“Here’s a new episode of The Reddy Rundown, crafted so you don’t have to frantically follow everything in the AI news space wondering what you are missing as a an exec in 2025 trying to keep up

”I am Shawn Reddy. CEO and Founder at AI Advantage Agency. I think like a systems first marketer who now runs a company. My bias is simple. Marketing is powered by systems and those systems are now AI. This week’s news pushes three levers that matter to every executive who cares about growth. Speed. Credibility. Cost.

1. Stanford’s virtual AI lab is the blueprint for faster product marketing

Researchers spun up a team of AI agents that propose ideas, critique each other, and drive experiments with minimal human input. They already produced real candidate molecules and published agent transcripts for review.

My take

• Treat this as a pattern for your own R and D in marketing. Use agents to draft claims, generate counter arguments, and design tests in minutes, then have humans approve.

• Make compliance part of the loop. If you are in a regulated space, log agent reasoning and add a human sign off before anything touches a customer.

• The practical move this quarter. Build a small agent swarm to produce copy variants and offer tests tied to a single goal like booked calls or first reply time. Measure lift and cut what does not move the metric.

2. Meta is throwing absurd money at Thinking Machines Lab talent

Reports say Meta is making eye watering offers to recruit from Mira Murati’s new startup. Some declined. That tells you two things. The talent war is escalating. The best people want a clear roadmap more than money.

My take

• Expect faster model supply and lower prices as big players chase share. That compresses the advantage of model choice. Your edge becomes orchestration.

• Plan for volatility. If Meta ships a stronger model or cuts infrastructure pricing, you need a clean switch path. Keep a model harness and a rollback plan.

• Messaging risk is real. If you lean on open claims, be ready to defend data usage and safety choices. Prepare a plain language trust page before the first press request.

3. ChatGPT Study Mode changes how education brands market and sell

OpenAI rolled out a mode that teaches with questions and checks for understanding rather than giving instant answers.

My take

• If you sell learning, this is a retention tool. Build guided study plans that keep learners inside your ecosystem while ChatGPT does the tutoring.

• If you sell anything complex, borrow the pattern. Replace cheat sheet chatflows with guided discovery that leads prospects to the right package and books a call.

• Success depends on buy in. Add progress markers, reminders, and a visible outcome at the end. People need a reason to stay with the process.

4. Qwen 3 Coder is a credible open source coder for internal velocity

Alibaba’s coder model gives you a million free tokens and real power without a subscription.

My take

• Use it to cut engineering wait time on marketing work. Landing page tweaks. Tracking fixes. Data cleaning.

• Keep it inside a safe repo and require code review. Speed without guardrails creates cost later.

• Financial sanity check. For teams that only need periodic code help, this can replace a chunk of paid tokens with zero drop in output quality.

What I would test this week

1. Ship an agent led test loop for one funnel stage. Let agents propose, you approve, then run a rapid two week cycle with hard kill rules.

2. Build a model harness that lets you swap providers in a day. Include a one click rollback.

3. Launch a trust page that explains your model choices, data handling, and audit trail in plain English.

4. Turn one static guide into an interactive study path that ends in a booked call or a trial.

Tools I am trying and how I would use them

Qwen 3 Coder Use case for marketing. Generate and refactor tracking scripts. Build small internal tools that transform CSVs. Draft page components that your engineers review and ship.

ChatGPT Study Mode Use case for marketing. Turn your onboarding or product education into a guided path inside chat that checks understanding and upsells the right tier at completion.

Vertex AI and Google for Startups Cloud credits Use case for marketing. Cheap runway for experiments. Stand up a private model endpoint for your chatbot and quoting agent. Track cost per answer and deprecate anything that does not beat existing support macros.

Agent lab pattern from the Stanford paper Use case for marketing. Create a three agent loop inside your content pipeline. One agent proposes the angle. One agent attacks it for accuracy and risk. One agent turns the final into variants for email, page copy, and social. Human approves. Everything is logged.

The CEO view

Model drama makes headlines. System design wins P and L. You cannot outsource this. Pick a short list of use cases that touch revenue. Instrument them. Swap models when they improve the metric. Kill vanity experiments fast.

Looking for a community of like-minded individuals who are interested in AI and Entrepreneurship? Join our free community here to get started: The AI Advantage Community Thank you for reading! -Shawn