Julien

AI Consultant
789Labs | Ex-Microsoft AI 🧑‍💻 🌉 👾

[Julien @SystemOfOne]

Kimi K3 is looking like the new OSS heavy hitter! 💪🏅

It is beating out GLM 5.2 on our Ghidra reversing benchmarks and hanging close to the frontier closed models.

The pressure is mounting on closed model providers. Things are getting exciting!

[Elon Musk @elonmusk]

@jack Sparta never had a moat

[Julien @SystemOfOne]

A lot of engineers I talk to seem to think this way: “There is no upper bound to how much software we need”

Unfortunately, this software engineer wet dream 😝 is not the bottleneck for a lot of businesses. Especially those started by engineers themselves. It’s been a problem before AI and will be/is a hurdle to overcome after.

[Hamel Husain @HamelHusain]

I've been looking into public benchmarks and am astounded by the poor quality vs. how much we rely on them as an industry.

@xeophon pointed me to this excellent site https://t.co/xt5uUSyrcA which is an independent third party which scrutinizes benchmarks and "looks at the data" 💪

For example, here are some popular benchmarks we all rely on. Before trusting a benchmark its worth running them and inspecting examples the grader failed carefully, to get a sense of the quality.

I'm continuing to look more into this, and will write something up eventually once I've collected more data, but I think this is an important subject.

[Julien @SystemOfOne]

@typecraft_dev @theo Me too …

[Julien @SystemOfOne]

My wife got pregnant by another man.

It's been a challenging 9 months knowing he's not my son but I'm so excited to raise him like my own.

Here's 9 things it taught me about PHP:

[Julien @SystemOfOne]

Ban the slop kiddies !

[dax @thdxr]

whole industry is giving back all our productivity gains this week

[Julien @SystemOfOne]

this guy next to me is manually coding. what should I do?

[NVIDIA @nvidia]

Even Microducks need a nap. 😴

[Julien @SystemOfOne]

Based

[DeepSeek @deepseek_ai]

🚀 Introducing DeepInfer, our in-house inference framework, now fully open source!

Powering DeepSeek-V4.1-Flash at scale with high throughput and low latency. We’re sharing our production stack to help the community lower compute costs, reduce energy use, and make AI more affordable.

🔗 https://t.co/JGAik1kgk0

1/4

[@jason @Jason]

Be extremely intentional with your friendships — not acquaintances, not business partners, actual friends

Try to pick high-integrity people — the right people

Invest time in those relationships

Cut or downgrade folks who are transactional or who don’t show up for you

Reallocate that time and energy to the right people who do

It's ok to be cutthroat about this, as life is the memories you create with your friends and family.

Invest in making moments.

[Mark Saroufim @marksaroufim]

Why are we calling every new kernel release a Megakernel. This is a well written CUDA graph engine with persistent kernels and PDL.

The author didn’t even call this a megakernel
https://t.co/YUNNOvqasF

[Michael Seibel @mwseibel]

When making money is no longer your goal, that is when you can start being truly effective.

[Adam Cohen @adambcohen93]

Every person that moves to SF goes to a bunch of tech events in the first two weeks and realizes it's a complete waste of time.

[Julien @SystemOfOne]

@Sentdex Did they collaboratively do anything useful ?

[Julien @SystemOfOne]

@MeredithCheng22 @yacineMTB 🔥

[François Chollet @fchollet]

Some observations about the "total" automation of software engineering:

1. There are more software engineers now than in 2025, and demand is growing.

2. Software engineers have never worked harder than they do now.

3. They largely don't write code anymore, agents write ~100% of the code.

4. The bottom line of the companies that employs these engineers and agents (i.e. the terminal purpose of all this code) is typically not budging as a result of AI adoption.

This is why you have to think in terms of systems. Automating one aspect of a system creates its own friction and moves the bottlenecks elsewhere.

[Cindy Sridharan @copyconstruct]

I’m literally that weirdo who wrote (all by hand) a 15K word blog post on:

- why one cant treat models as oracles
- how models gaslight you all the time
- what it takes to build confidence in the model’s output

https://t.co/SmnEGkhJzX

So yeah sure, I believe in magical woo-woo

[Nick @nickcammarata]

interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had

with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works

https://t.co/zHij5zwKGT

[Julien @SystemOfOne]

@saranormous Girlfriends….