Niket Patel

You don't know how big a fish you are till you try a big pond.

India when? 🥲

Assemblers were faster at writing binary than humans were. Compilers were faster at writing assembly than humans were. AIs are faster at writing compiled languages then humans are. Deal with it. There's still plenty left for you to do.

Welcome Salesforce Headless 360: No Browser Required! Our API is the UI. Entire Salesforce & Agentforce & Slack platforms are now exposed as APIs, MCP, & CLI. All AI agents can access data, workflows, and tasks directly in Slack, Voice, or anywhere else with Salesforce Headless 360. Faster builds, agentic everything. 🚀 #Salesforce #Agentforce #AI venturebeat.com/ai/salesforce-…

@mattpocockuk @goodbyesahil most likely not a person

@goodbyesahil As in, the person who made this mistake will feel very bad about this

Appears that a big chunk of Claude Code's source code has been exposed on npm via a .map file accidentally uploaded to the public registry. ~512K lines of code ~1,900 files HugOps to the Anthropic team, this is brutal github.com/instructkr/cla…

You will never regret having a real thorough understanding of the code you produce, even if it's generated by an AI.

Developers spent decades complaining about 'spaghetti code' and 'technical debt.' Now we’ve built AI that generates 10,000 lines of it in seconds.

Complexity is a poison. There is a reason people still get drawn to TUIs in the year of 2026. Our predecessors expected we would have flying self-driving cars by now. Web is stalling civilizational progress.

The risk of AI for education is not students cheating in exams, it is people in general cheating themselves into believing they understand things they don’t.

I have only 30+ years of experience as an entrepreneur, but I too agree. The only way to truly know whether an idea is good or bad is to test it. Good news is that it's easier to test ideas now than it has ever been.

all your Obsidian files are now executables

@prisma doreveal.com - AI partner for qualitative research.

Building a SaaS is hard. Let’s give each other visibility. Drop it in the 🧵 below. We’d love to check it out 🔥

AI makes senior architects more productive and reduces the need for junior engineers. The architect needs to understand the requirements as well as the technology stack well, to be able to guide the AI and fine tune its output. But if we don't have junior engineers, we don't get to train the next generation of architects - after all how does someone become a software architect without being a junior engineer first? I am still thinking through how this gets resolved.

The Transformer architecture is fundamentally a parallel processor of context, but reasoning is a sequential, iterative process. To solve complex problems, a model needs a "scratchpad" not just in its output CoT, but in its internal state. A differentiable way to loop, branch, and backtrack until the model finds a solution that works.

@prisma @alexdeliadev Message: Error in Prisma Client request: Invalid `STUDIO_EMBED_BUILD<"u"&&STUDIO_EMBED_BUILD? I just used psql after that.

@nexneo @alexdeliadev Thanks for getting back to us. Could you share a bit more about your setup and the error logs you’re seeing? That will help us investigate further.

How do I run the old version of @prisma studio with the new version of prisma 😭

@prisma @alexdeliadev Mainly it was actually running. New one was broken few days back

@alexdeliadev What features you liked about the old version?

One thing I’ve noticed about people who say they “don’t code much anymore.” Most of them have been doing this for YEARS. They already understand systems. They already understand databases. They already understand how things break. So when they use AI, they know exactly what to ask and what to fix. The problem is beginners see this and think they can skip the fundamentals. That’s where it goes wrong. AI doesn’t replace understanding. It amplifies it. If you don’t know how things work, you won’t even know when the AI is wrong.

A few things I've noticed as all devs write code with AI. When you write foundational / architectural code of a new project by hand, you "feel" the code pushing back if your abstraction isn't right. You feel when something is harder than it should be. The code is telling you it's not in the right shape. Good engineers are sensitive to this. When you're using an LLM, you keep pushing right through this in a way that feels like you're making progress, and it may even be directionally correct in a sense, but the underlying foundation of it all is actually bad in a way that either kills progress of the LLM later as it buckles under the complexity it has created or destroys your ability to maintain the code long term. Related to this, I see a general restlessness with just sitting and thinking about a problem for a while. As I've been working on a new library here at Laravel, there have been days where it feels like I mainly just stare at my screen thinking about something. When Claude Code is at your fingertips, it's tempting to just start yapping into the terminal and watching code come out the other end. Again, directionally correct in some ways, but often doesn't land on the elegant solution that is waiting to be discovered.