Peter Sobot

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Peter Sobot

Peter Sobot

@psobot

research engineering lead @Spotify 🇨🇦🎶👨🏼‍🔬🥁🎹🎸

Brooklyn, NY Katılım Ocak 2009
2.6K Takip Edilen3.8K Takipçiler
Peter Sobot
Peter Sobot@psobot·
my friends back in canada: "why do you use amazon so much in the states? doesn't it suck?" here are the top two results for the same exact search query on .com and .ca
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Peter Sobot
Peter Sobot@psobot·
@cursor_ai is my favourite AI coding tool, full stop. Huge fan. But I have never seen a product play so fast and loose with remapping commonly-used keyboard shortcuts.
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siddharth ☻
siddharth ☻@siddharthkp·
staff/senior engineer thought:
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Peter Sobot
Peter Sobot@psobot·
@skooookum it’s really good. even with the rough edges in the UI, I’m still way way more productive with it than any other harness
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Peter Sobot
Peter Sobot@psobot·
After 15 years, I just got rid of my last Drobo product. I saved up for a used original Drobo in 2011, and just today retired my Drobo 5N and gave it to a friend. I still think about Drobo regularly - it was innovative technology deployed really well, and with style. Disks were expensive back then ($150/TB adjusted for inflation!) and people wanted to buy an extra terabyte at a time instead of having to do a big migration every time they needed more storage. It was perfect for consumers who were price-sensitive enough that buying bigger and bigger drives was not an option, but buying an elastic NAS was still within their price range. If you had less money, you couldn't afford one. But if you had *more* money, you had no need for a Drobo. Why spend $500 on an elastic NAS that could scale to 40TB when a single 20TB drive only cost $600 in 2020? Not to mention the rise of cloud storage and its plummet in price, the rise of high-efficiency media compression, etc. Every time I think about building a new product, I remember Drobo. Technically solid, elegantly built, impressively designed, but useful for only a tiny subset of users for about a decade.
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Charlie Marsh
Charlie Marsh@charliermarsh·
Average ty side project, from @sharkdp86: "just a reinterpretation of gradual types as k-faces in the N-dimensional hypercube of static materializations"
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Mark Worrall
Mark Worrall@infinitehumanai·
Reminds me of Peter Naur's classic 1985 essay "Programming as Theory Building" which argues that a program is not its source code. A program is a shared mental construct (he uses the word theory) that lives in the minds of the people who work on it. If you lose the people, you lose the program. The code is merely a written representation of the program, and it's lossy, so you can't reconstruct a program from its code. If you think of total software debt as technical debt + cognitive debt, then previously, we mostly had technical debt. Now with AI we have both. Previously, when you built something, you accumulated technical debt but relatively little cognitive debt because you had to understand what you were building in order to build it. In other words: the theory came for free as a byproduct of the work. AI breaks that coupling. Now you can produce code without building the theory. So you're now able to accumulate both kinds of debt simultaneously - technical debt in the code and cognitive debt in yourself. And cognitive debt is arguably worse because you can fool yourself into believing it doesn't exist. Technical debt tends to show up in semi-obvious ways that we understand well as an industry. Cognitive debt is more insidious - it means you're unable to even reason about the program (because you possess no theory of it) - which is what Naur describes as the "death" of a program.
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Peter Sobot
Peter Sobot@psobot·
(On that topic, @projection_lab is amazing and cannot be beat by a couple hours of Claude use)
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Peter Sobot
Peter Sobot@psobot·
One of the biggest dangers of using AI agents to "just write this quick tool for me" is that it'll get you 90% of the way there after a couple of hours; when you could have instead spent those hours using a much better tool that someone else has already created.
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Rohan Paul
Rohan Paul@rohanpaul_ai·
Powerful new Harvard Business Review study. "AI does not reduce work. It intensifies it. " A 8-month field study at a US tech company with about 200 employees found that AI use did not shrink work, it intensified it, and made employees busier. Task expansion happened because AI filled in gaps in knowledge, so people started doing work that used to belong to other roles or would have been outsourced or deferred. That shift created extra coordination and review work for specialists, including fixing AI-assisted drafts and coaching colleagues whose work was only partly correct or complete. Boundaries blurred because starting became as easy as writing a prompt, so work slipped into lunch, meetings, and the minutes right before stepping away. Multitasking rose because people ran multiple AI threads at once and kept checking outputs, which increased attention switching and mental load. Over time, this faster rhythm raised expectations for speed through what became visible and normal, even without explicit pressure from managers.
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sudara
sudara@sudara·
razzle dazzle
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Peter Sobot
Peter Sobot@psobot·
reminder: only 10 days away. we can make it.
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Peter Sobot
Peter Sobot@psobot·
@bernhardsson Really good post - but please tell me this was an intentional easter egg? 😅
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Erik Bernhardsson
Erik Bernhardsson@bernhardsson·
I just published this blog post about software companies buying more software and all its corollaries: SF being back, tech layoffs, revenue going up but margins going down, and much more: erikbern.com/2026/02/25/sof…
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Peter Sobot
Peter Sobot@psobot·
is the big bad AI going to take all of our jobs or is it just cold and dark and February and we’re all spending too much time on computer
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skooks
skooks@skooookum·
Software engineering will only become more lucrative for those who love software engineering. We're experiencing a Tower of Babel moment, barbarians at the gate, so forth. The future of the profession belongs to those who loved the game before they invented the slop cannon.
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Nathan Lawrence 🌈
Nathan Lawrence 🌈@NathanBLawrence·
Almost everyone goes on this journey: 1. "These are useless" 2. "These are interesting" 3. "I am getting more productive" 4. "I am bored and need to use 2 of these at once" 5. "I run an army of these robots, and if you don't, skill issue, you are NGMI" 6. "Wait, WTF is this code?" 7. "I was fooling myself, clarity of intent is the real bottleneck"
Marcin Krzyzanowski@krzyzanowskim

my productivity skyrocketed when I stopped setup agents and started to write code again like a normal fucking human being

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