Munachi

Building ‘Vercel’ for confidential computing | prev MLE @ Linkedin

[Munachi @chiefmantissa]

@theo If you choose to do so. I would love to chat more. Been building this for a minute: https://t.co/q3lxqNqMHi

[Theo - t3.gg @theo]

For every person who replies with a screenshot of their cancelled Claude Code plan, I will donate $10 to open source.

[Munachi @chiefmantissa]

@benln Working on cursor for retail trading. Will love to chat

[Jaid @Jaidcel]

Thought this was an overly harsh response to someone who asks for permission to work for free.

Then I looked into the PRs attached to the application. Bless Mitchell’s soul.

[Munachi @chiefmantissa]

@paulg This is the tell tbh.

Not every sentence is meant to be a to the point marketing hit.

[Munachi @chiefmantissa]

lol everyone collects on twitter

[Dr_Gingerballs @Dr_Gingerballs]

Guys, it's time to have the conversation that @karpathy might be an idiot.

[Lukasz Olejnik @lukOlejnik]

Amazon is holding a mandatory meeting about AI breaking its systems. The official framing is "part of normal business." The briefing note describes a trend of incidents with "high blast radius" caused by "Gen-AI assisted changes" for which "best practices and safeguards are not yet fully established." Translation to human language: we gave AI to engineers and things keep breaking?
The response for now? Junior and mid-level engineers can no longer push AI-assisted code without a senior signing off. AWS spent 13 hours recovering after its own AI coding tool, asked to make some changes, decided instead to delete and recreate the environment (the software equivalent of fixing a leaky tap by knocking down the wall). Amazon called that an "extremely limited event" (the affected tool served customers in mainland China).

[Munachi @chiefmantissa]

@jamwt @weswinder been thinking along these lines as well. What do you think of lsps in 2026? I've often guessed an ideal agentic environment would have a much leaner mode.

+1 on visualizing diffs. Images are optimal overall. I

[Munachi @chiefmantissa]

Who’s building humanoids in 🇨🇦?

Please tag anyone or company

[Munachi @chiefmantissa]

As usual my beloved. Quick someone get me some models that can run on this.

[Marques Brownlee @MKBHD]

Finally, new M5 Pro and M5 Max Macbook Pros: https://t.co/ZEt1iU4uXE

[Munachi @chiefmantissa]

@thdxr Cmon I thought this could help 🥲: /code-review

[Munachi @chiefmantissa]

@ivanburazin Cloud dev environments. Aside from compute isn’t the bottleneck granular aurh

[Munachi @chiefmantissa]

@chrislevan Will dm as well

[Munachi @chiefmantissa]

@KrishivThakuria Cursor for ML

[Munachi @chiefmantissa]

@ycombinator @GoogleDeepMind @grok what’s lyria

[Munachi @chiefmantissa]

@yacineMTB If only there was one person that has all 4 skills👀?
That’s not possible lol, I used to detest electricals man. What you working on?

[Munachi @chiefmantissa]

@tejas3732 Working on something that prevents this miss forever ping me in 5 days

[Munachi @chiefmantissa]

@RhysSullivan @p0u4aa It’s probably mainly an RL issue. I don’t think the harness can get us there sufficiently. There has to be a mode on RL for working inside a repo, that ensures it writes the answer in the “right” place.

[Munachi @chiefmantissa]

@openclaw Didn’t know Peter was austrian 👀

[Munachi @chiefmantissa]

Yep, just talked about this earlier today.

Slightly disagree on the one winner side of thing.

There are infinite constraints and requirements. One people hate monopolies so one isn’t working but 2) we might reach some complexity where ai gains tapers off. Especially with super large codebases.

It would be more apparent with llms writing lots of the code

[Naval @naval]

Is Traditional Software Engineering Dead?

“Does this mean that traditional software engineering is dead? Absolutely not. Software engineers—even the ones who are not necessarily tuning or training AI models—these are now among the most leveraged people on earth. Sure, the guys who are training and tuning models are even more leveraged because they’re building the tool set that software engineers are using.

But software engineers still have two massive advantages on you. First, they think in code, so they actually know what’s going on underneath. And all abstractions are leaky. So when you have a computer programming for you—when you have Claude Code or equivalent programming for you—it’s going to make mistakes.

It’s going to have bugs. It’s going to have suboptimal architecture. So it’s not going to be quite right. And someone who understands what’s going on underneath will be able to plug the leaks as they occur.

So if you want to build a well-architected application, if you want to be able to even specify a well-architected application, if you want to be able to make it run at high performance, if you want it to do its best, if you want to catch the bugs early, then you’re going to want to have a software engineering background.

The traditional software engineer is going to be able to use these tools much better. And there are still many kinds of problems in software engineering that are out of scope for these AI programs today. The easiest way to think about those is problems that are outside of their data distribution.

For example, if they need to do a binary sort or reverse a linked list, they’ve seen countless examples of that, so they’re extremely good at it. But when you start getting out of their domain—where you have to write very high-performance code, when you’re running on architectures that are novel or brand new, when you’re actually creating new things or solving new problems, then you still need to get in there and hand code it.

At least until either there are so many of those examples that new models can be trained on them, or until these models can sufficiently reason at even higher levels of abstraction and crack it on their own…

And remember: there is no demand for average. The average app—nobody wants it, at least as long as it’s not filling some niche that is filled by a superior app. The app that is better will win essentially a hundred percent of the market. Maybe there’s some small percentage that will bleed off to the second-best app because it does some little niche feature better than the main app, or it’s cheaper, or something of the sort.

But generally speaking, people only want the best of anything. So the bad news is there’s no point in being number two or number three—like in the famous Glengarry Glen Ross scene where Alec Baldwin says, “First place gets a Cadillac Eldorado, second place gets a set of steak knives, and third place you’re fired.”

That’s absolutely true in these winner-take-all markets. That’s the bad news: You have to be the best at something if you want to win.

However, the set of things you can be best at is infinite. You can always find some niche that is perfect for you, and you can be the best at that thing. This goes back to an old tweet of mine where I said, “Become the best in the world at what you do. Keep redefining what you do until this is true.”

And I think that still applies in this age of AI.”