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Operational Muscle: The Missing Key to Every Company's AI Strategy
Google’s new Gemini 2.5 tops charts, OpenAI releases new image model, and ChatGPT’s advanced voice mode got smarter.
Everyday AI
March 25, 2025
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Outsmart The Future
Sup y’all 👋
What a random Tuesday in AI.
Hot dang.
OpenAI got rid of Dall-E and introduced its next gen image generator
Google released the world’s most powerful LLM in Gemini 2.5
OpenAI updated its Advanced Voice Mode.
Which one should we cover next?
What should we cover next? |
You tell us what you want and we’ll dive in.
✌️
Jordan
(Let’s connect on LinkedIn. Tell me you’re from the newsletter so there’s no stranger danger.)
Today in Everyday AI
7 minute read
🎙 Daily Podcast Episode: Your company’s missing piece in its AI strategy? Operational Muscle. Listen Now.
🕵️‍♂️ Fresh Finds: Figure shows off AI-powered humanoid updates, why banks aren't seeing an ROI on GenAI yet and why AI is ruining hiring. Read on for Fresh Finds.
🗞 Byte Sized Daily AI News: Google’s new Gemini 2.5 tops charts, OpenAI releases new image model, and ChatGPT’s advanced voice mode got smarter. Read on for Byte Sized News.
🧠Leverage AI: How do you find the balance between AI processes and operational muscle? And how do you make it work for your business? An industry leader shares his secrets. Keep reading for that!
↩️ Don’t miss out: Did you miss our last newsletter? We talked about: OpenAI shakes up its leadership, Microsoft unveils new AI agents for cyber, new LLM test stumps top models.. Check it here!
Operational Muscle: The Missing Key to Every Company's AI Strategy
Muscles hurt first before you build em. đź’Ş
But once you build it, you're stronger.
Same can be true with company muscle.
And your org might be missing a key piece of the AI puzzle: Operational muscle.
Dive in with us to figure out how to build it from an AI industry vet.
Also on the pod today:
The 10-person rule 👨‍👩‍👧‍👦
Building operational muscle 🦾
The right way to start small 🤏
It’ll be worth your 30 minutes:
Listen on our site:
Click to listen
Subscribe and listen on your favorite podcast platform
Listen on:
Here’s our favorite AI finds from across the web:
New AI Tool Spotlight – Inferless helps you deploy Machine Learning models in minutes, Podcastle launched a suite of high quality AI voices, Jotform's new AI Agents organize requests to help you get stuff done.
Careers and AI — AI is making it hard for companies to actually hire qualified employees. What will happen?
Global AI Legislation — EU Lawmakers are sounding the alarm against dampening any AI legislation.
AI and Banking — Banks aren’t yet seeing ROI on GenAI. Here’s why.
AI Humanoids — AI Humanoid Company Figure showed off its latest robotic skills.
Introducing learned natural walking
Figure can now walk naturally like a human
Years of data was trained in simulation in just a few hours
— Figure (@Figure_robot)
2:02 PM • Mar 25, 2025
AI and Finance — AI-powered fraud tools are threatening auto lenders.
1. Google Unveils Experimental Gemini 2.5 Pro Model đź“Š
Google has just rolled out Gemini 2.5 Pro (experimental), codenamed “nebula,” as part of its latest AI model update for advanced users and developers.
This cutting-edge model introduces enhanced reasoning capabilities, multimodal comprehension, and a massive 1 million token context window, making it adept at tackling complex tasks like advanced coding and data analysis.
Scoring big on benchmarks like LMArena and Humanity’s Last Exam, it promises a transformative leap for businesses looking to scale with visually compelling apps and agentic code. Available now via Gemini Advanced and Google AI Studio, broader access—plus pricing details—is expected in the coming weeks.
2. OpenAI Rolls Out Native Image Generation in GPT-4o
OpenAI has introduced image generation directly into GPT-4o, combining advanced text and image understanding for sharper, more practical visual outputs. This new tool allows users to create photorealistic images, precisely render text, and refine visuals through conversation—handling up to 20 objects in a single scene, a leap from previous models.
It also integrates in-context learning, letting users upload and modify images while maintaining consistency across iterations. Starting today, this feature is available in ChatGPT for Plus, Pro, Team, and Free users, with API access coming soon.
3. ChatGPT Voice Mode Just Got Smarter 🎙️
OpenAI is rolling out a major upgrade to its Advanced Voice Mode, making conversations with AI feel more natural and less interrupted. According to OpenAI researcher Manuka Stratta, the update lets users pause or speak slowly without the AI cutting in, creating a smoother, more human-like interaction.
The feature, already available to free users and ChatGPT Plus subscribers, also includes an improved voice assistant personality. This marks another leap forward for AI tools, helping users communicate effortlessly—whether for casual chats or professional tasks—without overthinking how to phrase their thoughts.
4. Trump Administration Pressured to Ease AI Chip Restrictions 🖥️
Foreign officials and tech leaders are urging the Trump administration to loosen AI chip export rules ahead of a looming May 15 compliance deadline, according to Bloomberg.
The Framework for Artificial Intelligence Diffusion, initially introduced under Biden, sets strict limits on chip imports by tiered country classifications, sparking fears it could stifle innovation and investment globally.
Companies like Nvidia and Oracle argue the rules may harm U.S. competitiveness, with Nvidia calling them ineffective for national security. As debates continue in Washington, potential adjustments—like scrapping the tier system—could reshape AI development worldwide.
5. Virginia Governor Blocks AI Regulation Bill ❌
Virginia Governor Glenn Youngkin has vetoed a proposed bill aimed at regulating “high-risk” AI systems, citing concerns over its impact on innovation and small businesses. The legislation would have required companies to disclose AI uses, assess risks, and implement safeguards to prevent discrimination in critical areas like hiring and housing.
Critics, including tech industry groups, argued the measure would stifle startups while favoring corporate giants with larger compliance resources. According to Virginia Mercury, this decision leaves Virginia trailing Colorado in enacting comprehensive AI rules, while other states like California and New York weigh similar protections.
🦾How You Can Leverage:
Your company's AI failure isn't a tech problem.
It's a human one.
Andy Lin, VP of Strategy at Mark III Systems, shattered conventional wisdom during our in-depth convo today on Everyday AI.
While everyone obsesses over model size and GPU counts, Andy revealed the real AI success factor: "operational muscle" – the cross-functional human connections most companies completely ignore.
Companies waste millions on dormant AI hardware because they won't force different departments to collaborate on tiny projects first.
This insight could rescue your next AI initiative from the corporate graveyard.
So, how do you build that operational muscle?
Glad ya asked, shorty.
Here’s the big 1-2-3 from today’s convo.
1 . Why Half A Hospital Bed Beats Your Full-Factory Simulation 🛌
Most organizations get AI i mlementation backward.
They buy expensive tech first. Then wonder why nobody uses it.
Wrong move, shorty.
Andy told us the winning approach starts with what he calls "half a room" – sometimes just modeAndyg a single hospital bed with a cross-functional team. His most successful clients perfect that tiny digital twin before expanding one inch further.
Andy hammered home that organizations can build operational muscle without technology, but cannot succeed with AI if they start with technology instead of people.
This flips conventional implementation wisdom on its head.
Technology last, not first.
Try This Tomorrow, grab three people from departments that never interact (finance, manufacturing, IT, Ping Pong).
Give them 48 hours to build a paper prototype of your eventual AI goal. No computers allowed.
Their communication breakdowns reveal exactly where your organization lacks operational muscle. Address these specific weaknesses before spending another dollar on technology.
2. The 10-Person Rule That Breaks Every Org Chart 👨‍👩‍👧‍👦
Andy discovered successful AI implementations require 10 different specialists who've never worked together before.
He's talking about Operations Directors collaborating with machine learning engineers collaborating with HR Managers.
Developers partnering with medical professionals.
Subject matter experts teaming up with data scientists.
Traditional corporate structures can't handle this.
The companies struggling most with AI try molding everything at once without establishing cross-department communication protocols.
The successful ones start microscopically small and build what Andy describes as "sweat equity" through repeated tiny collaborations.
Try This Create a "collaboration map" identifying every department touching your AI project.
Schedule a two-hour workshop with one representative from each area.
Force them to build a physical model of their vision using only craft supplies. The places where they argue most?
That's your roadmap for where operational muscle needs development before writing a single line of code.
3. The "Andy Two" Technique That Eliminates AI Resistance 🧑‍🤝‍🧑
Andy shared a brilliant psychological framework that dissolves employee resistance to AI.
Or you can call it the Double Jordan.
We won’t be mad.
Imagine having a twin. What work does original you enjoy? What work does original you hate?
Then build an AI agent specifically to handle the tasks you dislike, preserving your control over meaningful work.
Andy stressed that employees should help create agents that amplify their strengths while eliminating their least favorite tasks. When team members design the AI that addresses their pain points instead of threatening their jobs, resistance vanishes overnight.
The key?
Human agency.
Successful implementations focus on building agency within teams rather than simply deploying agents.
Try This Identify one specific task your team hates but handles because it requires expertise.
Have them document their decision process, focusing on expert judgment calls.
Partner them directly with your technical team to design an AI agent that handles just that specific task.
Give them complete ownership over the agent's design. When they see AI eliminating soul-crushing work instead of their jobs, implementation succeeds.
The path to AI success isn't about specs or GPUs.
It's about building organizational muscles most companies don't know exist.
Start absurdly small.
Force uncomfortable collaborations.
Preserve human agency.
The operational muscle you develop now determines whether you'll lead or follow tomorrow.
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