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Most engineering teams capable of building an internal AI knowledge system think they should. But six months later, it's a platform team's full-time job. Building an in-house AI context layer costs more money and energy than you think.
Software only has value when shipped; faster release cadence matters. Development, deployment, and operations require different thinking, metrics, and investments. There are four impacts in tech: product success, compute capacity,…
Brendan O'Leary discusses how real-world AI adoption depends on building trust rather than chasing model benchmarks. Drawing from 40 trillion tokens of usage data, he explains the four rungs of the AI adoption ladder and analyzes key…
Spring Authorization Server now lives inside Spring Security 7 under the same Maven coordinates, so the upgrade is a version bump. This server-side guide covers enabling DPoP and RFC 8693 Token Exchange, explains why 7.1 apps can silently…