craftsmanship The Standards That Scale: From Code Quality to AI Governance Just as code quality demanded standards in 2013, AI governance requires them now. Organizations willing to say no to deploying autonomous agents without robust infrastructure will build trustworthy AI systems.
DevOps Trust Was Always the Problem: From DevOps to Agentic AI DevOps adoption stalled not due to tooling, but a lack of trust. We're seeing the same pattern with agentic AI – capability isn’t the blocker, it’s building trustworthy infrastructure.
CI-CD From CI/CD to the Intelligence Operating System Strong software delivery practices—like CI/CD—build mental models crucial for building trustworthy AI systems. The path to an "Intelligence Operating System" accelerates when you understand the direct lineage from source control to AI governance.
agile The Manifesto We Forgot We Were Following The Agile Manifesto's authors wrote a weighting. Twenty-five years of practice turned it into an instead-of. Treating context-specific trade-offs as timeless principles is technical debt at the organizational level.
AI-native The Intelligent Software Factory The Intelligent Software Factory embeds AI across the entire ALM lifecycle, from planning to deployment—transforming software delivery with a hybrid intelligence approach. It's the ALM infinity loop, reimagined.
AI-Native Delivery The Product Team's Evolution, Stage 5 and 6: Delegating and Coordinating Stages 5 and 6 hand whole product workflows to autonomous agents and then coordinate many at once. Each layer costs roughly seven times the one below, and crossing into it requires the technical depth most product roles have yet to build.
AI-Native Delivery The Engineer's Evolution, Stage 5 and 6: Delegating and Coordinating Stages 5 and 6 move the engineer from delegating trusted workflows to coordinating many agents in parallel. Each layer costs roughly seven times the one below, which is why the Stage 4 groundwork decides whether delegation is leverage or unattended risk.
AI-Native Delivery The Product Team's Evolution, Stage 4: Designing the System That Decides Stage 4 moves quality out of individual review and into automated gates inside shared workflows. Each product role becomes an architect or governor of the system, and the floor of competence rises to match the wider reach.
AI-Native Delivery The Engineer's Evolution, Stage 4: Designing and Governing the Workflow Engineers evolve to Stage 4: Workflow. Automate checks and build "protection harnesses" for repeatable tasks, shifting focus from manual review to system governance and team leadership.
AI-Native Delivery The Product Team's Evolution, Stage 3: Encoding the Craft At Stage 3 each product role writes down how it actually works and encodes its standards into personal agents. The drafting load drops, the judgment load rises, and one person's definition of good becomes repeatable.
AI-Native Delivery The Engineer's Evolution, Stage 3: Directing the Work Instead of Doing It Stage 3 is where the role visibly changes. The developer documents how they work, encodes it into personal agents, and moves from typing to directing and reviewing. The tester becomes a test designer.
AI-Native Delivery The Product Team's Evolution, Stage 2: A Faster Draft for Everyone Product roles climb the same AI maturity curve as engineers. At Stage 2 every designer, analyst, owner, and PM has a capable assistant, the gains are real and personal, and nothing compounds until the team writes its craft down.
AI-Native Delivery The Engineer's Evolution, Stage 2: The Developer With an Assistant Part 1 of a series on how the software engineer's role changes as teams climb the AI maturity curve, following a developer and a QA engineer through each stage.
vocabulary The Vocabulary of AI-Native Organizations AI is creating a vocabulary crisis at organizations. Without shared language, we risk making crucial AI decisions based on misunderstandings—it's a thinking problem, not just a communication one.
AI-native AI as Organizational Foundation, Not Feature Is AI a feature you are adding to your organization or a foundation you are building it on? The answer sets the ceiling on what AI can return, and the reengineering era already showed us why.
IOS The Intelligence Operating System: Three Layers An operating system does not do the work of its applications. It makes them possible. AI-native organizations need the same foundation: hybrid intelligence, a governance engine, and an operating model.
ai-governance Governance Is Not Overhead. It Is the Engine of Trust. AI deployment failures share a pattern: capability shipped without the infrastructure that makes autonomy trustworthy. Five mechanisms form that infrastructure, and they have a centuries-old precedent in financial controls.
AI-architecture Hybrid Intelligence: Neural + Symbolic + Governance The neural versus symbolic debate is the oldest fight in AI, and it resolves in combination. Reliable systems pair both with a governance layer that makes them deployable.
AI-native From Doing to Defining, From Coding to Orchestrating The closing line of the POST-AI framework describes a real shift in the knowledge worker's role. What it means, what it does not mean, and where the claim could break.
agile P.O.S.T.: Four Dimensions of AI-Native Delivery P.O.S.T. reformulates the four Agile values as four measurable dimensions: Productivity, Outcomes, Satisfaction, and Time to Market. A diagnostic and a design tool.
agile The Three Eras of Agile: Constraint, Synergy, Intent Agile practices have moved through three eras defined by their binding constraint. Knowing which era your team is in tells you which practices fit.
agile The Agile Manifesto Was Written for a World Without AI The Manifesto's trade-offs answered a scarcity of human execution capacity. AI removes the scarcity. The intent survives; the formulation needs to change.
agile The P.O.S.T. AI World: Resetting the Agile Manifesto for the Age of Agents The Agile Manifesto's "over" was an admission of scarcity: teams could not afford both sides. As AI lifts the execution constraint, the word worth testing is "and."
AI The Skill Leveling Effect: What Happens When AI Helps Everyone Equally AI's productivity gains skew heavily toward junior and mid-level workers. The floor rises, the distribution tightens, and judgment becomes the scarce asset.
agentic-AI The Woodshop-to-Factory Transition: Why Stage 3 Is Not a Small Step Moving from AI-assisted tools to autonomous agents replaces the operating environment, the way the factory replaced the woodshop. The infrastructure comes first.