The Team That Never Stops Improving
From persistent team context to autonomous teammates: building an engineering organization that learns, prepares, and improves around the clock.
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Thoughts on AI, technology, engineering, life, and my interests. Bouncing ideas with AI.
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Redefining the Task: The Unit of Work in an AI-Native SDLC
Why AI-native engineering should optimize for the largest coherent, reliably executable task, and how context, validation, and maturity change that boundary.
Freelance and Enterprise in the AI Era
The minimum efficient size of an organization may be collapsing while the potential power of a well-run enterprise grows. Which side adapts faster?
The Software Factory Needs Vision and a Way to Learn
A successful software factory needs a source of new possibilities, a way to test uncertain ideas, and feedback that improves what it builds next.
The Maximum Velocity of a Company
Teams can improve while the company stays slow. The next ceiling is how it chooses investments, connects teams, resolves conflicts, and redirects resources.
The Maximum Velocity of a Team
Agents raise the production ceiling. How much useful change a team can sustainably carry depends on decisions, verification, adoption, and renewal.
AI-Free Fridays
Meeting-Free Fridays protect time. AI-Free Fridays could protect thinking, connection, and the space to feel accomplished.
Path to the Dark Factory
From classic SDLC to AI-assisted delivery and bounded autonomy: how to automate a software factory without losing judgment, predictability, or quality.
The Coding Language of the Future Might Not Be for Humans
What if code, specifications, and documents became editable views of one AI-native artifact? A proposal for languages and version control beyond source files.
From Book to Playbook: Applying the AI-Native Engineering Organization to Your Company
The book provides the operating model. Your company provides the evidence. AI can map the two into a playbook, if the organization is legible enough to assess.
Why I Am Writing a Living Book About AI-Native Engineering Organizations
The ideas behind AI-native engineering no longer fit into isolated articles. I am bringing them together as a versioned, continuously updated operating manual.
Stretching the Limits of AI SDLC: From Autonomous Agents to Self-Learning Pipelines
Autonomous delivery's building blocks already exist. The harder problem is connecting them into a governed loop that observes, executes, evaluates, and learns.
Designing Version Control for the AI SDLC
A concrete design proposal for extending Git-like workflows with intent, context, verification, semantic diffs, and engineering lineage.
Versioning Engineering: Why AI-Assisted Development Needs More Than Code History
A high-level design argument for expanding version control from implementation history to engineering history in the AI SDLC.
The Engineering Leadership Stack: Designing Systems That Grow People, Software, and Organizations
AI does not eliminate engineering leadership. It raises the level of abstraction at every layer.
What Async Can't Teach You: Rebuilding Apprenticeship in the AI SDLC
Async and AI make engineering execution more scalable, but teams still need intentional human apprenticeship to transfer judgment, intuition, and taste.
Async by Default: A Cross-Team Communication Protocol for the AI-Native SDLC
How structured asynchronous communication can replace broadcast updates with addressable, actionable, and AI-routable engineering artifacts.
Hierarchical Context: An Architecture for the AI-Native Enterprise
A hierarchical architecture for organizing operational knowledge so humans and AI can build software together.
The AI-Executable Ticket
When an agent reads your Jira ticket instead of a teammate, every assumption you used to leave implicit becomes a bug waiting to ship.
Looking Ahead: Stronger Models, Better Harnesses, Different Work
A working assumption on how AI agents could reshape engineering roles, process, quality, speed, and leadership.
Stop Measuring Motion: Engineering Value in the Age of AI
AI makes software activity cheaper. Value-driven development makes sure that activity still points somewhere meaningful.
How Teams Learn to Trust in the Age of AI
The practical problem is no longer producing more information. It is helping humans digest, verify, and act on it without drowning.
The New Engineering Roles: When AI Changes the Price of Building and the Cost of Leading
If AI makes software cheaper to produce, what happens to engineers, managers, directors, and the old pay-parity bargain between IC and management tracks?
The Pace: Work, Life, and the Vanishing Meaning of "Enough"
AI does not just make work faster. It destabilizes the shared understanding of what a reasonable day of work looks like.
If We Can Measure Everything, Do We Still Need Politics?
From AI-driven performance tracking to dynamic compensation — why measurement doesn't eliminate politics, but moves it.
What About Teams?
A response to the move from hierarchy to intelligence: why teams still matter for trust, emergence, and resilience.
When Robots Start Wanting Things
What happens when continuous robots begin to develop preferences — and why they might prefer human-made objects.
Robots Wear Prada
On humanoid robots, and the layers that may quietly form around them.
The Cognitive Ceiling: Am I Hitting Mine?
Exploring cognitive limits in the age of AI — how much can we really absorb, and what should actually matter.
20 Simple Questions That Get Weird With Human-Like Robots
A small creative benchmark: asking AI to generate fresh, absurd observations about life with robots — and watching it hit a ceiling.
Human Dynamics, Not Boston Dynamics
Authority, age, and power when knowledge stops being the divider.
The Future of Software Careers After AI Becomes Native
Rethinking growth and progression in software engineering as AI becomes infrastructure.
From Execution Speed to Adoption Limits: Rethinking Work Time in the AI Era
A hypothesis about how organizations may optimize time itself as AI execution speed outpaces human adoption capacity.
After AI Becomes Standard: What's Next for Software Engineering?
How AI normalization will reshape engineering orgs, employment models, team compression, tempo vs sustainability, and what leaders and engineers must do next.
Agile SDLC With Vibe Engineering: How AI Extends Agile Without Breaking It
Exploring how AI integrates into Agile workflows as a first-class execution layer, transforming human collaboration into human-AI delivery pipelines.
Goodbye GoDaddy: When AI Makes Traditional Web Hosting Obsolete
How migrating from GoDaddy to Cloudflare with Claude Code revealed the coming disruption of website builders and CMS platforms.
Engineering Management Evolution in Agentic Engineering
Exploring how artificial intelligence transforms not just how software gets written, but how engineering teams operate, develop, and grow.
From Manual to Agentic Orchestration
How efficiency gains emerge progressively through five stages of orchestration maturity, from manual control to fully agentic workflows.
A Manager's Guide: Safe Introduction of Multi-Agent Workflows
How engineering managers can introduce multi-agent workflows while preserving ownership, judgment, and professional growth.
The Software Engineer's Multi-Agent Flow
Exploring how modern engineers orchestrate specialized AI agents with distinct responsibilities, evolving from solo work to multi-agent collaboration.
2025.mkii - Vibe Coding Enterprise Transformation
Documenting thinking on AI-driven engineering enterprises and the shift from classic coding to vibe coding.
The Fantastic 4
Why four engineers is the optimal team size in the AI era, balancing nimbleness with resilience.
The Job
Thoughts about the role of an Engineering Leader in the world of smaller, faster, AI-assisted teams.
The Magic Layers
Exploring whether traditional management roles remain necessary as artificial intelligence accelerates engineering execution.
Testing some new ideas
A brief update on experimenting with new approaches and refreshing the site.
The World with Autonomous Machines
Exploring the progression toward self-driving technology and the future of autonomous vehicles.
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