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#Python#Type Safety#Pydantic

Python Type Hints & Pydantic: Runtime Validation (Complete Guide)

Master Python type hints, Pydantic validation, catch runtime errors at input, prevent 70% of production bugs.

March 7, 20267 min read

#LLM#AI-Assisted Code#Debugging

The Silent Failure Cascade: Why LLM-Powered Code Breaks in Production

LLM-generated code often fails silently in production due to implicit assumptions. Learn why this happens, how to detect it, and proven strategies to write defensive code that survives the real world.

March 7, 202612 min read

#TypeScript#JavaScript#Type Safety

TypeScript Advanced Types: Generics, Discriminated Unions & Mapped Types

Master TypeScript advanced types, generics, conditional types, and build bulletproof type-safe applications.

March 7, 20269 min read

LangChain Output Parsers: Parse LLM Responses (Complete Guide)

Master LangChain output parsers for structuring LLM responses. Learn about StrOutputParser, PydanticOutputParser, and custom parsers.

March 1, 202616 min read

#langchain#llm#ai

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

February 5, 202610 min read

The Idiomatic Code Audit: Do AI Tools Write Modern Code?

Testing whether Claude Code, Codex CLI, and Gemini CLI produce modern, idiomatic, and secure code by default. Our experiments reveal a critical gap in library version awareness.

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

January 6, 202611 min read

Why LLMs Fail at Complex Tasks: The Math Behind Compounding Error in AI Code Generation

Learn why LLMs fail on long reasoning chains due to compounding error. Includes mathematical proofs, real-world AI coding failures, and actionable engineering strategies to mitigate AI hallucinations in software development.

#LLM limitations#compounding error#AI hallucinations

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 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 6, 20269 min read

Why LLMs Can't Revise Tokens: The Feed-Forward Constraint Every Developer Must Understand

Learn why LLMs hallucinate and can't self-correct. Understand feed-forward token generation and master vibe coding strategies for better AI-assisted development.

#LLM#token generation#feed-forward

#JavaScript#Async#Promises

JavaScript Promises vs Async/Await: Master Async Code (Complete Guide)

Master JavaScript promises and async/await, parallelize operations, speed up code 3x, handle errors correctly.

March 7, 20267 min read

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

#javascript#es6-features#strings

JavaScript Template Literals: String Interpolation & Multiline Strings

Master JavaScript template literals for string interpolation and multiline strings. Includes tagged templates, examples, and best practices.

March 1, 202614 min read

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

AWS Lambda & Serverless: Scale Without Servers (Complete Guide)

Master AWS Lambda, build serverless applications, scale to 1M requests/month for $2/month instead of $500/month.

March 7, 20267 min read

#AWS#Serverless#Lambda

January 27, 202610 min read

Can You Teach an AI How to Think? Testing Elaborate Reasoning Protocols on Claude Code

We gave Claude Code a 365-line protocol teaching it to think like an ICPC World Finalist. After 300 experiments, the elaborate methodology provided zero improvement over a simple "solve this problem" prompt—but the reasons why reveal something important about agentic AI.

#vibe-coding#Claude-Code#agentic-AI

January 6, 202610 min read

The Generative Core: Understanding Hallucination in Large Language Models

Hallucination isn't a bug in LLMs—it's the generative process itself. Understanding this changes how we should think about working with these tools.

#LLM hallucination#AI generation#confabulation

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

React Hooks: Master useEffect, useCallback & Custom Hooks (Complete Guide)

Master React hooks, eliminate memory leaks, optimize performance 100x, and build reusable hook libraries.

March 7, 202610 min read

#React#JavaScript#Hooks