@galdayan1895 @a16z @speedrun Metapyxl is rights infrastructure for visual media, helping rights holders and platforms make ownership, licensing, monetization, usage tracking, and proof visible wherever protected images travel.
English
Tiffany just Tiffany
595 posts
Tiffany just Tiffany
@metapyxl
Tiffany, Founder 🌟 Empowering creators with the tools to protect, promote, and profit from your digital work. Safeguard your digital galaxy. #MetapyxlMovement
San Francisco, CA Katılım Şubat 2020
741 Takip Edilen270 Takipçiler
Last day to apply to @a16z @speedrun SR007. As an a16z speedrun scout, I've already referred 2 startups who got accepted
Sell me your product in one sentence. I will rate each of them with one sentence feedback. Those who are above 9, I will reach out directly and schedule an instant meeting.
English
@rain41 Once “AI-generated” entered the room, the category became more powerful than the visual experience.
That feels like the trust problem now: images need context, but context can also distort them. The question is whether that context is performative, financial, or verifiable.
English
What made the SHL0MS post interesting was not simply that people mistook a real Monet for AI. It was how quickly perception changed the moment the label “AI-generated” appeared.
Suddenly the brushwork felt “soulless.” The atmosphere became “artificial.” People began pointing out algorithmic textures and emotional emptiness inside an actual Monet painting.
Susan Sontag wrote in Against Interpretation that critics often approach art with the urge to extract meaning before truly encountering the work itself. Every image becomes allegory. Every detail becomes something to decode.
Kafka was endlessly subjected to this. Some read his work as social allegory about bureaucracy and alienation. Others reduced it to psychoanalytic fears of the father. Religious readings turned his characters into symbols of divine judgment and salvation.
Interpretation itself is not the problem. It can deepen understanding and reshape the past. But when interpretation overtakes experience, the artwork begins to disappear beneath explanation.
That is why Sontag wrote, “In place of a hermeneutics we need an erotics of art.”
The SHL0MS post revealed something uncomfortable. Many people were no longer looking at the painting itself. They were looking at the category surrounding it. The label determined the experience before the image even had the chance to speak.
Perhaps the real problem is not AI art, but our growing inability to encounter an artwork without immediately trying to classify, decode, and intellectually dominate it.
Was the painting truly worse once people believed it was AI?
Or did interpretation arrive before seeing ever could?
@SHL0MS @Jediwolf
𒐪@SHL0MS
i just generated an image in the style of a Monet painting using AI please describe, in as much detail as possible, what makes this inferior to a real Monet painting
English
@SHL0MS The gallery gives the artist institutional context.
Platform gives the artist social context. NFT gives the event financial context.
The discourse gives the work intellectual context.
The audience gives the whole thing proof of significance.
The image didn’t change. The frame did
English
English
@eli_schein @RogerDickerman @SHL0MS Totally agree. NFTs helped prove ownership, but they don’t explain the creative journey.
The next layer is provenance: who made it, how it was made, what tools or AI were involved, and what rights travel with it.
That’s the layer Metapyxl is solving.
English
@RogerDickerman @SHL0MS The problem NFTs do not yet solve is how an artwork was created. There is no verifiable provenance to trace the creative process, tools used and models employed.
English
Shoutout to Lindsey Lugrin, Founder and CEO of @FYPM_vip for being one of the loudest and most consistent voices fighting for creators to get paid what they are worth.
English
What a week at NAB Show 2026.
Our co-founder and CMO Jennifer Walling hit the floor in Las Vegas and brought Metapyxl into some incredible conversations around image intelligence, provenance, and the future of creator rights.
Proud of her and excited about what comes next.
English
Drop what you're building
Just the link
No pitch
I'll start↓
English
2000 in 50 days 🎉
no ads
just posting
Building a “YouTube for articles”
Launching soon
English
@neuralunlock Metapyxl combines Vault + Lens: creators protect, license, and track images in the Vault, while Lens surfaces ownership, rights, and trust context wherever content appears online.
English
What Does It Mean to Respect Creative Work? open.substack.com/pub/tiffanymcg…
English
@yrechtman Strongly agree. I’ve been working on this from the visual media rights side, and the pattern feels very real: the file itself matters less than the context around it: ownership, provenance, license scope, AI permissions, usage history, and enforcement evidence.
English
That is what Metapyxl is built for. Every image has an origin. We make sure it travels with one.
Thank you Jay for trusting us with your work.
English
Creator. Provenance. Rights. A clear record that this work is human-made and not available for AI training.
English
This is Joe Fong. San Francisco OG. Beloved figure in the Bay Area skate community. Photographed by @jaywatsonphoto
Jay has been doing this for decades across editorial, advertising, and documentary work.
English
Images like this deserve to exist with their full story intact. Who made it. When. The rights that protect it. The creator behind the lens.
English
@hanghuang_ @tonychang430 Metapyxl is building trust and rights infrastructure for digital media. Our Vault registers, protects, licenses, and tracks assets, while Lens brings ownership, provenance, and usage context with the content wherever it appears online.
English
YC's deadline is in 10 days
If you are applying and want to see the application that got me and @tonychang430 into YC P26, comment what you are building below and I will send you our application!
Bonus: for the top ideas, happy to refer + help with the application/interview!
Hang Huang@hanghuang_
After 6 applications and 6 rejection emails, we finally got into Y Combinator. Yes, read that one more time: 6 applications. 6 rejections. We turned a rejection into an admission offer. For a long time, every rejection led to the same question: "Do we pivot, or keep going?" We didn't think much of the first few rejections. Our reaction was mostly just: okay, back to building, apply again next time. Honestly, the hardest one was the 5th rejection because we felt so close. It was the first time we got an interview. We believed we had a real shot. But in the end, we got rejected… again. Looking back, the decision was fair. We were only doing around $300/month, and YC didn’t see a clear path to building a billion-dollar company through enterprise. So we stopped guessing and started listening. We did 20+ user interviews and realized something important: the people who really loved InsForge were not big enterprises. They were AI-native small teams and startups. That fundamentally changed how we saw the company. We clarified who the product was actually for, doubled down on what was working, and kept building in public on X and LinkedIn. We grew from 2,300 to 4,000+ databases in 2 months. Then we applied again. Our second interview with YC. We really thought this would be the one. But once again, we were rejected. That was the moment the question we had been asking ourselves after every rejection finally changed. No longer: “Do we pivot?” Instead: “How do we execute so well that the need for this product becomes impossible to ignore?” After 30 days of hell, we launched @insforge Launch Week 1. And it took off. Like, really took off! → 1.5M+ views on X → #1 on Product Hunt → #1 on GitHub Trending → 3K+ GitHub stars in one week But here's the craziest part: after rejecting us, YC changed their mind. Here was our second chance. We got an email from general partner Andrew Miklas (@amiklas), congratulating us on our launch and asking us to meet one more time. We figured it would be another tough interview. But the meeting was in two hours. No time to prepare. We were so nervous up until the very end. When we finally hopped on the call, he just said, “You guys have made huge progress. I want to work with you. Do you want to do YC?” WTF????????? Tony (@tonychang430) and I looked at each other. We were so shocked, we didn't even know what to say. Of course, the answer was yes. This is when we learned: Execute so well that your company becomes impossible to reject. Every rejection forced us to clarify our vision. The last one forced us to prove it. Next stop: YC P26!! @ycombinator 🥳 ( Read the full story below ⬇️ )
English
@hthieblot Metapyxl combines Vault + Lens: creators protect, license, and track images in the Vault, while Lens surfaces ownership, rights, and trust context wherever content appears online.
English
The longer I'm on X, the more I realize:
Founders with small accounts are the most interesting ones.
- too busy building to posture
- 0 Ego, they just wanna win
- keep posting with 0 likes
- the world isn’t rooting for them yet but I will
Tell me what you are building
English