Hi! Welcome to the 26th edition of the TomorrowToday newsletter.

We’re here to decode the AI chaos so you don't have to. Think of us as your friendly neighbourhood tech translators - we cut through the chaos, translate the jargon, and spotlight new AI tools that matter for founders, builders, and curious minds.

Buckle up, because the future's moving fast and we're here to make sure you don't get left behind! ⚡

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/Automation /Enterprise /Productivity /Workplace

Here's the thing about automation tools like Zapier and n8n—they're brilliant, but they're also a bit like learning a new language. Even though they're "no code," you still need to understand logic flows, conditionals, and how to wire everything together. Most people look at them and think, "This is too hard, I'll just do it manually."

Google just solved that problem with Workspace Studio, which launched into general availability this week. Instead of learning automation syntax, you literally just describe what you want in plain English. Say something like "Flag emails from my boss as important and move them to a folder" or "Generate a weekly summary of my Google Drive files and post it to Chat," and Gemini builds the agent for you. No learning curve, no special training needed.

The big difference? Workspace Studio agents actually understand context. They're not just following IF-THEN rules, they can reason through problems, pull information from your real documents and emails, and adapt to new situations. Early testers saw some serious wins. Kärcher, the cleaning company, used it to automate their internal product-planning workflow and cut manual planning time by 90%. Let that sink in.

Rolling out over the next few weeks for Google Workspace customers in South Africa and globally, with promotional access to higher usage limits while they're still in the experimental phase.

/Video /Production /ContentCreation

Here's where the story gets interesting. Last week, Kling (the Chinese AI video model from Kuaishou) dropped version 2.6, and for the first time, they've genuinely one-upped Google and OpenAI on something specific: they've built audio generation directly into the video creation process.

Unlike Google Veo 3.1 and OpenAI's Sora, which bolted audio on as an afterthought, Kling 2.6 generates video and audio simultaneously with perfect synchronisation. Think cinematic dialogue that matches mouth movements, sound effects that hit on the exact frame they should, and background music that swells at the right moment. All in one go.

Here's the pricing comparison that matters: A 10-second Kling 2.6 video costs 100 credits at standard rates. Google Veo 3 costs significantly more per second, and Sora pricing is comparable or higher, depending on your plan. But here's the kicker: Kling 2.6 is 30% more efficient than their own previous version, which means you're getting better quality for less. Plus, it handles bilingual output (English and Chinese), which neither of its competitors does natively.

The real impact? If you're making product demos, social content, or short-form videos, Kling is becoming the go-to choice for creators on a budget who don't want to compromise on quality. This isn't about being "almost as good"—in some ways, particularly camera movement and motion consistency, Kling's actually ahead.

/Research /Enterprise /Workforce /Methodology

Anthropic published something genuinely interesting this week that doesn't get the hype it deserves. They built a tool called Anthropic Interviewer and used it to conduct more than 1,250 interviews with professionals about their relationship with AI at work. The kicker? The AI itself ran the interviews.

This isn't just clever; it's a glimpse at how AI might transform research at scale. They had Claude conduct real-time, adaptive interviews with scientists, creatives, and general workforce professionals. No scripts, no bias, just genuine conversations about how AI is changing people's jobs. The results are remarkably honest: creatives love the efficiency gains but worry about displacement, scientists want AI that can generate hypotheses (it can't yet), and most people in general roles want to keep the human stuff while automating the admin.

The finding that stood out to us? Most professionals see their future working alongside AI, keeping the decision-making and human touch, delegating the repetitive tasks. But there's tension: 55% worry about their future, yet 86% say AI saves them time. It's the kind of nuanced data you don't get from surveys.

What matters here is the precedent. This is the first time AI has been used at this scale for qualitative research. You can participate in the ongoing study here if you want to add your voice.

In this section, we aim to spotlight an incredible AI tool or use case and guide you on how you can try it.

This week’s challenge: Design a Stunning Brand Campaign Using Freepik's New Spaces Tool

What if you could build a complete creative campaign - from concept to final design - without jumping between five different apps? That's essentially what Freepik Spaces does. It's a canvas-based AI workspace where you connect visual "nodes" (think: building blocks) to create, iterate, and collaborate on creative projects in one place.

Think of it as Figma meets Zapier for creatives. Instead of exporting from one tool and importing to another, you're building a visual workflow where each node performs a specific creative task: generating images, refining them, adding text, synchronising with team members. You can save workflows, iterate on them, and reuse them for future projects.

Here's how to create a Nike shoe ad campaign in Spaces:

The beauty? You're not switching tools. You're not dealing with version control chaos. It's one canvas, one workflow, all your creative decisions visible and reversible.

You spoke, we listened. “AI in Enterprise” is here to stay. In this section, we're spotlighting real businesses using AI to solve actual problems.

How Brands Are Breaking Free From Big Ad Budgets

The Landscape:
AI is officially changing TV advertising - but not in the way you might think. It's not replacing human creatives en masse. Instead, it's demolishing the gatekeepers who've been saying you need a six-figure budget to play in prime time.

The Evidence:
This year's Super Bowl saw multiple AI-driven ads from OpenAI, Google, and Meta. But the real story isn't those polished corporate spots. It's the Kalshi NBA Finals commercial that aired during Game 3 in June 2025.

Here's the math: A typical national TV ad costs USD $250K–$500K to produce. Kalshi's 30-second spot, created entirely with Google's Veo 3, cost $2,000 in production (plus creative fees) and took two days to make. The creator, PJ Accetturo, generated 300–400 AI clips, cherry-picked the 15 best ones, and edited them together using CapCut and Premiere. The result was chaotic, unhinged, absolutely unmissable, and it racked up 3+ million views on social media alone.

Meanwhile, the Toys R Us Approach:
Toys R Us created a more polished AI ad using OpenAI's Sora, showing the origin story of founder Charles Lazarus. It took a few weeks, cost significantly less than traditional production, and sparked both praise and criticism for being too "uncanny." But the point stands: they made a national-level commercial without traditional actors or crews.

What's Actually Changing:
According to Gartner research, 90% of retailers will deploy generative AI in marketing within the next two years. The main benefit? Personalisation at scale and rapid testing. Why create one expensive ad and hope it works? Create five variations in a week, test them with small audiences, kill the duds, and amplify the winners. AI lowers the cost of experimentation so dramatically that the economics of advertising are shifting.

AI is full of jargon, and we’re here to decode it. Each week, we’ll give you a plain-English definition of a buzzy term you’ve probably seen (but never fully understood).

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