frontpage.
newsnewestaskshowjobs

Open Source @Github

fp.

Open in hackernews

Building an agentic image generator that improves itself

https://simulate.trybezel.com/research/image_agent
67•palashshah•1y 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•1y ago
Quite interesting, do you have some documentation of your platform and capabilities? Your landing page is quite synthetic
palashshah•1y ago
hey! we're working with an initial set of customers, and plan to launch full capabilities soon. stay tuned :)
ramesh31•1y 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•1y ago
appreciate the compliment! yep, it's definitely necessary and is the bare minimum for building image generation systems in production.
shmoogy•1y 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•1y 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•1y 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•1y 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•1y 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•1y 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•1y ago
Why do you agree? I think we should outsource as much as we can to abstraction. We've been doing it forever.
dandelany•1y 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•1y 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•1y 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•1y 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•1y ago
Palash this is a great post, I learnt a lot as an image gen noob! Keep writing more :)
palashshah•1y ago
this is incredible to hear! i plan to keep writing on a weekly basis, and will be posting them on twitter.
t_mann•1y 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•1y 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•1y 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•1y 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?

Elevators

https://john.fun/elevators
108•Jrh0203•59m ago•35 comments

US Government lists fictional nation Wakanda as trade partner

https://www.bbc.com/news/world-us-canada-50849559
26•ceejayoz•14m ago•11 comments

Is AI Reasoning Right for the Wrong Reasons?

https://www.quantamagazine.org/is-ai-reasoning-right-for-the-wrong-reasons-20260731/
48•retupmoc01•47m ago•36 comments

Dubious research tied to Red Bull has shaped energy drink policy

https://www.theexamination.org/articles/red-bull-funded-research-energy-drinks-alcohol
10•Jimmc414•18m ago•0 comments

DeepSeek V4 Flash 0731 Intelligence, Performance and Price Analysis

https://artificialanalysis.ai/models/deepseek-v4-flash-ga
353•theanonymousone•8h ago•184 comments

A GTK4 SSH-askpass in Zig

https://xn--gckvb8fzb.com/a-gtk4-ssh-askpass-in-zig/
15•surprisetalk•36m ago•1 comments

U.S. debt-to-GDP ratio reaches 123%

https://fred.stlouisfed.org/series/GFDEGDQ188S
59•johnbarron•2h ago•48 comments

Google fixed more Chrome bugs in June than over the past two years, thanks to AI

https://blog.google/security/chrome-stronger-with-every-update/
377•Garbage•8h ago•353 comments

The session you cannot take with you

https://earendil.com/posts/session-portability/
654•apitman•12h ago•179 comments

Big Food vs. the People

https://www.lighthousereports.com/investigation/big-food-vs-the-people/
3•jruohonen•12m ago•1 comments

Show HN: Shared memory graph for Claude and ChatGPT, over MCP

https://uml.gpmai.workers.dev
3•12ziyad•18m ago•0 comments

Puberty blockers trial can start recruiting children

https://www.bbc.com/news/articles/c0jl4np49w1o
5•ksec•46m ago•0 comments

Next-Level Productivity Revealed to Be Smart Sticky Notes

https://www.taskloco.com/
3•taskloco_nyc•21m ago•1 comments

Algorithms on billion-scale graph using 10GB RAM: I love DataFusion

https://semyonsinchenko.github.io/ssinchenko/post/datafusion-graphs-cc-2/
3•speckx•23m ago•1 comments

Tasklet (YC P26) Is Hiring a Customer Success Engineer

https://tasklet.ai/careers/customer-success-engineer
1•mayop100•4h ago

New Defcon Badges Pack a Unique Open-Source Chip That Doubles as a Security Key

https://www.wired.com/story/defcon-34-badge-baochip-andrew-bunnie-huang/
24•hn_acker•43m ago•3 comments

The Art of Decision-Making (2019)

https://www.newyorker.com/magazine/2019/01/21/the-art-of-decision-making
3•EndXA•34m ago•0 comments

Admin: Terminally Ill Patients Aren't Exempt from Medicaid Work Requirements

https://www.commondreams.org/news/trump-medicaid-work-requirements-2677293170
23•hn_acker•51m ago•3 comments

The C ``Clockwise/Spiral Rule''

https://c-faq.com/decl/spiral.anderson.html
8•etrvic•2h ago•0 comments

Make Everything to Markdown

https://klartext.it-handwerk-stuttgart.de/
3•Beko2210•40m ago•0 comments

Winding Down Artichoke Ruby

https://hyperbo.la/w/winding-down-artichoke-ruby/
33•ksec•5d ago•2 comments

13 Models and 4 Agents on SWE Tasks: Go, Java, Python, Rust, TS

https://swe-rebench.com
3•ibragim_bad•48m ago•0 comments

Where .env Went Wrong

https://secretspec.dev/blog/where-env-went-wrong/
6•domenkozar•52m ago•0 comments

Show HN: Gander, an Android file viewer that asks for no permissions at all

https://github.com/mokshablr/gander
166•mokshablr•10h ago•61 comments

Online Friends Are Real Friends

https://toska.bearblog.dev/re-online-friends-are-real-friends/
7•Tomte•8m ago•0 comments

Stacked PRs are now live on GitHub

https://github.blog/changelog/2026-07-30-stacked-pull-requests-are-now-in-public-preview/
753•tomzorz•23h ago•263 comments

I 4x'd a 367x479 stamp-sized photo through 8 upscaling models

https://enlarger.app/blog/upscayl-vs-enlarger/
5•jaakkoc•3d ago•3 comments

DeepSeek-V4-Flash Update

https://api-docs.deepseek.com/updates/
507•dnhkng•10h ago•253 comments

JEP 401: Value Objects (Preview) merged to OpenJDK master

https://github.com/openjdk/jdk/pull/31120
212•mfiguiere•11h ago•132 comments

The Maxwell Conjecture Is False (GPT 5.6 Sol)

https://arxiv.org/abs/2607.27197
102•rahen•4h ago•91 comments