Learning on the Shop floor

2026-05-11 · Source: Simon Willison's Weblog · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Emerging Technologies & Innovation · Depth: Intermediate, quick

Summary

Shopify has developed an internal coding agent tool named River, designed to foster a "Lehrwerkstatt" or teaching workshop environment. River operates exclusively in public Slack channels, declining direct messages and encouraging users to create public channels for collaboration. This ensures all conversations are searchable and accessible to anyone at Shopify, allowing over 100 people to observe, contribute, and learn from ongoing work. This approach facilitates "osmosis learning" by making work visible to the maximum extent, eliminating the need for formal curricula or training plans. The concept is likened to Midjourney's early success, where public Discord channels for prompt sharing accelerated user learning in a complex domain.

Key takeaway

For engineering leaders aiming to scale knowledge transfer and accelerate team learning, consider adopting a "Lehrwerkstatt" model. By deploying internal AI tools like Shopify's River that operate exclusively in public, searchable channels, you can cultivate an environment where collective problem-solving and skill development occur organically through observation and shared context, reducing reliance on formal training programs.

Key insights

Public, visible AI agent interactions foster organizational learning and knowledge transfer.

Principles

• Visibility drives learning by osmosis.
• Public interaction enhances collective intelligence.

Method

Deploy AI agents to operate only in public, searchable channels, encouraging open collaboration and observation among team members.

In practice

• Implement public-by-default AI agent interactions.
• Design tools for transparent, shared workspaces.

Topics

• Shopify
• River Coding Agent
• Lehrwerkstatt
• Osmosis Learning
• Public Collaboration

Best for: CTO, VP of Engineering/Data, Executive, Director of AI/ML, Software Engineer, AI Product Manager

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Editorial summary, takeaway, and curation by AIssential. Original article published by Simon Willison's Weblog.