Building scalable AI agents with modular prompt transpilation- Google Developers Blog
Jul 16, 2026Simerus Mahesh

Summary
This post introduces a novel approach to AI agent development by treating prompts as build artifacts rather than static text. It proposes modular prompt transpilation, enabling developers to break down complex agent instructions into smaller, manageable skill files. This facilitates better collaboration, testing, and CI/CD integration by applying software engineering principles like dependency management, static validation, and drift checking to AI agent prompts. The post also highlights the potential for agents to contribute to their own instruction layer through proposed code changes.
More from the Google Developer Platform trail
- Autonomous LLM post-training with Tunix on TPUs- Google Developers Blog
- HeyGen x Google Cloud: Bringing Avatar IV to TPUs- Google Developers Blog
- Run Ray on TPU, Part 2: Ray AI libraries- Google Developers Blog
- Scaling Agentic RL: High-Throughput Agentic Training with Tunix- Google Developers Blog
- Run Ray on TPU, Part 1: The foundations- Google Developers Blog