Cofounder & CTO @ Creatify
San Francisco, CA
Joined August 2013
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exactly why ours isn't another travel-booking demo. marketers make ads every day — we built the agent for the job people actually do daily, not the one that looks good on stage.
It is in early access, however Creatify’s Ad Agent is live at creatify.ai.
Their headline says 10× the creative volume and 2× ROAS, but they haven’t shown that one caused the other.
How many creatives actually received meaningful spend? What changed in targeting, retargeting and attribution? Until that’s disclosed, it’s a before-and-after marketing story.
In the demo, it's thru moving prospecting to retargeting, ofc that "works" ;)
Introducing Runway Ads, an autonomous engine for performance marketing.
Since July, we’ve used Runway Ads to:
-Scale ad volume 1,000% while doubling our return on ad spend
-Increase conversion by 34% with click-through rate holding steady
-Bring our cost per subscriber down 41%
-And add $100M ARR
Now, we’re making it available to select enterprise partners and will be rolling it out widely in the coming weeks.
Learn more and request early access: runway.com/news/company-news…
Directly use it in slack is even better ;) creatify.ai/slack
Why wait, if you can already do this on creatify.ai ;)
meanwhile this ad is one-shot with our agent
bullish on Explainer videos as well ;)
We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks:
Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better:
Diagrams / images. Instead of writing, ask your LLM to create a diagram. These can be a lot easier to process, parse, and understand. But even better:
Web pages. Ask for output "in HTML" to get a beautiful, interactive webpage. LLMs are getting really good at frontend and can create beautiful experiences, animations, etc. But even better:
Explainer videos. The output format I am most bullish on is fully custom / bespoke explainer videos generated on any arbitrary topic. Experiment with things like "Create a 3b1b style video explainer on X. Use my ElevenLabs API key for audio narration". (you'd need an API key for the latter or you can ask your LLM to find you decent free alternatives that use your local compute). This is actually starting to work!
In summary:
- As LLMs get better, they will do more and more of the legwork autonomously, and a lot more of our work will rise up the abstractions into oversight and understanding.
- Luckily, LLMs can help here too because as intelligence and code are increasingly abundant, you can ask for large, custom, discardable software artifacts (e.g. web apps, video explainers) that would have never made sense to create before. Push the boundaries here and you'll be surprised.
Ben Affleck talks about the origin of InterPositive, the film-AI company he founded in 2022. Ultimately Netflix bought that company in March-2026 for $587 mn in cash.
Ben Affleck walked into OpenAI, saw early text-to-image, and called Matt Damon to say they needed to shoot as many movies as possible in the next few years because they were finished.
The panic lasted until he looked again and saw the researchers were brilliant at the model and almost blank on how a shot is captured, lit, and cut. That gap is what he later built a company on.
----
From "Bloomberg Live" YouTube channel, (link in comment)
behind the scene @Creatify_AI
Why wait, if you can already do this on creatify.ai ;)
meanwhile this ad is one-shot with our agent
Introducing Runway Ads, an autonomous engine for performance marketing.
Since July, we’ve used Runway Ads to:
-Scale ad volume 1,000% while doubling our return on ad spend
-Increase conversion by 34% with click-through rate holding steady
-Bring our cost per subscriber down 41%
-And add $100M ARR
Now, we’re making it available to select enterprise partners and will be rolling it out widely in the coming weeks.
Learn more and request early access: runway.com/news/company-news…
Chaz retweeted
Really excited to finally share Boreal-H3, our video generation model built for advertising.
What excites me most isn’t just the model quality—it’s our post-training approach behind it.
We started with a strong foundation model, then built a feedback-driven post-training system around the things that actually matter for advertising: reference fidelity, brief following, identity consistency, motion, and failure detection.
Evaluation feeds back into what data we collect, which failures we target, and how we design the next round of post-training—so each cycle improves not only the model, but the process for improving it.
The result: Boreal-H3 reaches 85.3% reference fidelity while making major gains in ad usability.
This is a strong example of how much capability can still be unlocked through post-training—and a step toward a more systematic, self-improving paradigm for video generation.
Huge credit to the team behind this. More technical details in the launch post 👇
Read our technical report: labs.creatify.ai/research/bo…
Introducing Boreal-H3 — a video model built for ads and our next step toward recursive self-improvement in video generation.
A good-looking video isn’t enough. The product has to stay the same. The actor has to stay the same. The label has to be right. And the action in the brief actually has to happen.
So we post-trained MiniMax H3 specifically for advertising.
But this isn’t a one-off SFT or LoRA fine-tune. We built a closed-loop system that learns what to improve next.
Human-calibrated evaluation diagnoses failures and guides the next intervention: targeted data collection, reinforcement learning, or inference optimization. When the feedback is unreliable, we revise the evaluator or reward—not just the generator.
Every experiment feeds into shared memory, informing the next training decision. The model improves, and so does the process that produces its successor.
The results:
→ 85.3% reference fidelity — highest among the frontier video generation models we evaluated
→ Brief success: 28% → 50%
→ Identity match: 83% → 94%
→ Visible defects per clip: down 70%
→ Generation time and estimated cost: down 20%
Boreal-H3 doesn’t just make better-looking video. It makes more usable ads.
Credit to the @MiniMax_AI team for the foundation we’re building on.
This launch is a checkpoint, not the finish line. We’re building more than a better video model. We’re building a system that learns how to make the next one better.
Chaz retweeted
Built on MiniMax H3, @Creatify_Labs' Boreal-H3 is a video model optimized for advertising, keeping products and characters consistent while following creative briefs more accurately.
Excited to see MiniMax H3 serve as the foundation for more frontier models tailored to specific industries! ✨
Introducing Boreal-H3 — a video model built for ads and our next step toward recursive self-improvement in video generation.
A good-looking video isn’t enough. The product has to stay the same. The actor has to stay the same. The label has to be right. And the action in the brief actually has to happen.
So we post-trained MiniMax H3 specifically for advertising.
But this isn’t a one-off SFT or LoRA fine-tune. We built a closed-loop system that learns what to improve next.
Human-calibrated evaluation diagnoses failures and guides the next intervention: targeted data collection, reinforcement learning, or inference optimization. When the feedback is unreliable, we revise the evaluator or reward—not just the generator.
Every experiment feeds into shared memory, informing the next training decision. The model improves, and so does the process that produces its successor.
The results:
→ 85.3% reference fidelity — highest among the frontier video generation models we evaluated
→ Brief success: 28% → 50%
→ Identity match: 83% → 94%
→ Visible defects per clip: down 70%
→ Generation time and estimated cost: down 20%
Boreal-H3 doesn’t just make better-looking video. It makes more usable ads.
Credit to the @MiniMax_AI team for the foundation we’re building on.
This launch is a checkpoint, not the finish line. We’re building more than a better video model. We’re building a system that learns how to make the next one better.
#MuseMoneyChallenge saved me 480$/yr for now, muse really doesn't like me subscribe to other AI agents for sure, but i'm happy about the result :)
@alexandr_wang Muse saved me money, so I made an ad for Muse to say thanks 🙏
Tried to send it through Muse, but somehow it wouldn't go through. So here it is 👇
