Today, we’re bringing you the latest in AI-powered marketing and business strategies. Here’s what’s inside:
🚨 AI Top Story: The mechanics behind multi-agent AI are already in place—now it’s just a matter of putting the right interface on top.
🌟 Creator Spotlight: A sneak peek inside OpenAI’s official GPT-5 prompting guide—shared by How To Prompt and packed with practical gems.
🎯 Killer Marketing Prompt: Practice handling objections in real time with a voice-based AI roleplay. Perfect for sharpening your pitch and pressure-testing your messaging.
🎥 AI YouTube Resource Of The Week: What You Should Use GPT-5 For & More AI Use Cases
Multi-Agent Setups Are Real And Ready
Teams of AI Agents Are Now a Real Thing
A lot of the AI tools people are familiar with today still feel like single-task systems. You give them a prompt, they give you an output - one input, one response, one model doing the heavy lifting.
It works well for straightforward use cases, but it starts to fall short when you’re trying to manage more complex or multi-step workflows. Instead of one model trying to handle everything, we’re starting to see AI agents working together, each focused on a specific role, passing tasks between them like a team would.
This idea is at the core of what’s known as multi-agent workflows. One agent might map out a strategy, another writes code, a third evaluates the results, and another one troubleshoots or optimises.
They're not all operating in isolation either - these agents can communicate, share context, and make decisions based on what’s happening in the workflow. Instead of just automating individual tasks, the goal is to build more thoughtful systems where different agents actively contribute to a larger process, each one handling what it does best.
Developers are already testing these systems in some pretty advanced ways. Teams are building multi-agent setups where one agent writes code, another reviews it for errors, a third handles deployment, and others run tests or suggest improvements - all with minimal human input.
Some agents are even able to call external tools, manage files, or communicate via APIs to get things done. It's not polished or plug-and-play yet, but it’s functional enough to build real products faster than ever before. Most of this is still happening inside GitHub repos and experimental environments, but the mechanics are starting to solidify.
For marketers, this points to a future where AI agents could take on creative production in a similar way. Imagine one agent writing ad copy based on a brief, another generating image variations, a third evaluating previous campaign performance to inform direction, and a fourth setting up A/B tests or building out landing pages.
Campaigns aren’t made in a single step. There’s research, concepting, creative development, copy, design, distribution, testing, and analysis. Multi-agent workflows offer a way to split these tasks up and let different agents take ownership, without trying to cram everything into a single prompt or relying on manual handoffs between tools. It’s a more flexible, modular way to build with AI, and it has the potential to make creative production and performance optimization faster and more consistent.
This isn’t mainstream yet, and it’s not something you’ll find built into your favorite tools overnight. But the foundations are already there, and the speed of experimentation in this space is hard to ignore.
It’s worth starting to think beyond single-task prompting and begin imagining how AI could work more like a collaborative system, one that mirrors how real teams operate.
🤫 Confessions: Inside a marketing executive’s ‘intimate, complicated’ relationship with AI - A marketer gets candid about how AI feels like a trusted ally—but one they still question, revealing the messy, personal side of embracing AI in creative work.
💬 OpenAI CEO says ads could be added to ChatGPT as the company explores new monetization options - The head of ChatGPT didn’t shut the door on ads, hinting at cautious monetization moves, yet promises any ads would respect user experience and purpose.
👨💻 Anthropic adds coding lessons and learning modes to Claude AI chatbot - Claude’s new learning mode turns it from answer-producer into a patient teacher; walking you through how code works, not just giving you the solution.
🚀 AI Agents Are Joining Your Team. Are You Ready To Manage Them? - A Forbes piece that puts the spotlight on a question all managers will face soon: how to coordinate teams that include AI agents alongside humans.
Roleplay to a Skeptical Buyer (in Voice Mode)
Use this to practice handling tough questions from a doubtful customer - out loud. Great for refining your messaging, stress-testing your pitch, and preparing for live calls or presentations.
Let’s role-play a conversation. You’re a skeptical customer considering [product/service]. You’re not convinced it’s worth the money, you’re unsure it will deliver real results, and you’ve seen other tools make similar promises.
I’m a marketer/salesperson at [company] selling [product/serivce] trying to answer your questions and help you feel confident.
Speak to me naturally, one objection at a time. Wait for my response before continuing. Keep it conversational and realistic. When you’ve heard enough, let me know your final decision—whether yes or no.
When you’ve heard enough to decide—yes or no—end the conversation. After that, give me clear feedback on how I could improve my messaging, build more trust, or respond more effectively next time.
Servers must love it when schools out..
