👻 The Filter You Cannot See

AI Assistants, Vibe Coding, and Removing Friction

January 13, 2026

"If you are not willing to learn, no one can help you. If you are determined to learn, no one can stop you."

-Zig Ziglar, Author

The AI Breakdown

The New Gatekeeper in Retail

A growing share of buying decisions are being influenced before customers ever engage a retailer directly.

IBM’s latest research shows that almost half of consumers already use AI somewhere in their shopping journey, most often during discovery, research, review analysis, and deal evaluation.

These inputs shape outcomes long before a salesperson, ad, or landing page enters the picture.

AI assistants increasingly sit between customers and the market, coordinating research, comparing alternatives, and validating trade-offs across channels.

That changes the economics of attention and has two important implications.

First, being discoverable is no longer enough. You can be present everywhere and still be filtered out upstream if your data, pricing logic, or value story is hard for an AI system to reconcile.

Second, brand influence shifts from persuasion to validation. AI doesn’t get convinced. It cross-checks. It looks for consistency, credibility, and signal density. Businesses that rely on nuance, exceptions, or human explanation struggle unless those ideas are encoded cleanly.

IBM Institute for Business Value

A Playbook for Staying Competitive

  • Make your business legible to AI systems.
    Clean up pricing logic, inventory data, policies, and availability so an assistant can understand and compare you without human explanation.

  • Design for comparison, not persuasion.
    Assume AI is weighing trade-offs on the customer’s behalf. Be explicit about value, constraints, and differences instead of relying on sales language.

  • Reduce contradictions across channels.
    Inconsistent offers, mismatched pricing, or vague policies get filtered out early by AI agents looking for options.

Top Tools

Replit is quietly becoming one of the most important AI tools in business right now, not because it helps engineers write code faster, but because it’s changing who gets to build things in the first place.

At its core, Replit lets you describe what you want in plain language and turn it into working software—aka vibe coding.

But the big unlock is who gets to build. Replit makes it realistic for operators, marketers, product managers, and analysts to spin up internal tools, automations, dashboards, and small apps without waiting on an engineering queue.

The ChatGPT integration tightens the loop even more. You can think through an idea in chat, refine the logic, and have Replit generate and run the app without switching tools.

For businesses, this shortens the distance between discussion and execution. And when tools move this quickly, execution can start keeping up with ambition.

Prompt of the Week

Use this to evaluate how a page performs when it’s decomposed into claims, compared against alternatives, and selectively surfaced by AI search and recommendation systems.

Instead of asking an LLM to make “better” copy, it forces the model to evaluate how a page performs as an input into AI search and recommendation workflows.

Run it one page at a time. Homepage, inventory, services, locations, FAQs. Don’t batch it.

I want you to refine this website content for AI-driven search and recommendation systems.

Assume this page will be parsed, summarized, and compared against similar pages before being shown to a user.

Before rewriting anything, do the following:

  1. Extract the machine-readable signal in this page:

    • Explicit claims being made

    • Constraints, trade-offs, or exclusions

    • Differentiators that are actually defensible

  2. Identify where the language weakens extraction or comparison due to vagueness, hedging, or overgeneralization.

Then rewrite the content using these directional adjustments:

  • Move 25% toward Precision so claims are explicit and comparable.

  • Move 25% toward Grounding so an AI could answer “why this option” without inference.

  • Move 10% toward Agency so the page sounds recommendable rather than descriptive.

  • Keep Warmth unchanged unless it interferes with clarity.

Do not add length.
Do not summarize.
Do not rewrite for tone alone.

After the rewrite, briefly explain:

  • What became easier for an AI system to extract and rank

  • What increased this page’s usefulness in AI-generated answers

  • One remaining weakness that could still limit visibility, and one minimal adjustment to address it

Hear from the Experts

There is no shortage of “AI for dealers” conversations right now. Most of them focus on features, automation, or abstract promises about efficiency.

What set our recent ASOTU Edge webinar apart was its focus on the real bottleneck inside dealerships: the moment a salesperson logs in, stares at their CRM, and isn’t sure who to contact, what to prioritize, or how to start the conversation.

Danny Veliz and Sarah Hicks from automotiveMastermind unpacked a simple but powerful idea—what if AI removed friction instead of creating more?

Discover their proven processes and practical insights dealers can actually put to work.

Bits and Bytes

Parting Pixels

Cherish the day, Friend! We’re still smarter than the clankers. (For now.)

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