architecture.
33 writings found
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Treating AI Instructions as Infrastructure, Not Documentation
How encoding team standards as versioned AI instructions solves the consistency problem that plagues AI-assisted development workflows.
Making Team Standards Executable: Infrastructure for AI-Assisted Development
AI coding tools produce wildly different results based on who's prompting. Treating team standards as versioned, executable instructions solves the consistency problem.
Tests Are the Real Safety Net: Why Your AI Specs Need Executable Validation
Writing specs for LLMs is trendy. But without automated tests, you're flying blind. Here's why the spec document isn't your safety net.
Code Review, Observability, and the Cognitive Cost of AI Amplification
Rethinking code review as product judgment, observability as our new IDE, and whether AI tools extend our capabilities or replace them entirely.
The Apprentice Gap: Why Watching AI Code Matters More Than Ever
As AI agents automate more development work, we're creating a generation gap where juniors never learn the fundamentals. The ralph loop offers a solution.
AI as an Organizational Multiplier: Why Your Team's Experience Varies Wildly
AI amplifies what you're already doing. Why some teams see half the incidents while others face double, and what agent architecture teaches us about control.
AI as an Organizational Multiplier: The Case for Fine-Scoped Agents
How AI amplifies existing organizational practices, why averages deceive us, and the emerging patterns for safer agentic systems in production.
AI as an Organizational Multiplier: Why Your Company's Experience Will Be Wildly Different
AI amplifies what you already do, for better or worse. From agentic patterns to security constraints, here's what actually matters in production.
Knowledge Priming: Teaching AI Assistants Your Codebase Like You'd Onboard a Human
Stop fighting AI's generic patterns. Treat project context as infrastructure and watch code quality transform through systematic knowledge priming.
The Map That Became the Territory: AI, Specifications, and What We Mean When We Say 'I Built This'
On AI agents, observability, bespoke software, and the uncomfortable question of who actually built what when LLMs generate our code.
The Governor Is Gone: AI, Cognitive Limits, and the Mess We're Making
AI removed the natural ceiling on how much we can produce. Now the only limit is cognitive endurance, and most of us are blowing past it.
The Supervisory Programmer: Managing Agents, Context Switching, and Cognitive Debt
Senior devs thrive with LLMs while mid-level careers face challenges. But can we really manage multiple AI agents without burning out?
The Three-Tier Developer Split: How LLMs Are Reshaping Software Teams
Junior devs gain mentors, seniors gain leverage, but mid-level developers face an existential challenge as AI agents reshape programming careers.
Context Engineering: The New Frontier in AI-Assisted Development
As coding agents evolve, context engineering becomes crucial. Here's what developers need to know about rules, skills, and the art of prompt curation.
The Typography Trap: Why Bold Text is Losing Its Power
LLMs have spread the overuse of bold text everywhere. Here's why less emphasis creates more impact and how to write text that actually guides readers.