Building A Generative AI Platform
Source: https://huyenchip.com/2024/07/25/ai-engineering.html Author: Chip Huyen Date: 2024-08-10
Summary
Chip Huyen’s guide to the engineering infrastructure needed for production generative AI systems. Covers the full stack: model serving, evaluation pipelines, guardrails, monitoring, and cost management.
Key Claims
- Platform layers: (1) model serving, (2) orchestration, (3) evaluation, (4) guardrails, (5) data pipelines, (6) monitoring.
- Orchestration is underrated: the logic of how you chain model calls, route requests, and handle retries determines product quality.
- Evaluation is non-negotiable: you cannot ship a gen AI product without an eval pipeline — but most startups skip it.
- Cost structure: model calls dominate at first, then retrieval, then infra. Design for each stage.
- Guardrails are a system, not a prompt: safety requires dedicated models, not just careful prompting.
- The “good enough” problem: gen AI outputs are probabilistic — define what “good enough” means before building.
Entities
- Chip Huyen — ML systems author
Concepts
- Coding Agents — platform as substrate for agents
- Context Engineering — orchestration = context management at platform level