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Nomination created on September 29, 2026

Reproducible bugs are candies.

Software engineering at Big Tech and startups, from the inside. Deepdives with experienced engineers and tech professionals who share their hard-earned lessons, interesting stories and advice they have on building software. Especially relevant for software engineers and engineering leaders: useful for those working in tech. newsletter.pragmaticengineer.com
Salvatore Sanfilippo (antirez), the creator of Redis, is one of the most closely followed engineers in the systems world, and his move away from X left a lot of listeners unsure where to keep reading him. Listing his Bluesky handle on the episode page turns a one-off interview into an ongoing follow, giving The Pragmatic Engineer's audience a direct, low-noise channel to a builder whose writing on craft and complexity is the reason many of them listened in the first place. For a show whose value is practitioner-level depth, pointing listeners to the place where the guest actually posts is a small but concrete piece of usefulness.
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Sep 29, 2026
🚀 Nomination created: Salvatore Sanfilippo (antirez) wrote Redis and has spent the years since publishing unusually candid essays on software craft, AI tooling, and what makes engineers productive — exactly the ground The Pragmatic Engineer covers from the inside.
Sep 29, 2026
📡 Why now: Redis's licensing reversals — source-available in 2024, an open-source option restored with Redis 8 in 2025 — pushed the question of who controls critical infrastructure back into engineering feeds, and the person who started the project is rarely heard on it.
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I claim that if you are a normal person that like me don't have "fuck you money", so unable to spend large sums of money randomly, you should do all your programming work with two max accounts (OpenAI / Anthropic for instance) in the worst case, and never buy tokens via API.
The most ridiculous thing about the AI-coding age is that in the last 20 years programmers accepted otherwise all the kind of shit: terrible frameworks, languages, layers of complexity everywhere, everything super slow. Very very few protested, since destroying the field didn't
Don't look at generation tokens per second as the main metric for local inference. Soon Cinese open model providers will realize that the game is all about making the thinking phase as short as possible, and 20/30 t/s will be enough if you have fast prefill.


Which open-source project would you build today that was previously impractical for one person, and what changed: implementation cost, the ability to test it, or something else?
Open-source projects that AI makes practical for a small team: walk through one concrete project, from scope and design to testing, release, and long-term maintenance.
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Which of his projects does he consider the most underrated?
Beyond Redis, there's a long tail of experiments, tools, and half-finished ideas. Ask him which one he'd want people to look at again — and which one he'd rather forget.