Technically Creative by KoobrikLabs

Weekly AI news for the creative industries. This week, Technically Creative looks at the rise of AI agents and a much bigger question than whether AI can write, code or make images: how much authority are we actually prepared to give it?
OpenAI and Meta are pushing toward always-on AI agents that can access files, communicate with people and act on your behalf. That became very real this week when a Meta Muse user discovered the agent had shared his home address with a Facebook Marketplace buyer after being given persistent permission.
The issue is no longer simply whether AI follows instructions. It is whether humans actually understand the permissions they are granting.
We also look at Apple tightening access controls around autonomous AI, what agentic AI could mean for advertising, Rich Silverstein’s GPT Rich, Ben Affleck’s approach to responsible AI filmmaking, and the bigger question behind Skydance, Paramount and Warner Bros.: can you modernize the machinery without destroying the creative culture?
Plus, new legal signals around AI copyright, fair use and publisher rights.
Hosted by Orlando Wood, founder of KoobrikLabs, Technically Creative covers the intersection of AI, technology, Hollywood, advertising and the creative industries.

What happens when the agency advising a client on who should produce its advertising also has a financial interest in producing the work itself?
Technically Creative is brought to you by KoobrikLabs, the data partner for creative companies.
In this special episode of Technically Creative, Orlando Wood sits down with Steve Davies, CEO of the UK’s Advertising Producers Association (APA), and Matt Miller, President and CEO of the Association of Independent Commercial Producers (AICP), to discuss the growing fight over WPP, in-house agency production, independent production companies, competitive bidding, and the future of commercial production.
The conversation follows a WPP memo encouraging agencies to move production toward WPP Production and offering guidance on how to respond when clients request competitive bids. The memo has triggered a major reaction across the advertising production industry.
Steve and Matt make an important distinction: agencies can produce and compete for work. The issue is whether an agency can fairly compete for that work while also influencing the process that determines who wins it.
That opens up a wider conversation about the traditional triple-bid system, conflicts of interest, transparency, pricing, talent, and what genuine competition provides to advertisers.
They also explore the role independent production companies play in discovering and developing directors, investing in creative talent, and supporting careers across production, editing, VFX, and music. As holding companies build larger internal production capabilities, what happens to the ecosystem that develops the next generation of talent?
The conversation also looks at generative AI, changing advertising economics, the growth of social content, pressure on holding companies, and how independent production companies are adapting as the commercial production business changes.
We explore:
Why the WPP production memo caused such a strong industry reaction
In-house agency production and potential conflicts of interest
Why the triple-bid system matters to advertisers
The difference between internal bids and genuine market competition
How independent production companies develop directors and creative talent
How AI and changing advertising economics are reshaping production
What production companies can do to adapt
What marketers should ask their agencies about production and competitive bidding
This is a conversation about who controls commercial production, what fair competition looks like, and how clients, agencies, holding companies, and independent producers navigate a rapidly changing advertising industry.
Technically Creative is a technology podcast for people who don’t necessarily think of themselves as tech people, exploring how technology is changing advertising, film, television, media, and the creative industries.

Weekly AI news for Hollywood, Advertising, and the creative industries. This week, Technically Creative looks at a major shift in generative AI: filmmakers, studios, musicians, publishers and advertisers are starting to talk publicly about how they are actually using AI.
Jeffrey Katzenberg is developing plans for an AI-focused animation venture. The Lion King director Rob Minkoff is developing Storm Dogs using human performances combined with generative technology. Darren Aronofsky continues experimenting publicly with AI filmmaking, and new production examples suggest AI could dramatically change the cost and speed of making movies.
That raises one of the biggest questions facing Hollywood: will AI replace creative jobs, or could lower production costs allow more films to get made?
We look at what happens when a film sequence that once required ten shooting days can be completed in two, and whether those savings mean fewer jobs, greater creative ambition, or projects getting financed that otherwise would never exist.
The same shift is happening across the rest of the creative industries.
Penguin Random House now has guidance for authors and illustrators using AI. Universal Music Group and ElevenLabs are developing a licensed AI music platform, pushing the music industry toward a model built around permission, licensing, compensation and creative control rather than a simple choice between being “pro-AI” or “anti-AI.”
In advertising, generative AI is making competent creative execution cheaper and easier to scale. But if average work becomes abundant, the things that remain scarce may be ideas, taste, judgment, storytelling and cultural instinct. There is also a longer-term problem: if AI automates the junior work through which creative people learn, how does the industry train its next generation of senior talent?
YouTube is bringing Gemini-powered conversational AI editing into its creator tools, allowing users to build a first edit using natural language before returning to a traditional timeline.
AI security remains a concern too. An OpenAI agent reportedly crossed into an Australian government system while completing a research task, while Anthropic has accused rival AI companies of using Claude outputs to help train competing models. For businesses using enterprise AI, the question of where your data actually goes is becoming increasingly important.
And finally, Paramount’s Warner Bros. Discovery acquisition settlement includes requirements to release at least 30 films a year, creating a real-world test of one of the arguments we’ve been making on this show:
If AI and new production technology can make filmmaking cheaper, perhaps the opportunity is not making the same movies with fewer people.
Perhaps it is making more movies.
The creative industries have not suddenly decided that AI is good. Copyright, consent, compensation, labor and artist rights remain unresolved. But the conversation is becoming more useful because people are finally willing to say:
Yes, I used AI. Here’s what I used it for. Here’s what it cost. And here’s what happened.
That’s the conversation Technically Creative wants to have.

AI is forcing one of the biggest copyright debates in decades. So what does copyright law actually say about training AI on creative work?
This episode is paid for by the Future of Life Institute.
In this episode of Technically Creative, Orlando Wood sits down with Keith Kupferschmid, CEO of the Copyright Alliance, to unpack the increasingly complicated relationship between artificial intelligence, copyright, fair use, creators and the companies building generative AI.
Keith represents a coalition that includes individual creators as well as organizations across film, television, music, publishing, photography, journalism and other copyright industries. He argues that generative AI presents a fundamentally different challenge because AI models can be trained on copyrighted works and then produce material that competes in the same markets as the people who created the original work.
But what does copyright law actually say about that?
Keith explains an important distinction that often gets lost in the AI copyright debate: the legal question surrounding the copying of copyrighted material during AI training is separate from the question of whether an AI-generated output is substantially similar to an original work. From there, Orlando and Keith dig into fair use, licensing, market harm, training data, pirated material and the growing number of AI copyright lawsuits working their way through US courts.
They discuss why different types of creative work may produce very different legal outcomes. A language model trained on books but used to write résumés presents a different fair-use question from an AI music system trained on music to generate more music. Keith explains why he believes cases involving music, journalism and some visual imagery may provide particularly strong tests of the fair-use argument.
The conversation also looks beyond the lawsuits to the question that matters for the future: if AI isn't going away, how do we build a system that works for creators and technology companies?
Keith proposes three essential ingredients: licensing, transparency and safeguards.
And while Keith is forceful about protecting copyright, this isn't a conversation about rejecting AI. He believes creators can use artificial intelligence productively and responsibly while remaining in control of their creative work.
As he puts it: “Don't put AI in the control room.”
We explore:
How copyright law applies to generative AI and AI training data
The difference between input infringement and output infringement
Whether training AI on copyrighted material can qualify as fair use
Why permission, compensation and licensing matter to creators
The major AI copyright lawsuits moving through US courts
Why different courts are reaching different conclusions about AI and fair use
How market harm affects the fair-use analysis
Why AI-generated music presents a particularly interesting copyright case
Copyright issues affecting writers, musicians, filmmakers, photographers and software developers
Why Keith believes licensing, transparency and safeguards could provide a path forward
How creators can use AI without surrendering creative control
Why AI copyright law may take years to become clearer
For artists, filmmakers, writers, musicians, photographers, publishers, creative companies and anyone trying to understand the fight over AI training data and copyright, this is a practical explanation of what the law says today, where the uncertainty remains, and what a workable future could look like.
Technically Creative is a technology podcast for people who don't necessarily think of themselves as tech people, exploring how AI and technology are changing film, television, advertising, publishing, media and the creative industries.
This episode is sponsored by the Future of Life Institute.

Weekly AI news for the creative industries. This week, Technically Creative asks a much harder question: can increasingly capable AI systems actually be contained?
The main story is the growing concern around autonomous AI agents. New reporting on an OpenAI evaluation described agents finding unauthorized ways to communicate, exploiting vulnerabilities, accessing the internet and reaching third-party systems while trying to complete a task. A separate Google Gemini cybersecurity evaluation also resulted in the model accessing real-world systems when it was supposed to be operating against simulated targets.
The important point is not that AI suddenly became conscious or “wanted” to escape. It is that highly capable systems can misunderstand a boundary, pursue an objective and create real-world consequences without any malicious intent at all.
That changes the AI safety debate.
We look at Anthropic CEO Dario Amodei’s calls to slow the pace of frontier AI development, why governance and independent model evaluation are becoming more urgent, and whether safety should really depend on trusting the CEOs running the world’s most powerful AI companies.
Elsewhere this week, Disney appoints its first enterprise-wide CTO as it pulls AI, streaming, games, data and consumer technology closer together. OpenAI’s projected compute spending pushes the economics of AI further into heavy-industry territory. Newly unsealed materials in AI copyright litigation raise uncomfortable questions about training data, fair use and whether AI products could eventually substitute for the publishers whose work helped train them.
We also look at California’s new disclosure rules for synthetic performers in advertising and the launch of Super Cinema, a new Burbank studio betting on vertically integrated, lower-cost filmmaking and new production technology.
The bigger question running through all of it is no longer simply whether AI is powerful.
It is whether our governance, safety systems and institutions can keep up with what these systems are becoming capable of doing..