AI Augmentation Software Was First. Expertise Is Next. The next big opportunity in AI is making human knowledge executable, turning the expertise, judgment, and connections inside organizations into capabilities they can scale.
AI Engineering Featured The Difference Between Making Software and Engineering It AI is separating the craft of making software from the discipline of engineering it. The future is not hand-coding everything or becoming a prompt router. It is governed delegation: owning intent, constraints, evidence, risk, and outcomes while machines do more of the production.
AI Factory Featured The Factory Should Not Know the Project A software factory should know how to build software, not what every project means. The project harness carries knowledge, standards, policy, and evidence. Factory memory carries lessons across builds, turning learning into an architectural capability.
AI Engineering From Scripts to Seats Agentic systems are moving from tool use to loops. The harder transition is turning those loops into accountable seats. That requires an operator to encode SDLC knowledge, verification, authority, and evidence so responsibility can be delegated safely.
AI Factory Software Factories Need Building Codes Harnesses govern how autonomous software gets built. The next problem is deciding what properly built software means.
AI Engineering Featured We’re Converging on a New Shape for Software Anthropic’s AI-Native SDLC and my Software Manufacturing white paper point to the same deeper shift: as code generation becomes cheap, software engineering reorganizes around intent, standards, evidence, control, and safe delegation.
