Agent approvals catch errors only at irreversible actions, with a clear diff, at a pace reviewers can read. Where to put them, and how to tell they work.
Which IT operations actions AI agents can safely take, at what autonomy level, with which controls, and how to measure it without fooling yourself.
Why card payments get declined, soft vs hard declines, and the levers that raise authorization rates without letting fraud and chargebacks rise with them.
Why banks still run mainframes, the real cost of COBOL estates, and which modernization paths work: rehost, refactor, strangler or full core replacement.
An LLM feature has four parts that change on their own. Release them as one versioned artifact behind an eval gate. The rules, tables and build order.
Why LLMs hallucinate, the three kinds of AI hallucination, and which controls actually reduce it, ranked by cost and matched to the cost of an error.
Credit card surcharge rules differ by network, state and country. When a surcharge is legal, what it does to sales, and cheaper ways to cut card costs.
Passkeys remove phishable passwords, but enterprise rollout hinges on synced vs device-bound keys and account recovery. A phased plan by user population.
Most systems called agents should be workflows with a model call inside. The four shapes, a scoring rubric, and when autonomy is worth what it costs.
LLM document extraction reads layouts OCR templates cannot, and invents fields it cannot read. When it beats IDP, what it costs, and the controls it needs.
A company has no biometric and no single registry. Why KYB still takes days, what beneficial ownership really requires, and how to tier verification by risk.
SLI, SLO, and SLA are three different things. How to pick targets users can perceive, and why the error budget policy is the only part that changes behavior.
Deep analysis across the systems, strategies, and economics that shape modern technology.
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