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Found 12 results for "competitive-programming"

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

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🔮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

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🔮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

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🔮Vibe Coding

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

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🔮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

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🔮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

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🔮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

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🔮Vibe Coding

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

#LLM#AI-Assisted Code#Debugging

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🔮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

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💻Tech Skills

Python asyncio.gather(): Run Concurrent Tasks (Complete Guide)

Learn how to run multiple async functions concurrently with Python asyncio.gather(). Includes practical examples, error handling, and performance comparisons.

March 1, 202618 min read

#python#async-programming#concurrency

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💻Tech Skills

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

#architecture#design-patterns#messaging

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🔮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