Dani Zhu

What ships in AI & why it matters
Founding product lead: TIME Best Invention · 0→1→scale · millions of users
Building proactive, self-evolving memory @EverMind

[Dani Zhu @danizhu]

Raven is open source and still pre-alpha. Feedback and contributions are very welcome. 🫶
https://t.co/i7VjgaFvD5

[Dani Zhu @danizhu]

We’re releasing a new version of Raven soon. Here’s an early look at one long-running task Raven completed autonomously. 🙌

To build this game, Raven ran 42 planning, building, and verification rounds over roughly 4 days.

Each round used three Raven-Code roles in sequence:

• A Planner selected the next coherent piece of work from the backlog and previous review

• A Builder implemented it in Godot, ran the checks, played through the main path, and captured evidence

• A Verifier independently reviewed the build and screenshots, then either marked the task proven or pushed the gaps into the next round

Progress persisted through Git commits, reports, the backlog, fix log, and a project journal. Failed checks could be handed straight back to the Builder for another attempt.

That sustained loop is what excites me most about Raven. The system can keep a complex project moving for days, carry progress forward from one round to the next, check its own work, and correct course as it goes. 🐦‍⬛

[Elliot 艾略特 @elliotchen100]

Two months ago, we, @evermind, launched Raven 🐦‍⬛.

The next version is almost here, and I think this game shows where we're headed better than a diagram could.

We built this 3D boss fight with Raven. Watch the lighting, the two boss phases, the weapons, and the ending. Please turn the sound on too. I'm genuinely impressed by how it all came together.

It took real compute and plenty of iteration. What excites me is Raven coordinating specialized agents on one task graph to make something that feels like one game. That's what we mean by “Harness of Harnesses.”

More soon. Raven is open source: https://t.co/V7vNuBBTys

[Dani Zhu @danizhu]

Built on @typesafeai's Jev via @OpenRouter
Code: https://t.co/MXLIXT2zCM

[Dani Zhu @danizhu]

I asked Jev to read Mary Shelley’s Frankenstein and score each passage across 9 emotions, plus overall intensity.

Jev finished the task in 24.7 seconds, reading 601 passages, making 6,010 decisions for a total cost of just $0.0337. ⚡️

I turned those scores into emotional aurora of the whole book. Pretty cool. And the efficiency is insane to be honest.

Not every task needs an LLM. We should rethink how often we default to it. 🤔

For high-volume, structured decisions with a clear output schema, a decision model like Jev can be a much better fit.

[Dani Zhu @danizhu]

Really thoughtful piece, worth reading! 🎯

Jeffrey Katzenberg led Walt Disney Studios through the animation renaissance, then co-founded DreamWorks and helped navigate the industry’s shift from hand-drawn animation to CGI.

His argument on AI and creativity is more nuanced than “AI will replace artists” or “AI can never create”:

1. Technological shifts expand what can be made, but the human cost of the transition is real.
2. The tools vs. no tools debate is a trap. The real fight is over the terms: consent, credit and compensation.
3. AI can make production dramatically cheaper, but cheaper production does not create taste, intention or emotional meaning.
4. The artists who learn to use these tools will create things the engineers never imagined.

AI will expand the creative canvas. What matters now is who gets to shape it, and on what terms.

[JK @jeffreykWNDR]

The World is Changing: AI For Creativity

By Jeffrey Katzenberg

A few months ago, I sat in my office in Silicon Valley and watched as a tech founder showed me something extraordinary. On the screen was a fully realized, beautifully lit, well-composed animated scene. It was stunning and it made me feel exactly what I felt in 1986 watching Luxo Jr. That was the first time I watched a computer-animated 3D character take a breath and seem, against all reason, to have life. It left me in awe.

Later that day, I received a text from an artist I've known for thirty years, 350 miles to the south, in the city where I spent most of my career. After seeing a similar video, she texted: "Is this the end of us?" My answer was, "Certainly not.”

I have spent the better part of the last decade in Silicon Valley, but the heart of my career has been in Hollywood. Being deeply connected to both worlds means I have deep loyalties to each and a responsibility to speak honestly to both.

In 2023, I said that these new AI tools would cut the time and cost of producing world-class animation by as much as ninety percent within three years. Some colleagues were alarmed, many were furious.

There is growing fear and resistance surrounding AI within the creative community. I deeply understand it, because I've spent countless hours walking through animation studios watching gifted artists bent over their desks, rebuilding a single second of film for the tenth time because the ninth version wasn't quite right. I've sat in screening rooms where four years of people's labor played out in minutes, and I knew the name of every person that had spent countless hours bringing those images to life. The creative process is a calling, there's really no other way to describe it. From the outside some see resistance. From the inside, it is love.

People do not fight this hard for things they don't care about. The pushback coming out of Hollywood represents the collective effort of people who are deeply passionate about their craft.

Is History Repeating Itself?

The history here is more complicated than either side may realize. In 1906, the most famous composer in America, John Philip Sousa, published an essay titled “The Menace of Mechanical Music." He warned that the phonograph would become "a substitute for human skill, intelligence and soul."

Sousa's fight was not really about the machine, it was about money. The machines were playing his compositions, and the men who built them weren't paying him a cent. His campaign helped create the Copyright Act of 1909. He did not stop the technology. He changed the terms under which it could use his work.
A hundred years ago, sound came to the movies. We remember it now as a miracle, and it was. What we forget is who paid for it. Before sound, tens of thousands of musicians made their living in the orchestra pits of movie houses, scoring every film live, every night, in towns all over the world. When the soundtrack arrived, the work of one composer and one orchestra was recorded for a film that went into thousands of theaters. The union fought back with everything it had, taking out newspaper ads across the country warning against the menace of "canned music," one of them showing a mechanical man tearing the strings out of a harp while an angel wept.

They were not fools, and they were not Luddites. They were right. Those pit jobs did not come back. And yet (this is the part we have to be brave enough to admit), sound gave us the movie musical, the modern score, sfx, sound design, audio engineering, and an art form vastly larger than the one it disrupted. And it helped keep Hollywood in the forefront of world entertainment for the rest of the century and into the next. The loss was real. And yet the art form expanded.

This is a story that has been told over and over again. To resist technology is to risk irrelevance. Just look at Kodak or Blockbuster. To embrace technology is to open doors of new possibility. Just consider Apple and Netflix.

What I Learned From Walt Disney

In the mid-1980s, I was tapped to lead Disney's animation division at a moment when the studio was at an inflection point. Animation wasn't just another business unit. It was the soul of the company, a medium revered because of Walt's genius and his passion. But the production system was cumbersome and unforgiving. A single movie was 125,000 individual hand-drawn and painted cels, photographed one frame at a time. Every revision carried a cost measured in months. These degrees of difficulty shaped the kinds of stories we could tell.

We found our way forward in an unexpected place: Walt himself. The Disney archives held astonishing recordings of Walt explaining his creative process. His own writings. His notes and storyboards. Work product captured at every stage of his process. This was truly a gift. Listening, reading, sitting with the work itself, we heard him talk about character, about emotion, about how an audience feels when a character truly comes alive. He talked about making bold choices and refining a scene until it genuinely moved people. We didn't hear a word about pencils or paintbrushes. In fact, Walt was famous for being a technologist, forever hunting for state-of-the-art tools, often inventing them himself to achieve the images he saw in his head. But he never defined animation by the tools. He defined it by whether the audience believed the character. His principles were timeless. The tools were not.

That realization changed everything. We co-developed the Computer Animation Production System (CAPS) with a young Northern California company called Pixar, replacing hand-painted cels with CGI. In The Little Mermaid, the final scene shimmered with a dimensionality and light that the old process simply couldn't achieve. In Beauty and the Beast, the ballroom sequence moved with a cinematic sweep that placed the audience inside the emotion of the moment. In Aladdin, the Cave of Wonders felt vast and alive, and the Magic Carpet became an intricate, compelling character all its own. In The Lion King, the stampede carried a scale and intensity that raised the emotional stakes beyond anything we'd done before. Technology didn't diminish the craft, it expanded the canvas. It gave artists more room to create.

A decade later, the canvas expanded again. When Disney released Pixar's Toy Story, it wasn't simply a technical milestone. It was proof that a fully computer-animated film could carry real emotional weight, that it could make audiences laugh, cry, and believe. At DreamWorks, we made the difficult decision to sunset hand-drawn animation and become a fully computer-animated studio. It was the right thing to do, but it was not without pain. It cost talented people their place in an industry where they had worked their whole lives. Some made the leap to the new tools and did the finest work of their careers. Some never did.

Tools are never the point. The instruments change with every generation. What endures is taste and imagination. The magical ability to make an audience feel. One of the greatest storytellers of our generation, George Lucas, succinctly captured the eternal essence of this issue: “It’s not the how, it’s the why.”

A Distinction With a Difference

I asked one of the leading AI models a question that has been challenging me for months. What is the difference between reasoning and creating? Its answer changed how I think about almost everything happening in this industry. It said . . .

Reasoning and creating are two distinct cognitive modes, though they also work together. Reasoning is fundamentally evaluative and analytical. It operates on what already exists: facts, premises, evidence. It moves toward a conclusion that was in a sense already implied by the input. Reasoning is constrained by logic and truth. Its goal is to arrive somewhere correct, not to invent somewhere new.

Creating is fundamentally generative. It produces something that didn't exist before. And crucially, there's no single right answer waiting to be found. A blank page has infinite valid responses. Creation involves choices that can't be fully justified by logic alone. Taste, intuition and vision fill the gap where deduction runs out.

Reasoning is what Silicon Valley has been perfecting. Creating is what Hollywood has been practicing for more than a century. AI today operates almost entirely on the reasoning side of the line. It can deduce, evaluate, optimize, and pattern-match brilliantly. And while it can create, there is a real distinction to being creative. What it doesn’t yet have is those things that make us human: empathy, devotion, serendipity, the kind of creativity that comes from a person trying to say something only they could say. When the bot generates a piece of art, it is not trying to communicate anything. It is statistics, not soul; it is emulating things that have been done. By contrast, human creativity isn’t about repeating patterns of zeros and ones; it is about doing something new.

One day, AI may close this gap. Three years ago, the leaders building AI would have called what they are achieving today, improbable, if not impossible. Impossible is no longer improbable.

Today, the line between reasoning and creating is real. Even the leading technologists acknowledge we are not there yet. There is no scientific path to crossing this divide that anyone in the field can articulate today. Understanding that gap is where we will find common ground.

A Path Forward

In 2016, I closed one chapter in Hollywood with the sale of DreamWorks and opened another in Northern California, co-founding WndrCo. We’ve backed more than 50 founders building the next generation of technology and watched how breakthroughs in Silicon Valley emerge, first as experiments, then as platforms, and finally as infrastructure that reshapes entire industries. It's worth remembering that the last great revolution in animation also came from the north. Pixar was a Northern California company, forged not in the conventions of the Hollywood studio system, but in the technological breakthroughs of Silicon Valley. I've spent years on both sides of this bridge. For sure, I don’t have all the answers (take Quibi, for one!). But, from my past and present vantage points of my long career, here is what I see . . .

Brilliant people in Northern California building this technology have made something extraordinary. They have earned the right for the rest of us to be, if not believers, at least optimistic that what comes next will be remarkable. But they have not made an artist. The tools are powerful, but they are not what makes a story matter. That knowledge lives 350 miles to the south, inside people whose life's work has informed the very models you are building. The right path forward includes them by design, with credit, with consent, and with compensation. Build this with the storytellers. Not on top of them. Taste is not something that can be synthesized, it is uniquely human.

At the same time, Hollywood needs to accept that AI is not going away. The energy they are spending trying to make it disappear is energy they are not spending deciding the terms on which it will exist. And the terms are everything. The north needs something from it that they cannot build and cannot buy: creativity. The kind that takes a blank page and conjures a single right answer where there was none and has held audiences for a century. Without it, the most powerful reasoning engine ever invented will still be missing the only thing that makes a story worth telling.

The artists who learn to wield these new instruments will do things the engineers never dreamed of. They always have. Edison invented the motion picture but made terrible movies. It took Chaplin, Lloyd, Keaton and so many others to make movies emotional. Now, the canvas is about to expand yet again. We should decide now that we intend to paint on it.

There are so many valuable lessons in history. This has happened many times before, and it was never settled by the technology. It was settled by the terms. Sousa did not stop the phonograph; he helped write the law that made sure composers got paid. And two years ago, when the writers and the actors walked out, they were fighting for the very things Sousa was fighting for in 1906. Consent, compensation, the basic recognition that human creative work has a price that must be paid. The terms of that fight are still being negotiated, but the principle is older than any of us.

The tools-versus-no-tools argument is a trap. First, we must all agree that there should be terms. Then we can have the crucial debate about what fairness requires.

What I Learned From Steve Jobs

Years ago, Steve Jobs said, "It's in Apple's DNA that technology alone is not enough. It's technology married with the liberal arts, married with the humanities, that yields us the result that makes our hearts sing." He was describing a device. But he could just as easily have been describing this tale of two cities.

What I See Coming Soon

As the barriers and the costs come down, more films will get made, not fewer. Studios will get to take more risks. There will be more seats at the table, and very soon entirely new forms of storytelling. In the 1980s, animation was dismissed as a niche corner of the business. Today it is one of the most beloved and profitable forms of storytelling in the world. In live action, filmmakers like Steven Spielberg, James Cameron and Peter Jackson embraced new visual tools not as shortcuts, but as instruments, and expanded cinema in the process. Every time storytelling has met a genuine technological shift, from synchronized sound to color to computer animation, it has redefined the boundaries of the medium and grown larger in the process.

Assuredly, I don’t have all the answers, but I am confident that the creative opportunities will expand yet again. How we come through this is a choice. The north has the new tools. The south has the creative soul. The best future will draw on the best of both worlds.

[Dani Zhu @danizhu]

@danlovesproofs hahahaha

[Dani Zhu @danizhu]

@shfred0 wahoo super cool!
the ending reminds me of Stranger Things though.. 😂

[Dani Zhu @danizhu]

Love seeing Raven make its way into the builder community 🧡

We’re entering a world where builders work with many specialized agents, not one universal assistant. Spinning up more agents is easy. Getting them to work as one system is hard.

That’s what we’re building with Raven: one orchestration layer for research, coding, design, and unattended workflows, backed by persistent memory from EverOS.

It’s open source and still pre-alpha. Feedback and contributions are very welcome. Come build with us 🙌

[Dan Kornas @DanKornas]

Running several agents gets messy fast. Raven is built to coordinate them.

Raven is a pre-alpha multi-agent orchestration repo for builders who want to coordinate specialized agents from one place.

It helps you delegate work across research, coding, design, and unattended workflows by bringing built-in and third-party agents into shared workflows.

Key features:

• Unified orchestration surface – delegate tasks, coordinate execution, and integrate results in one place
• Four built-in agents – Raven-Research, Raven-Code, Raven-Design, and Raven-Oncall cover distinct workflow types
• Deep research support – Raven-Research produces structured reports with traceable sources for complex questions and technical analysis
• Agentic development workflows – Raven-Code supports implementation, debugging, refactoring, data processing, and analysis
• Third-party agent connections – connect external agents and coordinate their capabilities in shared workflows

It’s open-source under the Apache License 2.0.

Link in the reply 👇

[Dani Zhu @danizhu]

@marcustrell_ai yeah agree, transparency and traceability are so critical. Most memory systems just feel like black box.

[Dani Zhu @danizhu]

Claude Opus 5.5 and GPT-6 Sol and Luna landed on the same day (and Grok 4.7 only came out yesterday). Choosing a daily driver just got harder. 🔥

Of course we want to test them all. And when one works better for a task, we should be able to switch. Models will keep leapfrogging each other, and people will keep moving between them.

But each time we switch, we’re not just swapping intelligence. We also want to carry over our project history, preferences, workflows, and everything our agents have learned. If every AI product keeps its own isolated memory, users either stay locked in or keep starting over.

That’s the problem we’re working on at EverMind. We believe memory needs to be durable and belong to users. It should become infrastructure outside any single model. We’re building EverOS, an open-source, local-first memory runtime that helps agents form, organize, consolidate, index, and retrieve memories across sessions.

The canonical memory lives in human-readable Markdown, so it remains inspectable and portable instead of being trapped inside one vendor’s product.

Models will keep changing. Your agent’s memory should not have to start over. 🧡

[Dani Zhu @danizhu]

Spot on! A portable mistake is still a mistake. Knowing what’s worth keeping, updating, or forgetting is the hard part. EverOS uses editable Markdown as its source of truth, and Reflection to consolidate and retire superseded memories.
Curious do you use any memory system today or maybe you've built your own?

[Dani Zhu @danizhu]

Poor Terra has been forgotten...

[Dani Zhu @danizhu]

oh so this is what's been cooking! We got GPT-6 Luna, Sol and Astra as the whole family 🔥

[Dani Zhu @danizhu]

and i believe we will get a reset soon 😂
https://t.co/me3ttQAvLy

[Tibo @thsottiaux]

GPT-6 Sol and Luna are out. Not only are they a very significant improvement across the board, but also in writing and general "you know when you try it" quality.

We are also permanently reducing the API price by 50% making both of them viable for a ton of new usecases and making your usage go further too, even on the subscriptions.

And one more thing. We are loading a banked reset into all accounts of our Plus, Pro and Business users. Let's go!

https://t.co/00DRh1sRrO

[Dani Zhu @danizhu]

@thsottiaux wahoo!

[Dani Zhu @danizhu]

@Ansezz yeah agree! Curious from your Shopify builder point of view: how do you think of this trend as more of the storefront experience moves into agents?

[Dani Zhu @danizhu]

Shopify partnered with Muse. Amazon blocked Muse.

The difference isn’t that Shopify believes in AI agents and Amazon doesn’t. It’s their business models.

Shopify is merchant infrastructure. It benefits whenever more interfaces bring demand to its merchants. Every new agent can become another distribution channel.

Amazon is a vertically integrated marketplace. It monetizes discovery, rankings, ads, checkout, and Prime. A third-party agent sitting between Amazon and the shopper doesn’t just automate the purchase. It takes away Amazon’s most valuable assets: customer intent, behavioral data, and the direct customer relationship.

Shopify wants to become the transaction layer beneath every AI agent.

Amazon wants Rufus to remain its primary shopping interface.

Different business models drive opposite strategies. 🎯