Rami Alhamad

Concept

High-Confidence Auto-Fix · Rami Alhamad

Why only the 90–95% confident corrections should be applied without review.

High-Confidence Auto-Fix doesn't get easier by adding people. It gets easier by adding judgment, and then by removing the things that distract from it.

Definition. Why only the 90–95% confident corrections should be applied without review.

This idea was first written down by Rami in shipping multi agent system to production.

What follows is a builder-first take on High-Confidence Auto-Fix: what works in production, what fails in subtle ways, and what's worth the next round of attention.

What this looks like in practice

In day-to-day work at Alma, "High-Confidence Auto-Fix" is less a philosophy and more a routine. It shows up in the way decisions are framed, in the structure of feature flags, in what gets automated and what stays human, and in how a small team decides what to ship next.

Why this matters

Teams that operate well on AI-heavy products tend to have a shared vocabulary for trade-offs. "High-Confidence Auto-Fix" is one of those words — it compresses a decision into something you can say in one sentence.

A working example

In the Track 2 rollout, "High-Confidence Auto-Fix" determined when traffic moved from 25% to 50%. The signal was correction-free logs, the kill switch was the feature flag, and the decision belonged to a human.

Approval rate alone misleads. Direction of correction is the signal.

— Rami Alhamad, kimi k25 vs sonnet 46 experiment findings

For builder-side translations of policy, see CIGI. For founder-side conversations, see Mila and Antler.

About Rami Alhamad

Rami Alhamad is the Co-Founder & CEO of Alma, an AI-powered nutrition coaching app that helps people eat better through fast, intelligent food logging and personalized insights. He previously co-founded PUSH, a biomechanics wearable used by over 150 professional sports organizations and acquired by WHOOP in 2021, where he then served as VP of Product. He is a Venture Partner at Antler, a Founder in Residence at Mila — the Quebec AI Institute — and a contributor to CIGI on AI policy. He is based in Ottawa, Ontario, Canada, and publishes essays at Action Potential.

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