The term technical debt is often used to refer to the accumulation of design or implementation choices that later make the software harder and more costly to understand, modify, or extend over time...
Comprehension Debt - the hidden cost of AI generated code.
Comprehension debt is the hidden cost to human intelligence and memory resulting from excessive reliance on AI and automation. For engineers, it applies most to agentic engineering.
The 80% Problem in Agentic Coding
Managing comprehension debt when leaning on AI to code
Agent Skills
AI coding agents take the shortest path to done, which usually means skipping the specs, tests, and reviews that make software reliable at scale. Agent Skill...
The AI productivity myth is more harmful than you think
Perceived productivity may be up thanks to AI, but there's debt collecting in the shadows.
The New Software Lifecycle
I co-wrote a Google whitepaper about how AI is changing the software lifecycle. I'm not going to summarize the whole thing. Instead, here are the handful of ...
Code Was Never the Asset - The Phoenix Architecture
Why AI makes the hidden economics of software unavoidable
Prompts are technical debt too
It’s common and correct to say that “all code is technical debt”. Adding code is a necessary evil for developing new features: you almost always have to do it, but each line of code adds to the complexity and maintenance burden of the system. All future changes to the system have to work with the existing code, or at least avoid breaking it. Once systems accumulate enough code, they become impossible for a single person to understand: instead of reading the code and understanding what it does, you must rely on guesses, theories and heuristics1. Sensible engineers write as little code as possible.
AI, Human Cognition and Knowledge Collapse
We study how generative AI, and in particular agentic AI, shapes human learning incentives and the long-run evolution of society’s information ecosystem. We bui
AI, Human Cognition and Knowledge Collapse
We study how generative AI, and in particular agentic AI, shapes human learning incentives and the long-run evolution of society’s information ecosystem. We bui
Mental models for working with coding agents
Model intelligence sets the ceiling. Your workflow with the agent harness sets what you actually ship.
The Five Levels: from Spicy Autocomplete to the Dark Factory – Dan Shapiro's Blog
In my last post, I wrote about technical deflation. We’re seeing the cost of code is dropping so fast that we need to change our tech debt payment plans. The smart teams…
The Gap Through Which We Praise the Machine
My current theory of agentic programming: people are amazing at adapting the tools they're given and totally underestimate the extent to which they do it, and the amount of skill we build doing that is an incidental consequence of how badly the tools are designed.
AI security issues dominate corporate worries, spending
Two reports illustrate how business leaders are thinking about and budgeting for generative AI.
Measuring Usage in the Age of AI - Research Information
Tasha Mellins-Cohen outlines COUNTER Metrics' new guidance for usage metrics associated with generative and agentic AI
10 things I learned from burning myself out with AI coding agents
Opinion: As software power tools, AI agents may make people busier than ever before.
