A guide to building an AI Center of Excellence, covering which AI practices need central control, which need a shared default, and which stay with each team.
Most AI change management advice blames people, not tech. The real failure is sequence: skipping the trust-building step before deploying the tool.
Learn why most AI business cases stall in the boardroom, and how to reframe yours around evidence instead of enthusiasm to win approval.
Over-engineering feels productive but costs teams 42% of their time. A senior architect on the linguistic tax, misaligned incentives, and user empathy.
AI compresses the manual work that consumed POs for years. A senior architect on taxonomy cleanup, BDD prototyping, and the shift to Impact Technology.
Legacy systems aren’t failures—they’re survivors. A senior architect’s case for evolutionary modernization over rip-and-replace.
Model Context Protocol (MCP) tools give AI agents direct access to production databases, internal APIs, and third-party platforms. But most teams deploying MCP today have no answer to a simple question: who authorized that tool call?
What senior engineers actually learn when they embed AI into daily development: from killing the cold start to the 3,000-test migration.
Explore the OWASP Top 10 for LLMs and learn how to identify, prioritize, and mitigate key AI risks including prompt injection, data leakage and tool misuse.
