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The struggle of resizing windows on macOS Tahoe

https://noheger.at/blog/2026/01/11/the-struggle-of-resizing-windows-on-macos-tahoe/
876•happosai•5h ago•392 comments

CLI agents make self-hosting on a home server easier and fun

https://fulghum.io/self-hosting
298•websku•5h ago•206 comments

This game is a single 13 KiB file that runs on Windows, Linux and in the Browser

https://iczelia.net/posts/snake-polyglot/
93•snoofydude•4h ago•30 comments

Which programming languages are most token-efficient?

https://martinalderson.com/posts/which-programming-languages-are-most-token-efficient/
12•tehnub•57m ago•1 comments

iCloud Photos Downloader

https://github.com/icloud-photos-downloader/icloud_photos_downloader
313•reconnecting•7h ago•153 comments

Jerome Powell Responds

https://www.federalreserve.gov/newsevents/speech/powell20260111a.htm
198•0xedb•1h ago•56 comments

I Cannot SSH into My Server Anymore (and That's Fine)

https://soap.coffee/~lthms/posts/i-cannot-ssh-into-my-server-anymore.html
78•TheWiggles•4d ago•48 comments

FUSE is All You Need – Giving agents access to anything via filesystems

https://jakobemmerling.de/posts/fuse-is-all-you-need/
72•jakobem•5h ago•27 comments

I'm making a game engine based on dynamic signed distance fields (SDFs) [video]

https://www.youtube.com/watch?v=il-TXbn5iMA
196•imagiro•3d ago•22 comments

Sampling at negative temperature

https://cavendishlabs.org/blog/negative-temperature/
116•ag8•6h ago•39 comments

Don't fall into the anti-AI hype

https://antirez.com/news/158
625•todsacerdoti•16h ago•806 comments

Moving Scratch generation to Python on browser

https://kushaldas.in/posts/introducing-ektupy.html
8•kushaldas•2d ago•1 comments

Elo – A data expression language which compiles to JavaScript, Ruby, and SQL

https://elo-lang.org/
51•ravenical•4d ago•7 comments

The Next Two Years of Software Engineering

https://addyosmani.com/blog/next-two-years/
59•napolux•4h ago•36 comments

Gentoo Linux 2025 Review

https://www.gentoo.org/news/2026/01/05/new-year.html
295•akhuettel•14h ago•151 comments

I'd tell you a UDP joke…

https://www.codepuns.com/post/805294580859879424/i-would-tell-you-a-udp-joke-but-you-might-not-get
95•redmattred•4h ago•28 comments

Insights into Claude Opus 4.5 from Pokémon

https://www.lesswrong.com/posts/u6Lacc7wx4yYkBQ3r/insights-into-claude-opus-4-5-from-pokemon
33•surprisetalk•5d ago•9 comments

A set of Idiomatic prod-grade katas for experienced devs transitioning to Go

https://github.com/MedUnes/go-kata
105•medunes•4d ago•14 comments

Perfectly Replicating Coca Cola [video]

https://www.youtube.com/watch?v=TDkH3EbWTYc
136•HansVanEijsden•3d ago•72 comments

Show HN: Engineering Schizophrenia: Trusting yourself through Byzantine faults

37•rescrv•4h ago•9 comments

Ask HN: What are you working on? (January 2026)

148•david927•9h ago•492 comments

Rare Iron Age war trumpet and boar standard found

https://www.bbc.com/news/articles/cr7jvj8d39eo
12•breve•4d ago•2 comments

Show HN: What if AI agents had Zodiac personalities?

https://github.com/baturyilmaz/what-if-ai-agents-had-zodiac-personalities
15•arbayi•2h ago•7 comments

Poison Fountain

https://rnsaffn.com/poison3/
173•atomic128•9h ago•108 comments

A Glimpse into DexProtector

https://www.romainthomas.fr/post/26-01-dexprotector/
4•shelfchair•4d ago•0 comments

BYD's cheapest electric cars to have Lidar self-driving tech

https://thedriven.io/2026/01/11/byds-cheapest-electric-cars-to-have-lidar-self-driving-tech/
129•senti_sentient•5h ago•144 comments

“Food JPEGs” in Super Smash Bros. and Kirby Air Riders

https://sethmlarson.dev/food-jpegs-in-super-smash-bros-and-kirby-air-riders
262•SethMLarson•5d ago•67 comments

"Scholars Will Call It Nonsense": The Structure of von Däniken's Argument (1987)

https://www.penn.museum/sites/expedition/scholars-will-call-it-nonsense/
58•Kaibeezy•7h ago•6 comments

Quake 1 Single-Player Map Design Theories (2001)

https://www.quaddicted.com/webarchive//teamshambler.planetquake.gamespy.com/theories1.html
50•Lammy•21h ago•8 comments

I dumped Windows 11 for Linux, and you should too

https://www.notebookcheck.net/I-dumped-Windows-11-for-Linux-and-you-should-too.1190961.0.html
746•smurda•15h ago•699 comments
Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•7mo ago
Hey HN! We recently graduated from YC, and have been building customer personas for large e-commerce companies. We recently expanded into the image generation space, and have been working on research about how to automatically improve the quality of generated images.

Comments

average_r_user•7mo ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•7mo ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•7mo ago
This is a wonderful writeup of building a simple agentic system in general. What OP describes is more or less the bare minimum you should be doing at this point to get good (consistent) results from an LLM; single-shot prompting is a thing of the past.
palashshah•7mo ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•7mo ago
I'm surprised you landed on using o3 as the judge - we found it way too expensive. I use llm as a judge for generating color variations of products, definitely hoping for some improvements - it can be brutal to get non hallucinated features along with proper final rendering.
omneity•7mo ago
Have you tried open weights vision models such as Qwen VL, MiniCPM, PaliGemma...?

I'm also curious how usable are simpler vision models such as Florence in case you explored this direction.

palashshah•7mo ago
we're currently in the process of doing this. i think something that could potentially work is to iterate upon the initial image composition / structure using cheaper models, and then upscale at the end. this way you're saving on that iteration cost, but eventually land on a higher-scale image.
shmoogy•7mo ago
I actually haven't but nova from Amazon was surprisingly good at things like bounding boxes compared to some others You kind of have to test and measure so many different aspects to get the best at specific tasks Thanks for the idea
elif•7mo ago
This is great and provides a good starting point for any similar efforts.

However I think the temptation to lean all tasks on AI is perhaps a little naive if not lazy.

For mask generation, there is really not much reason to use AI. In this example, simple stochastic blob detection, a trivial function you could get from openCV or ask a college sophomore to write would generate much better quality masks.

palashshah•7mo ago
totally agreed here. i think my goal primarily with the mask generation was to test out how effective openai's capabilities were.

we're currently working on pipelines that limit the the involvement of AI to various tasks. for example, when generating an ad there's usually logo, some banner text, and background image.

we can use gpt-image-1 to generate the background image, another LLM to identify the coordinates of where we place the logo, and just add the logo onto the image. this is just one example!

jackphilson•7mo ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•7mo ago
"Simple stochastic blob detection" is an abstraction. You write (or import) a function where the the gnarly logic lives and call `detectBlobs()`. "Use an abstraction" doesn't mean you should use the same abstraction for every task, you should use the right tool for the job.
mentalgear•7mo ago
Again another example of "the unreasonable effectiveness of LLMs in a loop". At with time, the tasks for loop become bigger and more complex, until we find ourselves "outlooped" at least job wise.
ramoz•7mo ago
Nice retrospective but I guess this process is no longer needed as model's get better; esp as they start enabling features like consistent subjects. Seems like a lot of overhead to correct text for inspirational images, but I can imagine you need to always present some form of _quality_ to your clients.

Feel like control nets and some minimal photoshop work would've been better.

palashshah•7mo ago
totally. it got to a point where most of the text generated in our images was incorrect, and so it wasn't a great look showing that to our clients.

we're actually working on some form of what you described where we take images generated from LLMs + add consistent logos discretely rather than generatively.

abshkbh•7mo ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•7mo ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•7mo ago
I was kind of hoping this would be in the 'Dreambooth mold' of finetuning open weights models. I have used that with some success some ~2 years ago, does anyone know what improvements there have been in that direction since Dreambooth?
zahlman•7mo ago
It's frankly amazing to me that "ask another LLM to evaluate the image" actually produces useful feedback that results in actual improvement from the first LLM.

But then, I guess it's not much different of an idea from the earlier use of GANs, or of telling LLMs to "stop hallucinating", etc.

palashshah•7mo ago
totally. the way i think about it (purely based on intuition) is that asking an LLM to do understanding + image generation is too complex for it to be effective. if we separate out the tasks into discrete steps, the evaluation becomes better, and the generation simply becomes instruction following.
jacob019•7mo ago
This is all edited with gpt-image-1? The revised images are amazing. Were example logos provided or is it just working off of it's knowledge of a well known brand?