A publication for people who have to make AI actually work
Supasifu covers applied AI. Not the discourse, not the funding theatre — the part where somebody has to ship a system, justify its cost, and explain to a room of skeptical people why it is better than what came before.
Five columns, written by two people who deploy AI inside enterprises for a living — the platform underneath it, the money around it, and the research about to change both. Everything here comes from someone still in the room when the thing breaks.
What we promise
- No hype tax. If a release changes nothing for you, we say so.
- Show the work. Benchmarks come with the method and the failures.
- Something to do. Every piece ends with a step you can take this week.
Write for us
Supasifu commissions from practitioners. If you have shipped something and can explain what it cost you, pitch hello@supasifu.com with three sentences: what you built, what surprised you, and who needs to read it.
Who writes it
Francis Kwan
Writer · finance and research
Francis writes for Supasifu on the money and the research behind enterprise AI. He works on AI deployments in finance, and covers what the numbers say about the build-out — cost, return, and capital — alongside the papers and model results that are about to change what any of it is worth.
Tim Cheung
Editor · platform and adoption
Tim edits Supasifu and has spent his career deploying AI inside enterprises. He writes about the platform engineering underneath it — the pipelines, evals, and guardrails that decide whether a system survives contact with production — and about onboarding: how you get a whole organisation using AI without breaking how it already works.
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