🚨 AI Raises the Stakes
Grok Goes Gov, Perfecting Your Pictures, and Keeping Connected Systems
“Wondering leads to wonder.”
—Carlos Whittaker, Author
The AI Breakdown
The Pentagon Is Putting Grok to Work
The U.S. Department of War announced last week that it will integrate xAI’s Grok chatbot into military systems, making it available to roughly 3M military and civilian personnel at Impact Level 5 starting in early 2026.
IIL5 approval allows Grok to handle controlled unclassified information. In practical terms, this positions the system for everyday operational work across the department.
Controversy Meets Operational Reality
Grok’s fraught history is well documented. Lawmakers have raised concerns about misinformation, offensive outputs, and ideological bias.
Despite the controversial track record, studies show that the most recent version of Grok has the lowest hallucination rate of any other AI model, certainly an important factor given the nature of the work.
The long-term partnership planned with the Department of War includes the broader xAI for Government platform. The offering combines foundation models, agentic tools, APIs, and access to real-time data from X.
Stan Ventures
How Grok Will Be Used
Based on statements from the Department of War and xAI, Grok is being positioned to handle foundation models, agentic tools, APIs, and access to real-time data from X with things like:
Administrative support such as summarizing internal documents, synthesizing reports, and answering questions tied to controlled data.
Workflow assistance embedded directly into existing tools (rather than accessed as a standalone chatbot).
Operational analysis allowing users to query large internal datasets and receive structured responses quickly.
The focus here is information compression. Grok acts as an interface between people and large volumes of fast-moving data.
Why This Matters Outside Defense
Deploying AI this close to potentially sensitive information raises the stakes. But for businesses and governments alike, what matters most is not how capable the system is, but how consistently it is monitored and challenged.
Convenience tends to move faster than governance if no one is paying attention.
The technology matters, but the long-term outcome will hinge on whether scrutiny keeps pace with adoption.
Prompt of the Week
If you’re looking to use AI to beef up your car images but they end up looking fake or oddly flat, the issue usually isn’t the vehicle or the environment. It’s perspective.
Most image models default to a wide field of view, which exaggerates proportions, flattens backgrounds, and makes vehicles feel like they’re sitting on top of the scene instead of inside it. Real automotive photography relies heavily on longer focal lengths to compress space, control reflections, and make cars feel planted and premium.
This week’s prompt framework forces the model to render vehicles using realistic lens physics. Use it to get cleaner lines, better stance, and images that look closer to real dealership or editorial photography.
Generate:
An image of a [vehicle make, model, and year] in motion or staged [driving, parked, rolling, or three-quarter view].
Assume:
The scene is rendered with realistic automotive photography perspective and physical lens behavior.
Render using:
A long focal length between 135mm and 400mm, with an aperture between f/2.0 and f/4.0.
Optimize for:
Strong background compression, natural reflections on paint and glass, realistic tire contact with the ground, shallow depth of field, and tack-sharp focus on the vehicle. The car should feel anchored to the road, not floating.
Avoid:
Wide-angle distortion, stretched body panels, warped wheels, overly glossy paint, fake-looking blur, and backgrounds that feel pasted behind the car.
Additional context:
[Location such as city street, highway, dealership lot, or scenic road; lighting conditions; weather like overcast, rain, or golden hour; surface details like wet pavement or dust; color grading notes.]
Fresh Finds for Auto Pros
Finance & Insurance: Zyplow
Uses AI to detect anomalies and potential fraud in insurance and financial data before small issues become costly problems. It adds a proactive layer of risk and compliance intelligence to F&I operations without slowing deals down.
Service and Parts: Self Inspection
An AI-driven vehicle inspection system that analyzes photos and videos from a simple walk-around to identify vehicle condition and generate a detailed inspection report. A scrappier alternative to heavy equipment—good for stores that want scale without the cost.
Data Management: DealerBuilt
Embeds AI directly into the dealership operating system, helping teams streamline workflows, surface operational insights, and reduce friction across departments. Instead of bolted-on tools, it focuses on making the core DMS smarter and more adaptive in real time.
Hear from the Experts
In our recent chat with Brian Benstock, he hits on something dealers deal with all the time. Customers are often in a good position to trade, but it is hard to see it clearly or act on it quickly. Trade-cycle management and equity visibility come down to having the right information at the right time.
That is where the AI angle shows up. When appraisal data, equity, inventory, and messaging tools all live in different places, automation can only do so much. When those systems connect, it gets easier to spot trade opportunities, talk affordability with confidence, and reach out when the timing actually makes sense.
Bits and Bytes
Waymo is reportedly testing Gemini AI integration to give robotaxi riders an interactive assistant. 🚕
OpenAI introduced curated Prompt Packs to better align ChatGPT with real-world job needs. 💬
China is considering sweeping AI regulations to prevent chatbots from emotionally influencing vulnerable users. 🙇
Oof. Hope you’re having a better day than this guy. 😵
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