LLMOps Operationalizing Large Language Models for the Real World

LLMOps Operationalizing Large Language Models for the Real World

Transcript

1. LLMOps Operationalizing Large Language Models for the Real World
2. Hello! I’m Raj 😊 I ❤ to design & develop modern software
3. About me Rajkumar Sakthivel (Raj) Senior Pro Dev @ Tesco Technology Founder @ tessellit_uk @rajkumarsakthi
4. LLMOps Operationalizing Large Language Models for the Real World
5. AI Disaster
12. Cost
14. Real-World Challenges
15. Hallucinations & Safety
16. Cost Management
17. Model Drift
18. Security
19. Best Practices
20. RAG Workflow Rule 1: Start with RAG & Fine tune later
21. Prompt Versioning: Rule 2: Treat prompts like code diff tool showing how changing ‘Summarize’ to ‘TLDR’ boosted accuracy
22. GPU Optimization: Rule 3: Right-size GPUs Use A100s for training, T4s for inference
24. LLMOps bridges the prototype-to-production gap. Start small, monitor obsessively, and never trust an LLM alone with customers.
25. Any Questions? 😊