Blog
Architecture, AI and Mind
Software architecture and code quality. AI — from real-world deployment to questions of consciousness, knowledge and values. And, at the edge, the philosophy of science and the biology of symbiosis. No filler, with a clear line between hypothesis and what we know.
Truth, Sources, and RAG: Why Citations Alone Are Not Enough
A citation looks like proof, but RAG only solves where the model got its information — not whether it holds. Four ways a citation lies, and how to measure truth, not just faithfulness to a source.
The End of Moore's Law? First Ask Which One
A vendor announces a "2-nanometer chip" and it sounds like engineering at the edge of the atom. But that number measures nothing — and "the end of Moore's law" depends on which of the three you mean.
Reasoning in Words or in Vectors? Latent Reasoning and the Window We Might Close
Each word in a chain of thought carries about 17 bits; the internal state, thousands. Why we force models to think in words when they compute in vectors — and what moving to vectors would irreversibly cost.
How Language Models Get Hacked: A Map of Attacks From Training to Deployment
Prompt Injection: The Security Hole You (Still) Can’t Patch
How to Track New AI Models Without the Hype: A Practical Radar for OpenAI, Claude, Gemini and Coding Agents
AI Agent Memory: Why a Long Context Is Not Memory
You give an agent a million-token context and expect it to stop “forgetting”. But memory is an umbrella word for several different mechanisms — and a long context solves only one of them.
Fine-Tuning Is Not Teaching: What You Risk When You Touch the Weights
Fine-tuning looks like the natural step after prompting. But it forks the model and takes on infrastructure: the durable asset is the data pipeline, not the weights, and the real cost is operational.
Can AI Invent Something New, or Only Recombine?
“AI just reshuffles what it has seen” sounds smart and skeptical. But a few systems have produced results that were demonstrably not in the training data — where is the line between remix and discovery?
Technical Debt and Architecture: Why You Will Not See the Most Expensive Debt in Code Review
When Does AI Deserve Moral Status? A Decision You Can’t Outsource to Philosophers
Can AI Be Conscious? A Serious Answer Without the Sci-Fi
Fungi, Mycelium, and the Illusion of Individuality: Where One Organism Ends
“One organism” sounds like an obvious unit. Fungi break that obviousness: mycelium, symbiosis and mycorrhizal networks show the boundary of an individual is often a habit, not a fact.
Bioelectricity, Form, and the Body’s Memory: How a Body Knows What Shape to Be
The genome is a parts list, not a build plan. So what holds the template of a body’s shape and guides regeneration? Michael Levin points to a measurable, editable layer: bioelectric signals.
How to Read Bold Claims: The Case of Morphic Resonance
The idea that nature has memory and forms repeat through “resonance” is seductive. But as a hypothesis it must pass the same test as any other: can it be refuted, and has it survived a controlled experiment?
AI and Values: Why Alignment Is Not Just a Safety Problem
Scientific Dogma and New Ideas: When Skepticism Protects and When It Blocks
AI and Identity Over Time: Is an Agent With Memories Still the Same Agent?
Science Is Fragmenting: Why Almost Nobody Sees the Whole Picture Anymore
Science has never known more — and never has anyone understood less of it whole. Specialization is both a triumph and a trap. On what is lost when fields stop talking.
Does AI Have Intentions? Intentionality, Goals, and Simulated Reasons
“The agent decided to…” — we say it without blinking. But does the agent have intent, or just generate behavior that looks like intent? And does it matter in practice? It does.
AI Architecture for Companies: When a Prompt Is Enough, When You Need RAG, When You Need an Agent
A company decides to “do AI” and six weeks later has a vector database and an agent framework — for a task a well-written prompt would have solved. The architecture was chosen before the problem was understood.
Agency and Accountability in AI Agents: When Does a Tool Start to Act?
Why Code Review Won’t Save Your Architecture If You Only Ask About Lines
AI and the Problem of Authority: Who Gets to Decide What Is True?
Architecture Is the Shape of the Team: Why Code Boundaries Mirror Company Boundaries
An architecture diagram and a company org chart tend to look suspiciously alike. That is not a coincidence — it is Conway’s law. And while you treat it as trivia, it works against you.
What Does It Mean for a Model to Understand? Between Tokens, the World, and Useful Behavior
The “understands vs. parrots” debate is framed wrong. The useful question is what kind of understanding a model has, where it ends, and where it fails you.
Architecture Decision Records: The Team Memory That Saves Future Refactoring
Code says what, git says who and when. The why is missing — and it leaves with the people who left. An ADR is a cheap way to remember an architectural decision before someone tears it out by accident.
Local Models vs Frontier Models: Where the Practical Limit Really Lies
Maintainable Code Is an Economic Property, Not an Aesthetic Preference
How to Read AI Papers Without Spending Your Life on arXiv
Technical Debt Is Not Messy Code: How to Spot the Debt That Actually Costs Money
Messy code and technical debt are not the same thing. Real debt is a deliberate or structural gap between your code and what you now know — and to manage it you first have to classify it.