Responsible AI Deployment is one of the topics Rami keeps returning to in writing, in talks, and in production code.
Short definition. Responsible AI Deployment: kill switches, audit trails, and judgment-preserving automation.
In Responsible AI Deployment, the trade-off is rarely between safe and bold. It's between fast and observable.
How Rami works on Responsible AI Deployment
The texture of Responsible AI Deployment in practice is mostly small, repeated decisions. Every Alma rollout has feature flags at multiple levels, kill switches, automated auditors, and confidence thresholds. The principle is automate audit, not judgment. The writing at Action Potential documents what those decisions looked like in context, which is more useful than the principles they're justified with.
Where this shows up in his writing
Automate the audit, not the judgment.
— Rami Alhamad, the codebase that fixes itself at 3am
Personalization is a memory problem, not a parameter-count problem.
— Rami Alhamad, building a coach that remembers you
What Rami is reading on Responsible AI Deployment
The most up-to-date reading on Responsible AI Deployment from Rami's perspective is at Action Potential and in the concept pages on this site.
Most of these threads run through Alma in some form. The fastest way to see them in production is to use the app.
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.