AI Engineering
The discipline of building reliable AI products.
AI engineering is the discipline of building software powered by AI — choosing and adapting models, engineering prompts and context, evaluating and testing, and shipping LLM features that hold up in production. Distinct from using AI to write code (that is AI coding) and from the research of training models from scratch.
6 episodes
- Explaining Eval Engineering | Galileo's Vikram Chatterji
- Architecting AI Agents: The Shift from Models to Systems | Aishwarya Srinivasan
- Mindset Over Metrics: How to Approach AI Engineering | Hamel Husain
- Using AI to Modernize Your Legacy Applications | MongoDB’s Rachelle Palmer
- AI in 2025: Agents & The Rise of Evaluation-Driven Development
- AI in 2025: Agents & The Rise of Evaluation Driven Development
Explainers on this topic
- 4 Things That Turn a Model Into an Agent
- When AI Hallucinations Are Good (and When They're Dangerous)
- Small Language Models in Production
- How to Test an AI System
Terms on this topic
- Fine-Tuning
- Knowledge Distillation
- LoRA (Low-Rank Adaptation)
- RLHF (Reinforcement Learning from Human Feedback)
- Temperature
Guests on this topic
Vikram ChatterjiAishwarya SrinivasanHamel HusainRachelle PalmerAndrew ZiglerYash ShethAtindriyo Sanyal