Jul 24, 2025
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 an exec in 2025 trying to keep up.
I’m Shawn Reddy—CEO of AI Advantage Agency. I don’t chase headlines for sport; I’m a marketing architect who treats AI like infrastructure. The question I ask every week: Does this change how we attract, convert, or retain customers—and how fast can I wire it in?
1. America Goes “All Gas, No Brakes” on AI — What That Means for Your Funnel
The move: The Trump administration just dropped a 28‑page AI Action Plan with 90+ actions—ripping out regulatory friction, pumping cash into data centers, cheering open source, and even mandating “objective” (read: ideology-policed) AI models for government contractors.
Why marketers should care:
Cheaper, faster infra = new toys sooner. Expect a flood of “enterprise-grade” tools priced like SaaS, not SAP. If your competitors can spin up agents in days, your cycle time just shrank—again.
Open source gets oxygen. Translation: more customizable models you can host/control. If brand voice and data privacy matter, this could be your chance to own your stack instead of renting GPT access forever.
“Bias policing” will be a marketing landmine. Every “objective AI” claim will be scrutinized by customers and press. If you sell AI features, get ahead of the messaging: show your evaluation framework, not just your ethics slide.
My move: I’m doubling down on modularity—swapping key model dependencies so policy swings don’t stall feature roadmaps. If you can’t re-route inference in a week, you’re one executive order away from downtime.
2. Google DeepMind’s Aeneas Restores Ancient Rome—And Hands Us a Content Playbook
The move: DeepMind launched Aeneas, an AI that reconstructs shattered Latin inscriptions, dates them within 13 years, and pins provenance with 72% accuracy. It’s open-sourced, tested by 23 historians, and actually useful.
Why marketers should care:
Pattern: AI as “context restorer.” This is the same tech arc you need for messy CRM notes, call transcripts, or 6-year-old blog posts. If it can rebuild a Roman decree, it can rebuild a customer journey.
Brand story angle: “We help you make sense of fragments” is a killer narrative for any data-rich product. Don’t just say “AI-powered knowledge base”—show the before/after like DeepMind did.
My move: I’m stealing the “scholar + model” model. Let your SMEs validate your agent’s output and bake the feedback in—then market the partnership, not just the model.
3. OpenAI’s Clinic Copilot Cuts Errors in Kenya — A Blueprint for “Assist, Don’t Replace”
The move: OpenAI + Penda Health ran a 40K-visit study in Nairobi. Clinicians using an AI consult copilot made 16% fewer diagnostic errors and 13% fewer treatment mistakes. Doctors stayed in control; the AI flagged issues, didn’t dictate care.
Why marketers should care:
Workflow-first integration wins. The copilot sat inside the decision flow. That’s your lesson: wedge AI where work already happens (Salesforce, Slack, EMR) instead of making users tab-hop to a chatbot.
Proof > promise. They published metrics and clinician quotes. If you’re selling AI outcomes, stop hand-waving and start instrumenting error rates, cycle times, and win rates.
My move: Our agents report “hours saved” and “response quality deltas” by default. If you can’t show the delta, your AI is a toy, not a tool.
4. Altman Says “AI Fraud Is Coming” — Translation: Trust Becomes a Feature
The move: Sam Altman warned that AI has already nuked the authentication methods banks rely on. Deepfakes will do to signatures what email did to direct mail.
Why marketers should care:
Verification UX is now part of your brand experience. Expect customers to ask, “How do I know it’s actually you?” Add verification layers (voiceprints, signed tokens, known device checks) without adding friction.
Content authenticity will be a differentiator. Watermarks will lag adoption. Real-time human touchpoints (short personalized loom, unique CTA paths) will matter more.
My move: I’m building “human proofs” into high-value sequences—quick founder videos, unique token links, and agent logs clients can audit.
5. Pew: Users Click 50% Less When AI Summaries Show — Goodbye Old SEO, Hello Answer Packs
The move: Pew Research reports Google users click half as often when an AI summary sits on top.
Why marketers should care:
Your “top 3 snippet” playbook is toast. You need content built as “answer surfaces”—structured FAQs, prompt-ready snippets, and code blocks that AI agents can lift cleanly.
Brand still matters. When clicks drop, recognition matters more. Your name needs to be in the summary. That means schema markup, consistent naming, and a real POV.
My move: I’m packaging content into “AIO Packs”—modular chunks that models can copy without mangling context. Then I measure how often we’re cited, not just how often we rank.
Quick Hits (Still Worth a Funnel Move)
YouTube Shorts gets photo→video + Veo 2 Effects. Cheap vertical content just got cheaper. Batch 10 hooks, let the tool animate, then test retention curves.
Google Photos adds AI “Remix” video tools. Internalize this: every employee is now a content editor. Train them on your brand kit or you’ll get Franken-content.
GitHub Spark (Claude Sonnet 4 under the hood) goes public preview. Ops teams can spin internal tools from prompts. Marketing ops: build scrapers, data cleaners, and reporting dashboards without bugging eng.
Amazon shutters its Shanghai AI lab. Vendor risk is real. If your provider’s core team can be reorganized via geopolitics, build fallback paths.
Slack’s Agentforce arrives. Agents inside Slack, grounded on your convo history. Use it to surface “what did we promise that client?” in seconds (see tool list below).
Conveyor claims 95%+ accuracy on security questionnaires. Sales ops dream: free your SEs to actually sell.
The Toolbox (Links + How I’d Actually Use Each in Marketing)
Agentforce for Slack (Salesforce) – Drop an agent into your team’s main channel to auto-summarize client threads, flag missed follow-ups, and draft renewal nudges. (Link: search “Agentforce Slack Salesforce”) → Marketing use: turn Slack into a living CRM sanity check.
Claude + Canva Connector – Rapid-fire branded asset generation. Spin a launch kit (IG post, banner, deck) from one prompt. (Link: search “Claude Canva Connector tutorial”) → Marketing use: enforce brand consistency while cutting creative turnaround to hours.
Conveyor Customer Trust Platform – Automate security questionnaire hell. (Link: search “Conveyor AI security questionnaire”) → Marketing use: shorten enterprise deal cycles; your “we’re secure” proof becomes a one-click experience.
GitHub Spark (Claude Sonnet 4) – Non-dev teams can prototype internal tools. (Link: search “GitHub Spark Copilot Pro+”) → Marketing use: build mini lead enrichment bots or reporting pipelines without begging engineering.
YouTube Shorts AI Effects (Veo 2) – Turn static product shots into motion assets for Shorts/IG Reels tests. (Link: YouTube Creator Blog) → Marketing use: scale top-of-funnel creative iterations cheaply, then double down on the winners.
Google Photos AI Remix – Repurpose user-generated content into campaigns. (Link: Google Photos update 2025) → Marketing use: remix customer photos into testimonial vids without a video team.
Pew Report on AI Summaries & Click Behavior – Rethink your content ops. (Link: Pew Research AI summaries click-through) → Marketing use: shift spend from “rankings” to “citation capture” and branded answer cards.
DeepMind Aeneas (Open source) – If you manage archives or legacy content, run your own “Aeneas” to resurrect evergreen assets. (Link: DeepMind Aeneas GitHub) → Marketing use: revive old webinars/blogs into promptable knowledge blocks for agents.
OpenAI + Penda Health Copilot Study – Case study template for your own AI rollout. (Link: OpenAI blog Penda Health study) → Marketing use: prove your AI feature actually moves a KPI, then market the proof, not just the feature.
Final Take
Every headline this week points to the same truth: your marketing edge is now your systems edge. Policy shifts change cost curves. Research labs hand you new primitives. Product teams keep shipping “assistant-in-the-flow” features. The exec who wins isn’t the one who “uses AI,” it’s the one who instruments, measures, and iterates faster than the rest.
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
