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Stay ahead with the most recent breakthroughs—here’s what’s new and making waves in AI-powered productivity:

Luma Agents – End‑to‑End Creative “AI Collaborators”

Luma has launched Luma Agents, a new class of AI “collaborators” that can take a creative brief and execute work across text, image, video, and audio from start to finish. Instead of bouncing between disconnected apps, teams can let an Agent keep full context from the initial idea through planning, iterations, and final delivery, coordinating models and tools inside one unified system. For agencies, studios, and marketing teams, this promises faster campaigns, fewer handoffs, and more time spent on direction and taste rather than manual asset wrangling.

Picsart Persona & Storyline – AI “Faceless” Content for Creators

Picsart, the popular consumer photo and video editing platform, just introduced Persona and Storyline, two AI tools aimed squarely at the booming “faceless influencer” and UGC economy. Persona can generate and maintain consistent virtual characters while Storyline helps creators script and structure content arcs, with the platform automatically choosing the best underlying AI model (from providers such as VEO 3.1 and Kling 3.0) for each job. For everyday creators, this means it’s now easier to spin up a consistent on‑screen persona and plan a whole content series without needing studio‑level tools or editing skills.

Notion Custom Agents – Autonomous Workflows in Your Docs

Notion’s new Custom Agents (released in version 3.3) turn the familiar workspace into an autonomous workflow engine instead of a passive notes and docs hub. Users can define jobs, attach triggers or schedules, and let agents independently answer internal Q&A, route incoming requests into tasks, or generate recurring status reports by pulling context from Notion, Slack, email, and calendar. The feature is aimed at teams that want AI to quietly handle repetitive “glue work” in the background, freeing people to focus on decisions and deep work rather than constant manual updating.

Todoist Ramble – Voice‑to‑Task Capture for Busy Days

Task manager Todoist has rolled out Ramble, a voice‑to‑task feature that lets you talk naturally while the app turns your speech into structured, properly formatted tasks. Instead of stopping to type, you can dictate a messy thought or to‑do list and let Ramble parse dates, projects, and priorities into something your system can actually use. It is particularly helpful for people capturing ideas on the go or in the middle of focused work, where pulling out a keyboard is enough friction to forget the task entirely.

Dialpad Agentic AI Platform – Build and Govern AI Agents for Customer Work

Dialpad has announced major advances to its Agentic AI platform, focusing on letting enterprises identify high‑impact use cases, design specialized AI agents, and rigorously validate their behavior before deployment. The system supports autonomous voice and digital agents that can sit inside contact centers and support workflows, with governance features to test, monitor, and refine outcomes before exposing them to real customers. For operations and CX leaders, this is meant to bridge the gap between promising AI demos and reliable production agents that actually move metrics like handle time and customer satisfaction.

Luma Agents – Turning Briefs into Finished Creative Work

Luma Agents are positioned as AI teammates that understand a creative brief and stay with it from concept to delivery, instead of acting like one‑off generators you ping for isolated assets. Built on Luma’s “Unified Intelligence” architecture, the same underlying system can reason about a project, visualize ideas, and produce outputs across text, image, video, and audio in a single coherent process. The intent is to mirror how human teams actually think: keep context, try variations, and refine until a campaign or asset is ready to ship, rather than shuttling files through a chain of disconnected tools.

In practical terms, a marketing team might start by giving an Agent a campaign brief, brand guidelines, and target channels. The Agent can then generate concept options, draft scripts or copy, propose visual directions, and assemble early cuts of social clips or product videos—all while preserving decisions and feedback along the way. Because the system coordinates multiple models and tools behind the scenes, users interact with a single workspace that feels more like collaborating with a very fast assistant than juggling an ever‑growing tool stack.

The immediate benefit of this new capability is throughput: teams can explore more concepts, test more variants, and get to a finished asset in less time, without expanding headcount. Luma emphasizes that Agents can also self‑evaluate and refine their own outputs, using iterative critique loops to improve quality before a human ever sees the result. That means humans spend their energy on taste, strategy, and final approval, while the Agent handles the tedious in‑between work of stitching assets together and pushing projects forward.

For creative leaders, perhaps the most useful aspect of Luma Agents is that they treat entire workflows—not single files—as the unit of work. Because an Agent maintains full project context, it can adapt when a brief changes, propagate updates across every asset, and keep the latest direction synchronized without someone manually tracking all the moving parts. As more teams experiment with “agentic” AI, Luma Agents offer a concrete example of what it looks like when AI is a persistent collaborator embedded in the creative process, rather than an impressive—but isolated—demo.

The Creativity Question — Are We Co-Creating, or Are We Outsourcing Our Taste?

I like to think of myself as a creative guy, but something weird happened to me last week.

I was working on a piece of writing — not this one, a different one — and I hit that familiar wall. You know the one. The blank page isn't blank anymore, but what's on it feels flat. The idea is there, the structure is there, but the voice is missing. So I did what a growing number of writers, designers, and creators do in 2026: I asked an AI for help.

And it helped. It gave me three variations on my opening paragraph. One of them had a turn of phrase I genuinely liked. I tweaked it, folded it into my draft, and kept moving. The piece came together faster than it would have otherwise.

But later that night, I couldn't stop thinking about that turn of phrase. Was it mine? I'd asked for it. I'd recognized it as good. I'd shaped the prompt that produced it. But I hadn't generated it — not in the way we traditionally think about generating ideas. And that nagging feeling led me to a question I think every person using AI for creative work needs to sit with:

Are we co-creating with AI, or are we slowly outsourcing our taste?

The Case for Co-Creation

Let's start with the generous reading, because I think there's genuine truth in it.

Creative work has never been a solo act. Songwriters bounce ideas off producers. Novelists have editors who reshape manuscripts in ways the author couldn't see. Filmmakers rely on hundreds of collaborators to realize a vision. The myth of the lone genius sweating over a canvas in a garret is mostly that — a myth. Creativity, in practice, is collaborative.

From this angle, AI is just the newest collaborator in the room. And honestly? It's a pretty useful one. It doesn't get tired. It doesn't have an ego. It can generate a dozen variations on a concept in seconds, giving you raw material to react to. For a lot of creative people, the hardest part isn't having good taste — it's producing enough raw material to apply that taste to. AI solves that problem elegantly.

Think of it like a musician using a loop pedal. The loops don't write the song. But they create a texture the musician can play against, respond to, build on. The creative act shifts from pure generation to curation and response — and that's still a deeply human skill.

I've experienced this firsthand. When I'm writing and I use AI to brainstorm angles or rephrase a clunky sentence, the result still feels like mine. I'm the one who knows what I'm trying to say. I'm the one who recognizes when the AI nails it versus when it produces something generic. That recognition — that editorial instinct — is where the creativity lives.

The Case for Outsourcing

Now here's the less comfortable version.

There's a difference between using a tool and depending on one. A carpenter who uses a power saw is still a carpenter. But a person who can't cut a straight line without one might just be someone who owns a power saw.

The worry isn't that AI helps us create. It's that, used carelessly, it can atrophy the very muscles that make creation meaningful. When you always have a machine ready to fill the silence, you stop learning how to sit with the silence yourself. And that silence — the discomfort of not knowing what comes next — is where a lot of the most interesting creative work actually happens.

I've noticed this in small ways. When I have AI available, I'm less patient with my own bad first drafts. I used to let a terrible paragraph sit there for a while, trusting that my subconscious would eventually fix it. Now there's a temptation to immediately reach for the AI and say, "Make this better." And it does, technically. But "better" according to whom? According to a model trained on the aggregate patterns of millions of writers? That's not better. That's average — polished, competent average, but average nonetheless.

There's a term in economics called the "paradox of skill." As the general skill level in a field rises, the difference between participants shrinks, and luck (or in this case, distinctiveness) matters more. If everyone is using AI to smooth out their rough edges, then everyone's work starts to converge on the same smooth, capable median. The rough edges were what made things interesting.

This is where the "taste" part of the question gets sharp. Taste isn't just knowing what's good. It's knowing what's good for you — what fits your voice, your perspective, your weird specific way of seeing things. When you outsource the generation of ideas to a system that, by design, reflects the statistical center of its training data, you risk drifting toward that center yourself. Not because the AI forces you to, but because it's easier to accept its suggestions than to fight for your own strange instincts.

The Uncomfortable Middle

Here's what I actually think: both of these are true, and the difference between them is entirely about intention.

Using AI as a creative tool is like using any powerful tool. It amplifies what you bring to it. If you come with a clear vision, strong instincts, and the willingness to reject 90% of what the machine offers you, AI is an incredible creative accelerant. You'll move faster, explore more possibilities, and produce work that's genuinely yours — just more efficiently.

But if you come to AI with a vague sense of "make something good," you'll get something that looks good. It'll be coherent, well-structured, and utterly forgettable. Because you've handed over not just the labor of creation but the judgment of creation. And judgment is the part that matters.

I think about this a lot in terms of learning. When I was first figuring out how to write, the struggle was the education. Every bad sentence I labored over taught me something about rhythm, word choice, structure. If I'd had an AI fixing my sentences at 22, I might have produced better work in the short term — but I wouldn't have developed the instincts that let me produce good work now.

This is especially relevant for anyone who's still building their creative skills. If you're an experienced writer or designer or musician, AI is a force multiplier for skills you already have. But if you're still developing those skills, there's a real risk that AI becomes a crutch that prevents you from ever building the strength to walk on your own.

Some Practical Guardrails

I don't think the answer is to avoid AI. That ship has sailed, and honestly, these tools are too useful to ignore. But I do think it's worth being deliberate about how you use them. A few principles I've been trying to follow:

Generate first, then consult. Write your own rough draft before asking AI for help. This preserves the messy, generative phase where your best ideas emerge from. Use AI to refine, not to originate.

Reject more than you accept. If you're using most of what an AI gives you, you're probably not being selective enough. The creative act in AI-assisted work is curation, and good curation means saying no a lot.

Protect your weird. Everyone has creative instincts that don't match the mainstream. Those instincts are your signature. When AI suggests something smoother or more conventional, sometimes that's an improvement — and sometimes it's sanding off the exact thing that makes your work yours. Learn to tell the difference.

Take breaks from the tool. Periodically do creative work without AI, just to keep those muscles active. Write a draft longhand. Sketch without reference. Improvise without a backing track. The discomfort is the point.

The Real Question

Ultimately, "are we co-creating or outsourcing?" is the wrong framing — because it suggests a fixed answer. The truth is that every time you sit down to make something with AI, you're choosing one or the other, moment by moment, decision by decision.

The question isn't what AI does to creativity in the abstract. It's what you do with AI in the specific. Are you bringing your judgment, your taste, your willingness to be weird? Or are you hitting "generate" and accepting whatever comes back because it's good enough?

Good enough is the enemy here. Not AI itself.

The people who'll do the most interesting creative work in the next decade won't be the ones who avoid AI, and they won't be the ones who surrender to it. They'll be the ones who figured out where the line is — and who chose, deliberately and repeatedly, to stay on the right side of it.

That line is going to be in a different place for everyone. But if you're not thinking about where yours is, you've probably already crossed it.

Partner Spotlight: Duet Display

Duet Display transforms an iPad, Android tablet, Mac, or PC into a high‑performance extra display for your main computer, giving you more screen space for AI tools, dashboards, and creative apps without buying a new monitor. By offloading chats, reference docs, or timelines onto a second screen, users can keep their primary workspace focused, which is especially valuable when working with modern AI assistants, video editors, or complex browser workflows. Duet also supports touch and Apple Pencil input on compatible devices, making it useful for creators who want to sketch ideas, annotate AI‑generated assets, or mark up documents directly on a secondary canvas. Get more information or sign up at Duet Display.

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