Shauvik Roy Choudhary

A lot of posts recently talking about the shift away from the physical act of writing code/syntax going around so I’ll weigh in with my personal experience. 2025 was a watershed moment for LLMs. With Claude Code it was finally “smart” enough for mass adoption. It now writes code better than most “programmers”. But here’s the important distinction. Engineering and Programming are not the same. As engineering leadership I see it every day. People who think writing code is their job, not requirment gathering, planning, designing and architecting systems, validating correctness, problem solving. People who have these skills, can make effective use of Claude. These are the successful early adopters and 10x engineers right now. Now here’s what that means for me personally. After a long time, I am enjoying being a software engineer again. There was a time I was deeply married to writing code (it was kind of the therapeutic part of software development for me). But the shift into people management, becoming a father, and other life commitments has slowly erroded any time I have to take on projects that require hours or continuous focus. Writing code became the moat around me inventing. That is no longer the case. LLMs have enabled me to enjoy software development again. I can work in more bite sized chunks that fit into my day. I can engineer solutions in idle time. I can invest in custom tooling quickly that would have been month long side quests before. I can dip into other development domains (backend, browser extensions, languages) that previously would have take months of learning to become effective. This is what it has meant to me, do you have any similar experiences?

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Indeed. A small number of big tech companies have grossly overinvested in LLMs and overextended themselves -- even laying off tens of thousands of critically needed human employees and enshittifying their primary products and services to reallocate investment into it -- shooting Nvidia's profits and shares to the moon -- all in an insane attempt to "be first" for something that has no forseeable compelling ROI. It's a collective delusion and hype bubble. This is markedly different from the strategic "operate in the red to build marketshare" strategy of the few survivors of the dot-com bust, because at least those survivors were able to articulate (and realize) a logical ROI after reaching a tipping point of critical mass. This is more like the 98% of dot-com startups that burned bright fueled by VC right until they burned themselves out because they never actually had any believable plan for monetizing anything they were building. The lack of ROI will come rudely crashing down on these companies over the next several quarters as they run out of tricks to cook the books and hide the losses. Shareholders will get spooked and back out, share prices will crash, and big tech companies that have bet the farm on LLMs will suddenly find themselves without the necessary employees, capital, quality products/services, or reputational sway needed to save themselves. And when they collapse, Nvidia will collapse with them. And then maybe, finally, we can get back to the business of making things of actual value to humans.

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Yet to see a firm talk seriously about outcome growth from AI. It is all “output, output”. Which is ironic given that for over a decade software has enjoyed compounding output gains through abstractions, while outcomes have stayed flat or even declined. Nobody seemed interested in measuring that. Individual output gains can actually reduce the productivity of the system as a whole. More output does not guarantee better outcomes. My mental model is this: if we are creating software at ten to twenty times the pace we did before, then the upstream and downstream feedback loops would also need to scale by the same factor to make sure we are building the right thing. That is not only unrealistic but undesirable. When everything speeds up, the noise to signal ratio explodes, and it becomes harder to know what actually moved the needle and what is worth iterating on.

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Most engineers think there's one way to be a Staff Engineer. There isn't. Will Larson identified four archetypes: Tech Lead — drives a single team's technical direction and execution Architect — owns technical vision across a broader domain Solver — drops into the hardest, most ambiguous problems wherever they are Right Hand — extends a senior leader's reach into areas they can't personally cover Most engineers default to chasing "Solver" because it scratches the itch that got them into programming in the first place. But your fastest path to Staff is the archetype that matches your strengths AND your org's needs. If your company is scaling fast, they need Tech Leads. If they're drowning in cross-cutting technical debt, they need a Solver. If a VP is stretched too thin, they need a Right Hand. Match the archetype to the opportunity. Don't force the one that sounds best on paper. More about navigating the path to Staff at https://www.evalx.dev

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Micro-Teams: Possibly a Leaner Operating Model in the GenAI Era: We’ve all worked on “full-stack teams,” but that phrase has meant wildly different things depending on the company. Sometimes it’s a team where iOS, Android, Web, and backend engineers work side-by-side — collectively “full-stack.” Other times it means every engineer is expected to build the whole thing end-to-end themselves, from mobile to backend and everything in between. But imagine a different model: a true micro-team made of just one engineer and one product/UX partner. A duo. A two-person unit that delivers solutions end-to-end. For the lifetime of a problem, they’re ...... (please click on the link to read the rest of the article) https://lnkd.in/ggRSthVC #softwareengineering #productivity #lean #efficiency #kanban #microteams

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A lot shifted in 2025. AI made some things easier and other things more complicated, and it pushed teams to focus more on resilience. The 2025 State of the Internet Year in Review breaks down what stood out most this year. https://lnkd.in/eh2eZXfA

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ACTORS + AI: Director/Actor/Producer/Writer AI Chef 🧑‍🍳 Hans Obma visits the Cozy AI Kitchen 🎂 https://lnkd.in/gjiAvEfP to share his insights on how AI has transformed his creative processes. You may have seen Chef Hans in such 📺 hits as Better Call Saul, Wandavision, or Narcos — and yes, he's probably the most handsome AI 🧑‍🍳 chef we've had in the kitchen to date :-). Hans needed to learn a new language ... how did he do it? He got multimodal AI models to help him speak Welsh. Hans needed a way to scale how he communicated with his stakeholders ... how did he do it? He created an authentic-to-him way of scaling by creating an instant entourage of supporting agents. HT 🧑‍🍳 Ross Heise 🧑‍🍳 Matt Scholz and the power of the Wisconsin network for bringing such a storied talent to the Cozy AI Kitchen! --- This 🍰 episode: https://lnkd.in/gjiAvEfP All 50 episodes: https://lnkd.in/g6upvbGX

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