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CrewAI Tools: Building Custom Agents & Tool Integration (Guide)

Complete guide to building tools for CrewAI agents. Learn @tool decorator, tool creation, built-in tools, and multi-agent workflows.

March 1, 202616 min read

#crewai#ai-agents#llm

January 9, 20268 min read

Screenshot-to-Code vs. Specs-Driven Development: The 2026 Design Handoff Evolution

A real-world experiment reveals the profound gap between AI visual approximation and production-ready code. Learn why context pipelines are the future of design-to-code workflows.

#vibe coding#AI development#design systems

January 21, 202615 min read

Few-Shot Prompting for STEM: Claude vs Gemini Across 128 Experiments

We ran 128 experiments comparing Claude Sonnet 4 and Gemini 2.0 Flash on STEM problems with zero-shot through 5-shot prompting. The results challenge common assumptions: accuracy stayed flat while format consistency and token efficiency improved dramatically.

#few-shot prompting#STEM education#prompt engineering

#nextjs#performance#optimization

Next.js Bundle Analyzer: Optimize Your Build Size

Learn how to use @next/bundle-analyzer to visualize and optimize your Next.js bundle size. Includes real optimization examples and case studies.

March 1, 202614 min read

February 5, 202612 min read

The Full Papercut Audit: Where AI Coding Tools Break Down

A comprehensive friction analysis across five dimensions: bracket completion, comment verbosity, over-engineering, multi-file projects, and iterative modification. Gemini CLI achieves perfect zero friction.

#ai-coding#claude-code#codex-cli

March 14, 202615 min read

Why LLM-Generated Code Accumulated 172 TypeScript Errors: A Technical Deep Dive

During a large-scale refactoring, we discovered 172 hidden TypeScript errors from LLM-generated code. This wasn't random—it revealed systematic patterns in how AI handles legacy removal, type inference, and build configurations. Learn the root causes and how to prevent them.

#vibe coding#TypeScript#LLM code generation

January 6, 20266 min read

Vibe Coding: Master AI-Assisted Programming with LLM Probability

Learn what vibe coding is, how LLM probability powers AI-assisted programming, and master the skills for the future of coding. Practical examples included.

#vibe coding#AI programming#LLM

February 5, 202612 min read

The Flow-State Experiment: Measuring Papercuts in AI Coding Tools

A systematic comparison of Claude Code, Codex CLI, and Gemini CLI measuring the small friction points that disrupt developer flow. Our experiments reveal fundamental differences in how these tools handle mid-task corrections and context.

#ai-coding#claude-code#codex-cli

January 14, 202612 min read

The Hidden Cost of "Ship It Fast": When Velocity Becomes Technical Debt

A post-mortem on vibe coding—the practice of prioritizing momentum over maintainability. Learn why shipping fast without foundations is the most expensive shortcut you'll ever take, and how to recover.

#vibe-coding#technical-debt#software-engineering

January 15, 20269 min read

XML vs Natural Language Prompts: An Experimental Comparison

We tested XML-structured versus natural language prompts across 144 experiments spanning code generation, mathematics, reasoning, and complex multi-step tasks. The results reveal significant efficiency gains—but with important caveats.

#vibe-coding#prompt-engineering#XML-prompts

#Git#Version Control#DevOps

Git Advanced Workflows: Rebasing, Cherry-Pick & Flow (Complete Guide)

Master Git rebase, cherry-pick, git flow, maintain clean history, prevent merge disasters in production.

March 7, 20268 min read

#architecture#design-patterns#messaging

Pub/Sub Architecture: A Complete Guide to Publish-Subscribe Pattern

Master the pub/sub messaging pattern with real-world examples, implementation guides, and comprehensive tutorials for distributed systems.

March 1, 202626 min read

January 16, 202611 min read

Testing LLM Reasoning on Novel Problems: What 400 Experiments Reveal

We ran 400 experiments on competitive programming problems LLMs have never seen before. The results reveal that when memorization is eliminated, prompt formatting matters far less than model selection.

#vibe-coding#LLM-benchmarks#novel-problems