SpaceX is reportedly seeking $40 billion in external financing to buy Nvidia AI chips, in a proposed package that would make advanced compute one of the largest new demands on corporate credit markets. Reuters, citing the Financial Times, said Apollo Global Management is expected to lead the transaction.

The reported structure comprises about $10 billion in bank loans and $30 billion in investment-grade debt, with the transaction expected to close in 2027. Pimco is said to be among a small group of lenders in talks. SpaceX, Apollo and Nvidia had not responded to Reuters requests for comment, while Pimco declined to comment. The proposal should therefore be treated as reported negotiations, not completed financing.

The strategic point extends beyond one borrower. AI infrastructure is becoming too capital-intensive to fund solely from operating cash or equity. Reuters cited a Morgan Stanley estimate that the sector could require $1.5 trillion in external financing by 2028, even as lenders become more selective about returns, collateral and concentration risk.

For financial institutions, this creates opportunities in lending, syndication and capital markets, but also new underwriting questions. Chip obsolescence, power availability, utilisation assumptions, customer concentration and links among model companies, cloud operators and hardware suppliers can turn a technology bet into a correlated credit exposure.

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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