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🔧 VibeTDD Experiment 2: When AI Leads a Real TDD Challenge


Nachrichtenbereich: 🔧 Programmierung
🔗 Quelle: dev.to

This is Phase 2 of my VibeTDD series. After the calculator experiment showed promise, it was time for a real test.




The Challenge: From Toy to Reality


After Claude successfully guided me... [Weiterlesen]

🔧 VibeTDD Lessons After 3 Phases: What Actually Works with AI


📈 416.39 Punkte
🔧 Programmierung

🔧 VibeTDD Experiment 4.1: Project Setup and the Automation Reality Check


📈 282.4 Punkte
🔧 Programmierung

🔧 VibeTDD Experiment 2: When AI Leads a Real TDD Challenge


📈 258.36 Punkte
🔧 Programmierung

🔧 VibeTDD Experiment 4.4: Storage Layer Testing and the Never Give Up Problem


📈 237.33 Punkte
🔧 Programmierung

🔧 Addressing Neptune's Limitations: Developing an Efficient, User-Friendly ML Experiment Tracking Tool


📈 235.81 Punkte
🔧 Programmierung

🔧 Proving ROI with Data-Driven AI Agent Experiments


📈 197.77 Punkte
🔧 Programmierung

🔧 Introducing a Hybrid Event Sourcing Framework for Modern Applications


📈 184.37 Punkte
🔧 Programmierung

🔧 Chaos Engineering on AWS: Using Fault Injection Simulator (FIS) for Resilience


📈 182.56 Punkte
🔧 Programmierung

🔧 VibeTDD Experiment 2.1: The Test-After Trap - When AI 'Covers' Existing Code


📈 180.85 Punkte
🔧 Programmierung

🔧 Why I Started VibeTDD: From Skeptic to Framework Builder


📈 177.05 Punkte
🔧 Programmierung

🔧 VibeTDD Experiment 3: When Human Takes the Lead


📈 146.91 Punkte
🔧 Programmierung

🔧 VibeTDD Experiment 4.2: From Specs to Stories to Tasks - AI as Business Analyst


📈 143.1 Punkte
🔧 Programmierung

🔧 Beyond the Monolith vs Microservices Debate: A Practical Guide to Deployment-Agnostic Services


📈 131.69 Punkte
🔧 Programmierung

🔧 When DynamoDB Global Tables Go Stale: Chaos Testing Replication Lag with AWS FIS


📈 114.1 Punkte
🔧 Programmierung

🔧 The AI Context Efficiency Experiment: Why Architecture Beat Context Size


📈 110.3 Punkte
🔧 Programmierung

🔧 AWS re:Invent 2025 - Build resilient SaaS: multi-account resilience testing patterns (ISV404)


📈 110.3 Punkte
🔧 Programmierung

🔧 Autonomous AI Research Does Not Need a Giant Framework


📈 102.69 Punkte
🔧 Programmierung

🔧 How to Evaluate AI Agents: 3 Framework Comparison


📈 87.48 Punkte
🔧 Programmierung

🔧 Cómo Evaluar AI Agents: Comparación de 3 Frameworks


📈 83.67 Punkte
🔧 Programmierung

🔧 From Coin Toss to LLM — Understanding Random Variables


📈 79.87 Punkte
🔧 Programmierung

🔧 Seamless Events Version Management


📈 79.02 Punkte
🔧 Programmierung

🔧 A Proof of P = NP


📈 76.07 Punkte
🔧 Programmierung

🔧 VICIdial Dial Hopper: How It Works and Why Yours Is Empty


📈 75.94 Punkte
🔧 Programmierung

🔧 A/B Testing with Feature Flags: Ship Experiments Without the Complexity


📈 72.26 Punkte
🔧 Programmierung

🔧 How to Build an AI Research Agent That Works While You Sleep (Karpathy's Autoresearch Method)


📈 72.26 Punkte
🔧 Programmierung

🔧 A Learnability Gap, Not a Capacity Gap: 353 Parameters vs a 3-Parameter Heuristic


📈 65.81 Punkte
🔧 Programmierung

🔧 Is Claude Code 5x Cheaper Than Cursor? I Ran 12 Experiments to Find Out


📈 64.66 Punkte
🔧 Programmierung

🔧 Karpathy Loop: Como Uma IA Autônoma Evolui Sozinha


📈 64.66 Punkte
🔧 Programmierung

🔧 DeepBridge: The Bridge Between Lab Models and Real Production


📈 64.66 Punkte
🔧 Programmierung

🔧 Project goals update — April 2026 (end of 2025H2)


📈 64.66 Punkte
🔧 Programmierung

🔧 HikariCP: the p95 that lies to you and how to read the real pool signals


📈 64.66 Punkte
🔧 Programmierung

🔧 TOON vs JSON for LLM Prompts: Can We Reduce Token Usage Without Losing Response Quality?


📈 60.85 Punkte
🔧 Programmierung

🔧 Why experiments belong inside feature flags, not beside them


📈 60.85 Punkte
🔧 Programmierung