Knowledge Base

AI-generated specs can look complete while quietly hiding the business rules that only exist in people's heads — and shipping on top of that gap compounds it.

Outdated documentation doesn't just mislead people anymore — fed into an AI agent, it becomes confidently wrong instructions at machine speed.

Tech debt isn't just old dependencies. Architecture debt, knowledge debt, and decision debt quietly cost teams more than the obvious kind.

Context alone doesn't make AI-assisted development work. Strong engineering culture — reviews, standards, ownership — matters more than the tools.

AI didn't kill SaaS — it's squeezing the weak, single-feature tools while mature platforms with real ecosystems keep compounding their advantage.

A look at attention engineering through the lens of industrial-era toxicity — and why pretending algorithmic manipulation of focus 'isn't our business' doesn't hold up.

Indexing a repo isn't the same as understanding it. Generate diagrams and maps with AI before trusting it to modify code, not after.

Shipping fast with AI and no process doesn't just create debt — it traps you as the only person who can maintain what got built.

Coding agents introduce a form of technical debt teams aren't tracking yet — and it doesn't show up in the usual places.

The last 20% of an AI-assisted feature is where most launches quietly fall apart. Don't crash before you launch.

Standard measures of developer productivity don't hold up under scrutiny — and leaning on them harder just optimizes for the wrong thing.

Stop coding, start building: a workflow for using AI tools that treats them as part of a building process, not a typing shortcut.

Model Context Protocol (MCP) is fundamentally a communication standard that allows Large Language Models (LLMs) to interact with external systems in real-time.