Analysis of DevRel evolution from 2020 to 2026, focusing on thematic shifts, product-centric advocacy, and the impact of coding agents.
Deep dive into Claude Code hooks: 27 events analyzed, practical usage tips for PreToolUse, PostToolUse, and more.
Explores how coding agents change software library documentation, focusing on making libraries agent-friendly rather than human-friendly.
Explores how AI coding agents shift engineering focus from writing code to code review, making review the most leveraged skill in software.
Explains why coding agents struggle with image-based architecture diagrams and advocates for code-based diagrams like Mermaid.
Explores loop engineering, a new approach where developers design systems that prompt AI agents instead of manually prompting them.
How to place low-level architecture documentation in the codebase for better clarity and AI agent support.
A curated daily reading list covering AI coding agents, Bigtable history, prototyping speed, design patterns, and tech industry trends.
Explores 10 essential design patterns for coding agents and agentic software delivery, moving beyond AI-assisted coding to AI-augmented development.
Uber caps employee AI coding tool spending at $1,500/month per tool to manage costs after overspending its 2026 AI budget.
Uber caps employee AI coding tool spending at $1,500/month per tool to manage costs after overshooting its 2026 AI budget.
Explores the paradox of AI tools boosting productivity yet causing distraction, with personal anecdotes and ADHD perspectives.
Explores the paradox of AI tools boosting productivity while causing attention fragmentation and project overload.
A comprehensive overview of agentic coding tools in 2026, covering CLI agents, UI-based IDEs, autonomous agents, and model routers.
Explains why coding agents need architectural context via Architecture Decision Records (ADRs) and how to make them accessible.
Analysis of MiniMax M2 LLM technical report highlighting production-oriented design choices like full attention, fine-grained MoE, and agent training pipelines.
Explores a third approach to using coding agents: implementing backpressure mechanisms like tests and types to validate work before human review.
Explore three static code analysis sensors for maintainability in AI-assisted coding, covering linting, dependency rules, and coupling data.
Explores how coding agents boost productivity but require strong technical skills to use effectively, debunking the myth that AI replaces developers.
Explores the challenges of using local AI models for coding agents, focusing on usability gaps like tool parameter streaming.
