Search Articles

Found 15 results for "reasoning-protocols"

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.

January 27, 202610 min read

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

🔮

🔮Vibe Coding

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.

January 9, 20268 min read

#vibe coding#AI development#design systems

🔮

🔮Vibe Coding

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.

January 16, 202611 min read

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

🔮

🔮Vibe Coding

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.

January 6, 202611 min read

#LLM limitations#compounding error#AI hallucinations

🔮

🔮Vibe Coding

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.

January 15, 20269 min read

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

🔮

🔮Vibe Coding

Temperature Sensitivity in LLM Code Generation: A 752-Run Experiment

We tested how temperature (0, 0.3, 0.7, 1.0) affects code generation accuracy on 100 competitive programming problems. The surprising result: temperature barely matters for problem-solving, but model selection does.

January 25, 202610 min read

#vibe coding#LLM temperature#Gemini

🔮

🔮Vibe Coding

Attention Mechanisms in LLMs: The Complete Guide to How Transformers Really Work

Learn how attention mechanisms power large language models (LLMs) like GPT-4 and Claude. This in-depth guide explains Query-Key-Value math, multi-head attention, and long-context processing with real code examples.

January 6, 202612 min read

#attention mechanisms#transformers#LLM

🔮

🔮Vibe Coding

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.

January 6, 202610 min read

#LLM hallucination#AI generation#confabulation

🔮

🔮Machine Learning

Gradient Descent: The Workhorse of Machine Learning

Learn how gradient descent optimizes machine learning models by iteratively minimizing the loss function.

December 22, 202513 min read

#machine-learning#optimization#neural-networks

🔮

🔮Vibe Coding

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.

January 6, 20266 min read

#vibe coding#AI programming#LLM

🔮

🔮Vibe Coding

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.

January 14, 202612 min read

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

🔮

🔮Vibe Coding

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.

January 6, 20269 min read

#LLM#token generation#feed-forward

💻

💻Tech Skills

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

🔮

🔮Vibe Coding

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.

March 14, 202615 min read

#vibe coding#TypeScript#LLM code generation

🔮

🔮Vibe Coding

The LLM Collaboration Guide: How to Avoid 20 Critical Bugs in Production

Learn how to turn LLMs from a liability into your most powerful engineering tool. Discover the three-phase workflow, constraint matrix framework, and production readiness checklist that prevents critical bugs in production.

March 12, 202624 min read

#LLM#AI-Assisted Code#Production