Here is a new episode of The Reddy Rundown, crafted so you do not have to frantically follow everything in the AI news space wondering what you are missing as an exec in 2025 trying to keep up.

I am Shawn Reddy, CEO and Founder at AI Advantage Agency. I build marketing systems that ship. I care about creative that works and the plumbing that makes it repeatable. Below is what actually matters for operators and why it moves budget, process, and performance.

META FAIR: predicting how the brain reacts to video

Meta’s FAIR team introduced TRIBE, a roughly one billion parameter model that predicts brain responses to movies using video, audio, and text. It performed best in regions tied to vision, sound, language, and attention.

My take

If attention is the currency, this is an early map of where to spend it. Creative testing will shift from only watching watch time to predicting cognitive lift before you ever run an ad. Think attention heatmaps for storyboards and trailer cuts. The marketing edge will come from teams that tag scenes and dialogue with ruthless consistency so models have clean inputs. Guardrails matter. You do not want to wander into creepy. Use it to reduce wasted iterations, not to manipulate.

Move now

Tighten your content taxonomy. Shot lists, transcript tags, and intent labels should be standard. Run smaller creative batches and score them against predicted attention profiles before you scale.

OPENAI: a reasoner that medals at real contests

OpenAI’s general reasoner placed at the top tier of the International Olympiad in Informatics and has wins across math and coding tasks.

My take

Benchmarks are bragging rights. Reliability is revenue protection. I do not care that a model solved a hard puzzle unless it holds up inside a messy funnel. The useful shift is consistent planning and tool use. This enables agents that write experiment code, check analytics, then stop when a metric drifts. Treat it like a sharp intern with perfect recall and very little judgment. Pair it with evaluation sets and stop loss rules.

Move now

Maintain two execution paths. One human led baseline. One agent assisted. Compare cycle time and defect rates weekly. Keep a rollback plan ready.

MUSIC GEN WITH CONTROL: production quality sound on demand

ElevenLabs rolled out a music model that lets you prompt, generate multiple variants, edit sections, and export studio quality tracks.

My take

Audio identity is underused. Most brands spend on visuals and settle for stock music. This flips the economics. You can test five hooks for an ad or podcast bed in an afternoon, then lock the winning motif across channels. Legal still matters. Lock your license terms. Track usage in your asset library so teams do not go rogue.

Move now

Create a small sound kit for your brand. Intro, outro, three mood beds, five short stings. Test for recall in short form video and pre roll.

ENTERPRISE DATA REALITY CHECK: Lockheed and IBM focus on cleanup

Lockheed Martin boosted AI output after cutting tool sprawl and standardizing data on a single system with watsonx.data.

My take

Most marketing teams do not need another tool. They need a clean data layer and fewer dashboards. Unifying events, spend, and outcomes will do more for CAC and LTV than any shiny model. If you cannot reconcile revenue to campaigns within a day, fix the pipe before you add more agents.

Move now

Pick one data layer to be the source of truth. Define a shared schema for campaigns, offers, and stages. Kill overlapping tools. Document how numbers roll up.

KAIST DRUG DESIGN: fast science means tighter claims

Researchers at KAIST showed an AI system that designs drug candidates from scratch and optimizes for safety and manufacturability.

My take

The point for marketers is not pharma. It is pace. Domain specific models will flood regulated categories. That creates pressure to publish findings faster and to update claims calendars more often. Brand trust will hinge on how clearly you separate education from promotion. Teams need an evidence review loop that is fast and boring.

Move now

Stand up a claims board with legal and product that meets weekly. Pre write explainer content with clear sourcing. Use agents to assemble literature, then require human approval before anything touches public channels.

The through line

Systems beat stunts. The winners will be the companies that pair creative taste with clean data, reliable agents, and simple rules. I am biased. I am a systems guy who loves good storytelling. The job now is to reduce time to truth and raise the floor on quality.

Tools I am testing and how I would use them

1. Lindy meeting prep agent - Marketing case: auto build pre call briefs with CRM context, last touch interactions, risk prompts, and three tailored talk tracks for each persona

2. Vanta AI Security Assessment - Marketing case: turn security questionnaires into a public trust asset. Publish a living security summary and route enterprise objections to approved answers

3. OpenAI workspace with tone guard - Marketing case: enforce brand voice across outbound, support, and product updates. Score drafts for clarity, claims, and risk before they reach review

4. IBM watsonx.data or any unified lakehouse - Marketing case: collapse campaign and revenue data into one store. Standardize your metric definitions so agents can run analyses that finance trusts

5. Vertex evaluation sets - Marketing case: build repeatable tests for your agents and prompts. Score against acceptance criteria for brand voice, safety, and task success before rollout

Operator checklist for this week

• Tighten your content and data taxonomy so models have something sane to learn from

• Run a two path experiment where agents assist one lane and humans lead the other. Compare cycle time, cost, and error rates

• Build a small audio identity kit and test it across ads and short form

• Create a lightweight claims and evidence routine if you operate in regulated spaces

If you want my playbooks for standing up the data layer or the evaluation sets, reply and I will share the templates.

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