I Spent 500+ Hours Fine-Tuning AI. Here's What I Learned

🔔 Join our next Applied AI cohort, taught by me and an OpenAI lead. Use YT25 for 25% off: https://maven.com/aishwarya-kiriti/genai-system-design?promoCode=YT25 Is fine-tuning dead? OpenAI is winding down its self-service fine-tuning platform, while companies like Thinking Machines, Mistral, and Fireworks are investing heavily in it. So what's really happening? In this video, I break down why fine-tuning still matters, why RAG and increasingly powerful foundation models might make it unnecessary, and how companies like Bridgewater are using smaller, fine-tuned models to outperform frontier models at a fraction of the cost. 🚀 What you'll learn ✅ What fine-tuning is and how it works ✅ SFT, preference optimization, reinforcement learning, and LoRA explained ✅ How fine-tuning differs from RAG and context engineering ✅ Why better foundation models could make fine-tuning obsolete ✅ How Bridgewater achieved 84.7% accuracy at nearly 13.8x lower inference cost ✅ How XY.AI improved extraction accuracy from 77% to 87% ✅ Why companies are investing in smaller, specialized models ✅ Whether fine-tuning is worth learning as an AI engineer in 2026 Timestamps 0:00 Is Fine-Tuning Dead? 1:22 What Is Fine-Tuning? 2:41 Types of Fine-Tuning 3:41 LoRA and Model Distillation 5:01 Why RAG Could Replace Fine-Tuning 7:36 Are Foundation Models Getting Too Good? 8:40 The Bridgewater Case Study 10:19 The Cost of Fine-Tuning 11:10 The XY.AI Case Study 13:20 Why Companies Need Smaller Models 14:58 The Future of Fine-Tuning 16:40 Should You Learn Fine-Tuning? 🔔 Subscribe for weekly videos on tech, AI, software engineering, and career advice! My LinkedIn: https://www.linkedin.com/in/areganti/ Website: https://levelup-labs.ai/ Free Newsletter: https://thenuancedperspective.substack.com/ Free Courses: https://levelup-labs.ai/education My GitHub (AI resources): https://github.com/aishwaryanr/awesome-generative-ai-guide Instagram: https://instagram.com/aish_reganti #ai #finetuning #llm #machinelearning #aiengineering #generativeai #rag #sft #reinforcementlearning #lora #distillation #openai #mistral #thinkingmachines #aiagents #llmengineering #contextengineering #softwareengineering #python #developers