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Mikhail Parakhin — Shopify's AI Stack

Source: transcript · Latent Space · Apr 2026.

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The December 2025 inflection. Shopify saw daily-active AI engineer usage approach 100% after a sharp December 2025 turn — small model improvements compounding into a threshold crossing. See shopify-ai-adoption-inflection. Parallels animals-vs-ghosts (Karpathy's framing that progress comes from accumulation, not single jumps) and corroborates agents-scale-not-fix.

Token budgets and the critique loop. Jensen is directionally right that engineers under-consume tokens, but raw count is wrong — tokens-need-critique-loop. Parallel agents that don't communicate are the anti-pattern; critic + author in dialogue is the minimum viable scaffold. Extends ai-generated-code-is-untrusted and do-not-outsource-thinking.

Tangle → Tangent → SimGym as a stack. tangle (reproducible workflows) unlocks tangent (auto-research loop) which unlocks simgym (customer simulation). auto-research-loop is the named primitive. Compounds only because Shopify has simulation-data-moat — years of merchant + buyer traces that calibrate the simulator away from prompt-confirmation bias.

PR review / git / CI-CD as bottleneck. Shopify's narrow-waist PR-review AI exists because code volume now exceeds human review throughput. Parakhin flags git + PRs + CI-CD as the top of mind bottleneck, echoing agents-scale-not-fix, pipeline-as-verifier, coding-agent-as-foundation.

Distill to small task model. distill-to-small-task-model + liquid-ai as the cost story — frontier models feed distillation loops into narrow 7-8B specialists for search, theme gisting, ucp-catalog, sidekick-pulse. Not running frontier in serving; using frontier as a teacher.

Sydney / personality shaping. Small but historically interesting: Sydney first shipped in India unnoticed, initially ran a Microsoft×NVIDIA Megatron model (not OpenAI), and the emergent personality was shaped deliberately — a counterpoint to the "accidental AI soul" mythology.

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