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The first open draft of the Protocol-Governed Computing (PGC) Standard is now available for public scrutiny. It is an attempt to address a problem that becomes increasingly expensive as business software grows older: how to preserve the governing meaning of a system while allowing its implementation to change. That picture is the whole idea in one frame. On the left, the governed meaning of a system: stable, explicit, written down. On the right, every language and runtime anyone might choose to realize it in. The protocol is the bridge, and it is deliberately narrow — it says what must be true, and says nothing about which road you take to make it true. ...

The new millennium entered adolescence after the Dotcom Bust, followed by waves of Cloud Computing, Mobile/Social Networking, and now, the AI boom. Each wave followed roughly a ten-year cycle, and the next one is already written on the wall in invisible ink, if you only connect the dots. The next great IT wave may not be CapEx-rich Quantum Computing. It may have to be some OpEx-rich wave, perhaps Software Engineering?. That is if you believe AI will survive and thrive unlike Dotcom bust. ...

“The future of software engineering is not about humans writing more code. It is about humans governing what software is allowed to do.” AI has changed the software equation. Something fundamental is happening in software engineering. AI coding systems can now generate applications, refactor repositories, explain architectures, and produce implementations at a speed that was unimaginable only a few years ago. The question dominating the industry has been: “How soon will AI write all software?” ...

“The future of software engineering isn’t about replacing programmers. It’s about separating business behavior from software implementation.” Every week brings another AI coding breakthrough Claude writes production code. Cursor refactors entire repositories. GitHub Copilot completes functions before we finish typing. OpenAI, Anthropic and Google continue pushing software generation toward astonishing levels. The question dominating our industry has become: “How soon will AI write all software?” I believe that’s the wrong question. ...

I want to tell you about a vacation that changed the way I think about software. Not a vacation spent debugging. Not a working trip. A real one — a milestone birthday, a mountain, eight days of trains — and somewhere on the far side of it, an idea I had been chasing for months finally walked up and introduced itself. The Trip My son treated me to a milestone birthday with a plan I could not have dreamed up myself: stand on top of Mt. Fuji on the 4th of July and unfurl a US flag at the summit. ...

Governed by Protocol. Constructed by Compiler. Proven by Trace. A reference architecture for building deterministic, inspectable, AI-era software systems. Why this exists Modern software has a governance problem. As systems become: distributed, event-driven, AI-assisted, and increasingly machine-generated, the gap between: what engineers intended, and what software is actually allowed to do keeps widening. Behavior hides in: orchestration code, runtime conditionals, framework conventions, implicit routing, service glue, and increasingly, AI-generated implementation details. PGS explores a different model: ...

I want to tell you about a Sunday evening that changed the way I think about software. Not a Sunday spent debugging. Not a Sunday in front of a whiteboard. A Sunday with friends — the kind where conversation wanders into the places you usually avoid, and then someone says something that reorients you without meaning to. The Weight of Watching We were a small group, sitting together the way old friends do. At some point the topic turned to the conflict in Gaza. I do not remember exactly how we got there — these things find their way in. ...

I should tell you something about myself before we get into software architecture. When I am not writing Python code as a hobby, I am a regenerative backyard organic edible gardener — or at least I was, until a software project took on a life of its own and consumed most of my waking hours. More on that in a moment. First, the garden. The Garden That photo above is mine. Taken this morning. ...

AI can now generate application layers faster than organizations can govern them. The bottleneck is no longer implementation. The bottleneck is admissibility — whether a piece of behavior should be allowed to exist at all, before it runs. Most modern SDLC tooling still assumes humans produce software slowly enough for governance to remain procedural: review, approve, release, monitor, patch. That assumption held for decades. It is now under pressure that none of its architects anticipated. ...

In the last few years, AI has dramatically accelerated software implementation velocity. Code generation. Agentic tooling. Autonomous orchestration. Self-modifying pipelines. Framework-assisted composition. Entire application layers can now be produced in hours instead of months. But underneath this acceleration, a deeper architectural problem is emerging: AI changed how fast we can build software. It did not change how software is fundamentally governed. And that distinction matters far more than most organizations currently realize. ...