by teltam
AI models can handle routine tasks, but developers must retain ownership of critical thinking—effective Claude Code usage requires intentional context management, strategic prompting, and robust testing infrastructure.
by geoffrey-huntley
Understanding how coding agents work—tool calls, inferencing loops, the basic primitives—is now baseline knowledge for software engineering interviews, not optional curiosity.
by anthropic
Official documentation on Skills—markdown files that extend Claude Code with specialized knowledge and workflows, triggered automatically based on semantic matching.
by worldofai
Claude Code 2.1 ships a massive feature set—skill hot-reloading, forked sub-agents, Chrome browser integration, LSP support, and async agents transform the terminal into a multi-threaded agent orchestration platform.
by alexander-opalic
Claude Code 2.1 collapses the distinction between skills, slash commands, and subagents—skills can now fork into isolated contexts and specify their own model, making them the single abstraction for agent orchestration.
by alexander-opalic
Claude Code 2.1 transforms skills from specialized knowledge containers into a unified automation abstraction—hot-reloading, forked contexts, lifecycle hooks, and agent specification make skills the default choice for extending Claude Code.
by zeframlou
A Claude Code plugin that phones you when the AI finishes a task, gets stuck, or needs a decision—enabling true asynchronous collaboration without constant monitoring.
by geoffrey-huntley
AI's perceived ineffectiveness stems from insufficient deliberate practice, not fundamental limitations—mastery requires the same intentional experimentation as learning a musical instrument.
by jediah-katz
Coding agents perform better when they pull context on demand rather than receiving everything upfront—files serve as a simple, future-proof abstraction for this dynamic retrieval.
by nuxt
Real-time accessibility auditing inside Nuxt DevTools catches WCAG violations during development rather than after deployment.
by u-similar-bid1784
Production-quality vibe coding requires strict CI/CD pipelines, git discipline, extensive planning, and expert oversight—code is 30% of the work, deployment and performance are the real challenges.
Resources for mastering Claude Code - from daily tips to advanced customization
by maggie-appleton
Language models will enable a new class of 'barefoot developers'—technically savvy non-programmers who build small-scale, personal software for their communities, and local-first should become the default infrastructure for this movement.
by peter-van-hardenberg
Ink & Switch's three-part vision: local-first software enables universal version control, which enables malleable software where users customize their tools without waiting for developers.
by aicodeking
Vibe Kanban is an open-source tool that lets you orchestrate multiple AI coding agents from a visual Kanban board, treating coding tasks as asynchronous jobs rather than blocking conversations.
by ado-kukic
A comprehensive guide compiling 31 daily Claude Code tips, progressing from foundational concepts to advanced patterns like subagents, skills, and SDK usage.
by ryan-peterman, boris-cherny
Boris Cherny, creator of Claude Code and former Meta principal engineer, shares how side projects, generalist thinking, and cross-org navigation shaped his career—plus insights on how AI tools are reshaping engineering productivity.
by carl-assmann
CLI tool that enables LLM conversations through markdown files in your preferred editor, storing chat history as readable documents.
by jesse-vincent
A skills library for Claude Code that provides structured workflows for AI-assisted development, including brainstorming, implementation planning, TDD, and debugging.
by alexander-opalic
A comprehensive breakdown of Claude Code's extensibility layers—MCP servers, CLAUDE.md files, slash commands, subagents, hooks, and skills—explaining when to use each component.
by lee-robinson
Lee Robinson reflects on how coding agents have surpassed his coding ability and shares four recommendations for software engineers adapting to 2026.
by steve-yegge
A distributed, git-backed graph issue tracker designed for AI coding agents, replacing markdown task lists with structured, dependency-aware workflows.
by alex-colvin
How to build a skill that searches past Claude Code conversations to find solutions to previously solved problems, leveraging the JSONL conversation history stored locally.
by scott-spence
Claude Code skills fail to auto-activate despite documentation claims; hook-based workarounds achieve only 40-50% reliability, so manual invocation remains the practical choice.
by andrej-karpathy
Andrej Karpathy's practical guide to using LLMs effectively: understanding them as lossy internet zip files, managing token windows, selecting models across providers, and leveraging thinking models for complex problems.
by steph-ango
Community-sourced patterns for combining Obsidian vaults with Claude Code: master context files, batch editing, backlink discovery, and metadata management.
by mark-winteringham
Practical guide to using generative AI for test design, synthetic data generation, and automation without the hype.
by tsvetan-tsvetanov
Quality foundations—testing, strict types, clean APIs—enable rapid AI-assisted development because features emerge naturally once verification loops exist.
by simon-willison
Simon Willison's comprehensive year-in-review analyzing how reasoning models, autonomous agents, and Chinese AI competition fundamentally reshaped the landscape in 2025.
A curated guide to optimizing AI-assisted development workflows with Claude Code
by humanlayer-team
Techniques for reducing context window waste in AI coding agents by suppressing verbose output from tests and builds, showing full details only on failure.
by microsoft
A systematic approach to providing AI agents with targeted project information through custom instructions, planning agents, and structured workflows to improve code generation quality.
Techniques for providing AI agents and LLMs with optimized context
by humanlayer-team
Guidelines for crafting an effective CLAUDE.md file, emphasizing brevity, universal applicability, and progressive disclosure to maximize Claude Code's instruction-following capacity.
by geoffrey-huntley
Coding agents require only 300 lines of code in a loop with LLM tokens - understanding these fundamentals transforms you from AI consumer to producer.
by mauricio-gomes
Using CLAUDE.md to give Claude Code persistent context about your personal knowledge base, preferences, and workflows.
by burke-holland
A custom VS Code chat mode that fixes GPT-4.1's tendency toward speed over thoroughness using todo lists, sequential thinking prompts, and forced web research.
by geoffrey-huntley
Software developers who fail to adopt AI tools will experience natural attrition—not mass layoffs—as their peers achieve 16x productivity gains and redefine baseline performance expectations.