How Together AI Uses AI Agents to Automate Complex Engineering Tasks: Lessons from Developing Efficient LLM Inference Systems

This post details six patterns for building AI agents to automate complex engineering tasks: Infrastructure Patterns (Good Tools, Documentation, Safe Execution) and Behavioral Patterns (Manage Parallel Sessions, Manage Wait Time, Progress Monitoring). It provides a case study on using these patterns to automate the training pipeline for speculator models, a key technique for accelerating LLM inference. The post highlights how these agents reduce manual intervention, improve consistency and reliability, and decrease turnaround time for developing efficient LLM inference systems.