Growth leaders are about to face AI memory, AI oversight, and machine-speed creative all at once.
Claude and ChatGPT are experimenting with memory. If they get it right, we’ll finally have AI teammates that actually remember campaign goals instead of acting like goldfish. At the same time, some models are starting to prompt themselves, which is equal parts useful and unsettling.
Regulators are moving in on AI agents. Oversight is shifting toward advertisers and publishers, and it will show up directly in budgets and compliance work.
Meta rolled out new brand tools, giving marketers more control over creative and targeting. Startups are racing in the opposite direction, building “ad factories” designed to crank out campaigns at machine speed.
Also, AI video keeps getting better, which is already reshaping how fast teams can move from idea to execution.
My takeaway: speed is going up, but so are the stakes. Growth leaders need to decide how to put these tools to work without creating new risks.
Let's get into this week's stories.
Patrick Patterson
CEO at Level Agency
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What's interesting this week
Models That Prompt Themselves Models can now generate and refine their own prompts. The AI you use tomorrow won’t just answer, it will steer. For business leaders, this creates leverage. Workflows will need transparency to surface reasoning if you want to trust the output. Read more
AI Oversight Arrives for Publishers and Advertisers Regulators are starting to scrutinize AI agents. Publishers and advertisers will need oversight layers for compliance, transparency, and bias. For growth leaders, this is a cost of scale. Building governance early avoids bigger problems later. Read more
Meta Adds New Brand Tools Meta is giving brands more ways to tweak creative and targeting inside Facebook and Instagram. This matters because faster adjustments reduce wasted spend. Add AI automation, and teams can scale campaigns with more precision and less effort. Read more
Claude vs ChatGPT Memory Compared Claude and ChatGPT are taking different approaches to remembering your context. For growth leaders, this isn’t about trivia. It’s about whether your AI teammate can recall customer history, campaign goals, and strategic intent. The models are improving, though memory is still fragile. Read more
Inside AI Video Generation Video generation looks like magic, but under the hood it’s diffusion models, transformers, and heavy compute. The speed of adoption for training, ads, and product explainers is striking. Workflows are already forming where AI drafts and humans polish. The economics flip overnight. Read more
Developers as AI Babysitters Vibe coding has senior developers calling themselves AI babysitters. The metaphor is accurate. AI delivers 80 percent of the work, and developers finish the job. For growth teams, this shift means more time spent on quality control and less on building from scratch. Read more
Deep dive: AI
How MCP could finally unify your AI workflows
MCP, or Model Context Protocol, is a technical idea with big practical consequences. It creates a standard way for AI models, tools, and data sources to communicate. Think of it as APIs redesigned for the AI era, where context is the real currency.
In practice, that means fewer fragile integrations. Imagine your AI assistant accessing live performance data from your ad platforms, blending it with pipeline data from your CRM, and pulling in competitive signals from market reports. Instead of duct-taping connectors together, MCP provides one common language.
This also matters for control. Publishers can decide what tools AI models are allowed to see and use. That changes the balance of power between content owners and AI systems that are constantly scraping and summarizing.
For growth leaders, the play is to get ahead of this shift. Ask your vendors how they’re preparing for MCP. Build scenarios where your data and tools can talk seamlessly. This protocol could reduce friction across marketing, finance, and ops in ways that feel invisible until suddenly they’re game-changing.
How to make your brand visible in the age of AI search
Search is changing from ten blue links to one AI-generated answer. That shift means brand visibility inside AI outputs is now critical. Tools like Ahrefs’ Brand Radar give a glimpse into how often AI assistants mention or recommend a brand. It’s like share of voice for the AI era.
Here’s the key insight: if your brand isn’t appearing in AI-generated answers, you’re effectively invisible to customers who rely on these tools for decisions. That risk compounds quickly as AI adoption spreads. Visibility isn’t just about SEO anymore, it’s about being recognized as an authority source that AI finds trustworthy.
The next move for leaders is straightforward. Monitor your mentions across AI outputs. Identify where competitors are appearing and you are not. Build content velocity around the themes, questions, and categories where you want to show up as the definitive answer.
This is no longer a side project for marketing. It’s a core visibility metric. Every CMO should treat AI share of voice the way they once treated organic rankings.
Predis.ai is like having a junior creative team that never sleeps. It generates ad creative, UGC-style clips, product videos, and social posts, then pushes them straight into Facebook, Instagram, TikTok, YouTube, LinkedIn, and more.
Growth today is about velocity. You need creative variants to test, you need content formatted for each channel, and you need it yesterday. Predis makes that cycle fast without turning your team into production zombies.
It won’t replace big-budget creative, but it will cover the endless need for fresh, “good enough” assets that drive experiments forward. For leaders who want to scale creative output without increasing headcount, this is worth testing.
Ready to turn AI into ROI?
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