real Claude project at their organisation with support from Anthropic engineers. Cohorts are running in London, New York and San Francisco, according to the announcement.

The investment addresses a problem that model procurement alone cannot solve. Moving an experiment into production requires people who understand the business process, its data and the consequences of a system making a mistake. Engineers also need to work with security and operational owners during deployment.

Enterprise buyers should distinguish a training commitment from evidence of successful projects. Useful measures will include whether participants can maintain systems after deployment, explain their controls and demonstrate improvements against an agreed baseline. A credential may help identify trained staff, but the harder test is whether their projects work safely in the organisation's own environment.

Execution Level Governance- What audit-ready agent governance actually looks like
David Girvin, founder and CEO of Assury argues that model-in-the-loop review, AI governing AI, is fundamentally unreliable for regulated environments: even the best-performing models miss a meaningful share of violations, the reviewing model is typically provided by the same vendor being reviewed, and prompt injection or context poisoning can compromise both the acting agent and its supposed overseer simultaneously. He makes the case for deterministic, architecturally enforced controls instead, walking through Assury’s approach of autonomy zones, session risk accumulation, and credential starvation, which lets a compromised agent be cut off from its tools instantly rather than relying on time-boxed access. The conversation touches on why David is sceptical of just-in-time credentialing as a solution for agent security more broadly, since agent sessions don’t run on predictable human timescales, along with the current gap between how identity and security vendors are pitching agent protection and what he sees happening at the execution layer in practice. He also discusses the compliance and audit implications of probabilistic decision-making, arguing that regulated industries will increasingly need tamper-evident, hash-chained audit trails that can withstand scrutiny from auditors and regulators who are only beginning to understand agentic risk, and reflects on a named frontier lab’s own published framework as an example of the gap between research and practitioner reality. Elsewhere, David reflects candidly on building a bootstrapped security company in an increasingly crowded market, why he turned down aggressive VC funding to stay in control of the product, and what a credible third-party assessment of his own gateway would need to look like given that Assury sits directly in the execution path for every customer’s agents.
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