Agent Loops in ML Engineering: Liquid AI's Vibe-Coded Tokenizer Trainer

Melvin Vivas · X post · 2026-08-19 · Open on X

Topics: AI Agents, Tool Use & MCP, AI Dev Tools & Productivity · Level: advanced

Summary

The creator shares a Liquid AI engineering blog post as the "ML version" of loop engineering. The post explains how Liquid AI's teams use agent loops, and what they learned from vibe-coding a tokenizer trainer that they now use in production.

Key points

• Loop engineering means running a coding agent in iterative loops to build and refine software.
• Liquid AI applied agent loops to ML infrastructure: a tokenizer trainer.
• The vibe-coded tokenizer trainer is actually used in production at Liquid AI.
• The blog post covers lessons learned from using loops in their engineering teams.

Resources mentioned

• Liquid AI blog: how our engineering teams use agent loops · article · liquid.ai · free
  Liquid AI's engineering blog post on using agent loops and the lessons from vibe-coding a production tokenizer trainer.
• Liquid AI (@liquidai) on X · website · x.com · free
  An AI company that builds efficient foundation models. The quoted post shows its PII handling working on Japanese text.
  Also in: Zero-Shot Prompt Routing with Liquid AI's LFM 2.5-Encoder-350M (Melvin Vivas on X · notes), Liquid AI LFM 2.5 Encoder: a CPU-friendly encoder model (Melvin Vivas on X · notes), Fine-tuning Liquid AI LFM2/LFM2.5 MoE models with the new Halo framework (Melvin Vivas on X · notes), Liquid AI's LFM2-Longevity models for aging-data analysis (Melvin Vivas on X · notes) and 19 more

Try this

• Read Liquid AI's agent loops blog post. The link is cut off, so find it on liquid.ai/blog.
• Use an agent loop to vibe-code a small ML tool, such as a tokenizer trainer.