Most products do not fail because a team cannot ship version one. They fail because version one quietly becomes the architecture, operating model, and decision-making process fo...
AI can produce a prototype in an afternoon. That is impressive, but it is not the same as creating software people would struggle to replace. The difference matters. A product b...
AI can produce a function in seconds. It can explain an unfamiliar error, draft a migration, summarize a pull request, and suggest tests that a busy teammate may have missed. Th...
Most teams now know how to ask an AI assistant for code. Far fewer know how to build software that gives the assistant something reliable to learn from. That distinction matters...
AI does not become useful because a team adds a chat box to an existing product. It becomes useful when the product creates a reliable loop between a real customer need, a well-...
Software is increasingly built with capable machines at our side. They can suggest code, summarize tickets, generate tests, and turn a rough idea into a prototype in minutes. Th...
AI is becoming part of the delivery team: it reads tickets, summarizes incidents, suggests code, answers support questions, and helps new contributors navigate unfamiliar system...
AI is changing product development before its rules are fully written. Models improve, vendors alter pricing, regulations evolve, and customer expectations move faster than most...
AI can produce a convincing function faster than most teams can open a pull request. It can explain a framework, draft tests, refactor a module, and offer three approaches to a ...
AI can write a function before a developer has finished describing it. That is impressive, but it is not the same as understanding software. The difficult part of building usefu...
AI can generate a screen, a function, or a passable product brief in seconds. That is impressive. It is also easy to mistake speed for progress. Software earns its place when it...
Software is no longer judged only by what it does today. Increasingly, it is also judged by whether people and AI systems can understand, change, test, operate, and learn from i...
Most AI teams do not have a learning problem. They have a signal problem. People can find courses, papers, frameworks, prompt libraries, model releases, and opinions faster than...
Artificial intelligence can produce a landing page, draft a feature brief, generate a component, and suggest a marketing headline in moments. That changes the economics of makin...
Artificial intelligence is becoming a new kind of product user. It reads your documentation, interprets your interfaces, navigates your workflows, and increasingly helps custome...
The loudest AI strategy is usually the least useful one: announce a capability, add a chatbot, race competitors to a demo, then hope customers discover a reason to care. That is...
Ownership is valuable, but it is no longer a sufficient moat. AI can produce competent code, summarize tickets, generate tests, and explain unfamiliar APIs with remarkable speed...
Most software teams say they want to move faster. Fewer ask a more revealing question: can the product help its own builders understand it? A codebase that requires oral traditi...
AI changes the economics of software, but it does not remove the need for engineering judgment. It makes that judgment more visible. A team can now generate a working feature, t...
A product rarely fails because its developers could not write code. More often, it fails because the people closest to the technical trade-offs were invited into the conversatio...
