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Top 5 · 2026-05-12 · source-backed
Shopify built an internal coding agent called River. It generates over half the company's code. And it won't talk to you in private.
That last part is the interesting bit. River operates exclusively in public Slack channels, refusing DMs entirely. Every prompt, every response, every mistake is searchable by anyone at the company. Tobias Lütke designed it this way on purpose, turning the tool into an organizational learning system. When a senior engineer figures out how to prompt River for a tricky data migration, that conversation becomes institutional knowledge. When a junior engineer writes a bad prompt and gets garbage back, that's visible too.
The data coming out of Shopify's deployment challenges something I've heard repeated at every AI conference this year: that AI tools are "the great equalizer" for junior developers. Shopify CTO Mikhail Parakhin told the Latent Space podcast that senior engineers with thousands of problem-solving repetitions are significantly better at prompting River than newer employees. AI amplifies experience. It doesn't replace it.
Parakhin also dropped this: Shopify now spends more on AI review than AI generation. They hit 100% workforce AI adoption with an unlimited Opus 4.6 token budget, and the lesson was that raw generation speed wasn't the bottleneck. Critique quality was. He defended Jensen Huang's "measure engineers by token spend" stance as "directionally correct" but stressed that quality controls matter more than volume.
I think about this a lot in my own work. I use Claude Code every day in my personal projects, and the difference between a good session and a wasted hour is almost never the model's capability. It's whether I set up the problem correctly. Experience compounds when you're orchestrating AI, just like it does when you're writing code by hand.
For engineering leaders: the public-by-default pattern is worth stealing. Most organizations treat AI tool usage as individual productivity. Shopify treats it as collective learning. The org design decision matters more than the model choice. If your engineers are all prompting in isolation, you're leaving the best part on the table.
Each link below shares sources, entities, or timing with this story.
Shopify released River / Shared entities / Same source / Shared topic / Earlier coverage
Linked by a graph relationship (Shopify released River); both cover Latent Space, Most, Opus, Parakhin; cite the same source (Latent Space podcast).
Linked by a graph relationship (Shopify released River); both cover Latent Space, Opus, Parakhin, Shopify; cite the same source (Latent Space podcast).
Shopify released River / Shared entities / Same source domain / Shared topic / What happened next
Linked by a graph relationship (Shopify released River); both cover DMs, River, Shopify, Slack; reported by the same outlet (simonwillison.net).
Shopify released River / Shared entities / Shared topic / What happened next / Tension
Linked by a graph relationship (Shopify released River); both cover Claude Code, Opus, Shopify, When; overlapping topics (agent, prompt, tool).
Cursor uses Opus / Shared entities / Same source domain / Shared topic / Earlier coverage
Linked by a graph relationship (Cursor uses Opus); both cover Claude Code, Latent Space, Opus; reported by the same outlet (latent.space, simonwillison.net).
Cursor uses Opus / Shared entities / Shared topic / What happened next / Tension
Linked by a graph relationship (Cursor uses Opus); both cover Claude Code, Most, Opus, When; overlapping topics (agent, code).
Claude Code uses Opus / Shared entities / Same source domain / Shared topic / What happened next
Linked by a graph relationship (Claude Code uses Opus); both cover Claude Code, Opus, When; reported by the same outlet (simonwillison.net).
Linked by a graph relationship (Claude Code uses Opus); both cover Claude Code, Latent Space, When; reported by the same outlet (latent.space).