Fahim

544 posts

Fahim banner
Fahim

Fahim

@fahim

co-founder @adquick (easiest way to book outdoor ads), co-founder @getcabal (yc '21), ex-instacart/yammer

🇺🇸 Katılım Mayıs 2007
5.4K Takip Edilen1.7K Takipçiler
Fahim
Fahim@fahim·
@datarade Luckily gates can be built
English
1
0
2
329
Kumar🇺🇸
Kumar🇺🇸@datarade·
Austin can't be America's startup growth capital. Good for fish tacos, "hops in your beer", and yeti coolers - but it lacks a viable airport for scale.
Kumar🇺🇸 tweet media
English
16
1
28
11.1K
Fahim
Fahim@fahim·
@warp Hitting "Enter" to push a command has gotten slow overtime to a point where I'm back in Terminal now. Can you please fix?
English
2
0
0
80
Fahim
Fahim@fahim·
@chamath As if we didn’t skim human PRs either
English
0
0
1
31
Chamath Palihapitiya
Chamath Palihapitiya@chamath·
lol. The revenue for the model makers are going parabolic. But if the below is true, a plurality of that revenue isn’t sustainable.
Aakash Gupta@aakashgupta

41% of all code shipped in 2025 was AI-generated or AI-assisted. The defect rate on that code is 1.7x higher than human-written code. And a randomized controlled trial found that experienced developers using AI tools were actually 19% slower than developers working without them. Devs have always written slop. The entire software industry is built on infrastructure designed to catch slop before it ships. Code review, linting, type checking, CI/CD pipelines, staging environments. All of it assumes one thing: the person who wrote the code can walk you through what it does when the reviewer asks. That assumption held for 50 years. It broke in about 18 months. When 41% of your codebase was generated by a machine and approved by a human who skimmed it because the tests passed, the review process becomes theater. The reviewer is checking code neither of them wrote. The linter catches syntax, not intent. The tests verify behavior, not understanding. The old slop had an owner. Someone could explain why temp_fix_v3_FINAL existed, what edge case it handled, and what would break if you removed it. The new slop has an approver. Different relationship entirely. Arvid’s right that devs wrote bad code before AI. The part he’s missing: the entire quality infrastructure of software engineering was designed around a world where the author and the debugger were the same person. That world ended last year and nothing has replaced it yet.

English
89
27
579
355.4K
Fahim retweetledi
Todd Goldberg
Todd Goldberg@toddgoldberg·
Spotted in Dogpatch 👀 First YC ad/billboard?
Todd Goldberg tweet media
English
18
10
297
29K
Fahim
Fahim@fahim·
@warp Long time user. I hate to churn and find an alternative. Love the product.
English
0
0
0
21
Fahim retweetledi
Fletch Phillips
Fletch Phillips@FletchPh·
Built a live NYC building permit map on top of @_coenen’s awesome isometric pixel-art color-coded by permit type — demolitions, new buildings, plumbing, mechanical, solar. Click any dot for full details. ~1,000 fresh permits every day
English
36
102
1.1K
147.6K
Fahim
Fahim@fahim·
We’re announcing a $20M investment and commercial partnership with Outfront ($OUT) today to upgrade their software and intelligence stack
English
2
1
4
436
Fahim
Fahim@fahim·
It's impressive how bad the Azure portal is
English
1
0
2
136
Fahim
Fahim@fahim·
Finally worked with Kimi 2.5 and it’s actually passably good 😊
English
0
0
0
104
Fahim
Fahim@fahim·
Looking for sharp, ambitious engineers with Ruby/Rails experience. Remote friendly. Hiring immediately. DMs open
English
9
0
8
343
Fahim retweetledi
Lukas Ziegler
Lukas Ziegler@lukas_m_ziegler·
Python SLAM library with CUDA acceleration! 🧭 [📍save it to build a robot that needs to navigate autonomously] NVIDIA's NVlabs recently released PyCuVSLAM on GitHub, a Python wrapper for their CUDA-accelerated cuVSLAM library. Almost 900 ⭐️ on the repo! 😮‍💨 This brings state-of-the-art SLAM to Python workflows with real-time performance and visual-inertial precision. It runs on both desktop GPUs and Jetson platforms. What's inside? Python API for NVIDIA cuVSLAM, real-time SLAM with CUDA acceleration, support for standard datasets like KITTI and EuRoC plus hardware like OAK-D and RealSense cameras, multi-platform compatibility on Ubuntu 22.04/24.04 and Jetson (JetPack 6.1/6.2), and integration with ROS 2 via Isaac ROS. SLAM is fundamental for any mobile robot that needs to navigate unknown environments. The robot needs to simultaneously build a map of its surroundings while figuring out where it is on that map. This is computationally expensive, especially when processing camera and IMU data in real time. CUDA acceleration is what makes this practical. By offloading the heavy computation to the GPU, PyCuVSLAM can process visual-inertial data fast enough for real-time operation on platforms like Jetson. Having a Python interface to a high-performance SLAM library means you can integrate it into existing pipelines without rewriting everything in C++. Whether you're building SLAM pipelines for drones, ground robots, or autonomous vehicles, this is a solid foundation. Check it out on GitHub: github.com/NVlabs/PyCuVSL… ~~ ♻️ Join the weekly robotics newsletter, and never miss any news → ziegler.substack.com
Lukas Ziegler tweet media
English
7
95
541
25.2K
Fahim retweetledi
Mike Solana
Mike Solana@micsolana·
our insane cost of housing is the problem of problems. almost every social ill is exacerbated by a general sense of anxiety rooted in housing insecurity. every politician should have a plan to address it, and if they don't they should to be fired.
Mike Solana tweet media
English
202
195
2.2K
343.5K
Fahim retweetledi
tobi lutke
tobi lutke@tobi·
I think QMD is one of my finest tools. I use it every day because it’s the foundation of all the other tools I build for myself. A local search engine that lives and executes entirely on your computer. github.com/tobi/qmd Both for you and agents
Zac@PerceptualPeak

Okay, I finally got up to speed on QMD & how it all works. First of all, WOW. Holy shit man, what a insanely clever & genius orchestration of tools. My mind is THOROUGHLY blown. I LOVE the query expansion implementation, genuinely a super clever idea (plus I love the x2 weight being applied to the original query, makes perfect sense). I'd be really curious to know just how much more effective implementing the query expansion improved the overall matching quality. The BM25 Integration is done reallllly really well. I've always thought it sort of had to be "one or the other" but the ranked reciprocal fusion (which btw I had no idea even EXISTED until going down this rabbit hole lol) along with your added weight adjustments to the formula integrate it super well. BUT, that's not all! The freaking Qwen 3 reranker is the literal cherry on top (which again, had NO IDEA even existed until today). Super mind blowing stuff you've done here my friend. @TomDavenport - after doing a deep dive into this, I don't think completely REPLACING my retrieval workflow with QMD would be the most optimal for this particular use case. Primarily because it seems QMD is best optimized for static docs & doesn't natively factor in a time dimension (smart forking retrieval factors in the recency of the chat session in its final relevance score - forking from a super outdated chat session is not optimal & native QMD would increase the odds of this happening). BUUUUT thinking about it, fixing that would just require customizing the RRF formula...which apparently is possible since tobi did it! I bet if I added an aggressive recency bonus to the already existing top rank bonus that would not only completely solve the problem, but make the overall Smart Fork retrieval system waaaay more robust. Ok I'm gunna try it.

English
35
26
584
111.7K
Fahim
Fahim@fahim·
Play stupid games, win stupid prizes.
English
0
0
0
92