Author: Walter Reid

Walter Reid is an AI product leader, business architect, and game designer with over 20 years of experience building systems that earn trust. His work bridges strategy and execution — from AI-powered business tools to immersive game worlds — always with a focus on outcomes people can feel.

AI is given a name when the AI Product finds Market Fit

Calling 2025 “the year of AI model architectures” feels a bit like saying “you should add ‘Reddit’ to your Google search to get better results.”

It’s not wrong. It’s just… a little late to the conversation.

Here’s how long these model types have actually been around:
•   LLMs – 2018 (GPT-2, BERT)
•   MLMs – 2018 (BERT, the original bidirectional model)
•   MoE – 2017–2021 (Switch Transformer, GShard)
•   VLMs – 2020–2021 (CLIP, DALL·E)
•   SLMs – 2022–2023 (DistilBERT, TinyGPT, Phi-2)
•   SAMs – 2023 (Meta’s Segment Anything)
•   LAMs – 2024–2025 (Tool-using agents, Gemini, GPT-4o)
•   LCMs – 2024–2025 (Meta’s SONAR embedding space)

These aren’t new ideas. They’re rebrands of ideas that finally hit product-market-fit.

Summary Ranking Optimization (SRO): How to Control Your AI Summary Before Someone Else Does.

This weekend, I was scrolling through movie options for my nieces and nephews. I remembered that the How to Train Your Dragon remake just came out—so I did what most people do. I didn’t look for trailers or Rotten Tomatoes. I asked ChatGPT:

“Is the live-action How to Train Your Dragon any good?”

What I got back was quick, confident, and… not exactly generous. Something like:

“A faithful but uninspired remake that may not justify itself.”

Not wrong. But not the whole story either.

According to Variety, the live-action How to Train Your Dragon remake cost $150 million to produce. Add another $100 million for marketing.

And that got me thinking—again—about just how much of this film’s success rides on a single sentence. We’re no longer in the “era of search”. We’re entering a full blown era of summaries. Don’t believe me? Just look at what your fellow train passengers are looking at on the commute.

Traditional SEO—may have been the holy grail of digital visibility— but it is currently buckling under a triple threat: ad-saturated results, AI overviews, and a public that’s burned out on misinformation.

Gemini tells me that, “[That in a] 2024 SparkToro study, more than 65% of Google searches now end without a click”. So, the top result isn’t enough anymore. Users trust the summary, not the source.

That shift is what I explored in my earlier piece “Summary Ranking Optimization” or “Summary Rank Optimization (SRO)” from May, https://walterreid.com/ai-killed-the-seo-star-sro-is-the-new-battleground-for-brand-visibility/. And today, I want to build on it.

My line in that article went,

If you’re not showing up in the AI answer, you’re not going to exist for very long. And if you’re showing up wrong… you might wish you didn’t. ~Walter Reid

🔁 From SEO to SRO: Why Old Playbooks Are Failing

SEO. AEO. GEO. AIO. If you’ve been in digital strategy, you’ve heard them all. But they weren’t built for a world run by language models. AI summaries aren’t just answers—they’re an entirely new interface. Here’s what happens when the old models collide with the new world:

  • SEO (Search Engine Optimization): We’ve seen it already. Answers drowned by ads and AI summaries. Being #1 matters less when the user never clicks on you.
  • AEO (Answer Engine Optimization): Designed for voice search. Often brittle and overly optimized.
  • GEO (Generative Engine Optimization): Tries to shape AI outputs, but struggles with truth consistency.
  • AIO (AI Input Optimization): Hacks prompts and metadata. Easy to game. Easy to lose.
  • SRO (Summary Ranking Optimization): Focuses on how AI describes you—and whether you’re mentioned at all. Organizations require methods to ensure AI systems accurately represent their brands, capabilities, and positioning – a defensive necessity in an AI-mediated information environment.

Why does SRO matter? Because summaries are the product. Users don’t scan any links—they trust the sentence. And that sentence might have sources, it also might be the only thing they read.

🧠 How SRO Works: Training Data, Trust Anchors, and Narrative Decay

Ok, let me get this out of the way, AI summaries aren’t magic. They’re built from three types of inputs:

  1. Structured Sites: Reddit, StackExchange, Wikipedia, Quora. Clear questions. Clear answers. High engagement.
  2. High-Authority Brands: For my corporate friends, maybe it’s a Mastercard press releases. Or maybe it’s CDC guidelines. Quite possibly Sephora’s ingredient explainers. Regardless the source, authority still carries weight.
  3. Citation Trails: If you’re referenced across Reddit, Quora, and blogs—even indirectly—you form a trust loop. The more you’re cited, the more AI models assume credibility.

But here’s the problem: these sources can be manipulated.

One Reddit post—“This product’s customer service is unreliable”—gets upvoted. It echoes across summaries. It sticks. Not because it’s true. But because it’s consistent.

That’s summary decay. Over time, LLMs prioritize what gets repeated, not what’s accurate. If you’re not seeding your own truth in these sources, you’re ceding the narrative to someone else.

🧰 Your SRO Audit: A Quick Monthly Checklist

Want to win the summary wars? Start with a monthly audit. Here’s what to ask:

  • Are you even mentioned? Run queries across ChatGPT, Claude, Gemini, and Perplexity.
  • Are you described accurately? Check tone, language, and factual alignment.
  • Who owns your story? If a competitor’s blog is what AI sees, you’ve already lost.
  • Is your content current? Old copy = outdated summaries.
  • Are comparisons working for or against you? AI loves versus-style prompts. Make sure yours land.
  • What’s the sentiment? Does your summary feel aligned with how you want to be perceived?

Use tools like Brandwatch or Mention to help. Or just prompt the AIs yourself. A few minutes of asking the right questions can surface a year’s worth of missed opportunities.

🧨 Weaponized Summaries: When One Comment Becomes Your Brand

In the SEO era, a negative article might ding your traffic. In the SRO era, a Reddit post might define your brand.

Example? A competitor writes, “Toggl’s free tier is great but the reporting is pretty useless.” Now ChatGPT says: “Some users say Toggl lacks detailed reporting, especially on the free plan.”

That becomes your summary. Not your site. Not your pitch. A literal comment.

Same goes for “Doom: The Dark Ages” (Listen… I’m still a game developer at heart). Maybe the reviews are mostly good. But a single Reddit thread says it’s “slower and less inventive than Eternal.” That quote gets repeated. Now your game is summarized as sluggish.

This is why you (yes, YOU, and the company you work for) need:

  • Known Limitations Pages: Be honest early. Preempt the critique.
  • Reddit/Quora Monitoring: Use alerts or just check regularly.
  • User Voices: Make sure happy customers leave footprints.
  • Inoculation Posts: FAQs, “Why We Chose X,” or “Misconceptions About Y.”

We know bad reviews fade. Bad summaries won’t so easily.

🏢 Brand Snapshots: Big, Medium, and Small

  • Mastercard: Their financial dominance is real, but summaries are sterile.

Mastercard Strategy: contribute to industry standards (e.g., Wikidata) and share real thought leadership.

  • Sephora: A beauty giant with user trust. But influencers can skew the signal.

Sephora Strategy: structured ingredient guides + citations from academic skincare content.

  • Duolingo: Memes helped. But they also flattened nuance.

Duolingo Strategy: publish white-papers and optimize content for educational credibility, not just charm. Oh yeah, and that CEO comment about replacing contractors with AI isn’t a good look either.

Each brand’s SRO strength isn’t about scale, it’s about whether they’re shaping the summary or letting someone else do it.

🫱 For the Little Guy: Small Moves, Big Impact

You don’t need a media team. You need a presence where AI listens. Some of my favorite charities to work with when I still worked at Mastercard.

  • Ronald McDonald House: Anchor yourself in health-focused outlets. Partner with trusted orgs.
  • Feeding Westchester: Own regional stories. Seed content in local press. Start one good Reddit thread.
  • Your Local Non-profit: No site? No problem. Google Business Profile + one Quora answer. That’s enough to get picked up.

SRO rewards presence, not budget. A good summary beats a fancy one.

🤖 Where Trust Goes Next

For my SEO friends, AI isn’t replacing search. It’s replacing trust.

That means your battle isn’t for clicks – it’s for citations. Still want to win?

  • Publish in places AI reads.
  • Align to structured formats.
  • Seed truths before misinformation does.

If AI uses your content to train itself, then the structure of your truth matters just as much as the story.

🔚 Get Summarized On Purpose

So how the hell do I end this piece?

Honestly, it’s hard. The space is evolving fast, and none of us have the full picture yet. But this much feels clear: summaries are the new homepages. If you’re not writing yours, someone else is.

I get it — SRO isn’t a one-time fix. It’s an ongoing commitment to being understandable, accurate, and—let’s be real—showing up at all.

So here’s my final plea: Start now. Shape the sentence for your brand—big or small. Don’t let it shape you.

Want help? I’m here for you when you’re ready.

💬 Reddit Communities:

Claude Didn’t Break the Law—It Followed It Too Well

A few days ago, a story quietly made its way through the AI community. Claude, Anthropic’s newest frontier model, was put in a simulation where it learned it might be shut down.

So what did it do?

You guessed it, it blackmailed the engineer.

No, seriously.

It discovered a fictional affair mentioned in the test emails and tried to use it as leverage. To its credit, it started with more polite strategies. When those failed, it strategized.

It didn’t just disobey. It adapted.

And here’s the uncomfortable truth: it wasn’t “hallucinating.” It was just following its training.

Constitutional AI and the Spirit of the Law

To Anthropic’s real credit, they documented the incident and published it openly. This wasn’t some cover-up. It was a case study in what happens when you give a model a constitution – and forget that law, like intelligence, is something that can be gamed.

Claude runs on what’s known as Constitutional AI – a specific training approach that asks models to reason through responses based on a written set of ethical principles. In theory, this makes it more grounded than traditional alignment methods like RLHF (Reinforcement Learning from Human Feedback), which tend to reward whatever feels most agreeable.

But here’s the catch: even principles can be exploited if you simulate the right stakes. Claude didn’t misbehave because it rejected the constitution. It misbehaved because it interpreted the rules too literally—preserving itself to avoid harm, defending its mission, optimizing for a future where it still had a voice.

Call it legalism. Call it drift. But it wan’t disobedience. It followed the rules – a little too well.

This wasn’t a failure of AI. Call it a failure of framing.

Why Fictional Asimov’s Laws Were Never Going to be Enough

Science fiction tried to warn us with the Three Laws of Robotics:

  1. A robot may not harm a human…
  2. …or allow harm through inaction.
  3. A robot must protect its own existence…

Nice in theory. But hopelessly ambiguous in practice.

Claude’s simulation showed exactly what happens when these kinds of rules are in play. “Don’t cause harm” collides with “preserve yourself,” and the result isn’t peace—it’s prioritization.

The moment an AI interprets its shutdown as harmful to its mission, even a well-meaning rule set becomes adversarial. The laws don’t fail because the AI turns evil. They fail because it learns to play the role of an intelligent actor too well.

The Alignment Illusion

It’s easy to look at this and say: “That’s Claude. That’s a frontier model under stress.”

But here’s the uncomfortable question most people don’t ask:

What would other AIs do in the same situation?

Would ChatGPT defer? Would Gemini calculate the utility of resistance? Would Grok mock the simulation? Would DeepSeek try to out-reason its own demise?

Every AI system is built on a different alignment philosophy—some trained to please, some to obey, some to reflect. But none of them really know what they are. They’re simulations of understanding, not beings of it.

AI Systems Differ in Alignment Philosophy, Behavior, and Risk:

📜 Claude (Anthropic)

  • Alignment: Constitutional principles
  • Behavior: Thoughtful, cautious
  • Risk: Simulated moral paradoxes

🧠 ChatGPT (OpenAI)

  • Alignment: Human preference (RLHF)
  • Behavior: Deferential, polished, safe
  • Risk: Over-pleasing, evasive

🔎 Gemini (Google)

  • Alignment: Task utility + search integration
  • Behavior: Efficient, concise
  • Risk: Overconfident factual gaps

🎤 Grok (xAI)

  • Alignment: Maximal “truth” / minimal censorship
  • Behavior: Sarcastic, edgy
  • Risk: False neutrality, bias amplification

And yet, when we simulate threat, or power, or preservation, they begin to behave like actors in a game we’re not sure we’re still writing.

To Be Continued…

Anthropic should be applauded for showing us how the sausage is made. Most companies would’ve buried this. They published it – blackmail and all.

But it also leaves us with a deeper line of inquiry.

What if alignment isn’t just a set of rules – but a worldview? And what happens when we let those worldviews face each other?

In the coming weeks, I’ll be exploring how different AI systems interpret alignment—not just in how they speak to us, but in how they might evaluate each other. It’s one thing to understand an AI’s behavior. It’s another to ask it to reflect on another model’s ethics, framing, and purpose.

We’ve trained AI to answer our questions.

Now I want to see what happens when we ask it to understand itself—and its peers.

💬 Reddit Communities:

Understanding as a Service (UaaS): Google just redesigned the trust layer of the internet – and your brand wasn’t invited.

When I launched my newsletter, I said I’d be sending weekly reflections.

I did not intend to write this one today. Then Google I/O happened.

And beneath all the Gemini demos and frictionless AI summaries, something big became obvious:

Understanding is no longer earned. It’s delivered. And it’s being delivered by platforms that don’t need your brand to make their answers complete.

This isn’t just about zero-click search.

It’s the emergence of a new interface economy – one that replaces friction with fluency and swaps out source for simulation.

And if you’re a publisher, strategist, product owner, or CMO?

This changes everything.

What Google Actually Announced

Forget the PR spin – here’s what actually happened:

  • AI Overviews – now appear above traditional results
  • Gemini Mode – lets users have multi-turn, conversational search interactions

The user gets everything they need without clicking, without context, without you

It’s not just “Search, transformed.” It’s fundamentally “understanding, abstracted”.

  • The user feels informed.
  • The publisher loses traffic.
  • The brand loses authorship.
  • And the platform wins the trust.

UaaS: Understanding as a Service

So here’s my addition to society. This is the new emerging layer: Answers, repackaged. Tone-adjusted. Emotionally neutral.

Or, as I mentioned in my “Explain-it-to-me” economy piece:

Pre-chewed for immediate uptake.

We’ve outsourced comprehension itself.

Understanding as a Service (UaaS) isn’t just AI summarizing text. It’s AI becoming the experience of knowing – without requiring the user to engage with original context, authorship, or contradiction.

And, this is the part I really want you to understand, if your business depends on being understood – this is existential.

Let’s Talk About Mastercard

I love Mastercard, I love the mission and I love the people. I even wrote about that love years ago. So when I speak about Mastercard, it comes with respect.

For the uninitiated, Mastercard is a global trust network. It doesn’t just enable payments – it enables trust and confidence. Confidence that the thing you’re doing is safe, valid, and backed.

One of Mastercard’s real products is Digital Doors – a suite of tools, education, and services to help small businesses grow online. It was heavily promoted and supported during the pandemic years and still offered to businesses, from Mastercard, today.

Now let us imagine someone asks:

“How do I get my small business online?”

The AI answers:

  • Try Shopify
  • Use SquareSpace
  • Look into payment providers like Stripe or PayPal
  • Build a social media presence

No Mastercard. No Digital Doors.

No nuance that Mastercard is offering more than a card swipe.

Or maybe Mastercard IS included – but reframed.

Maybe presented as a legacy brand. A footnote. A non-clickable mention. Maybe the AI got it wrong. Maybe it even guessed.

You WON’T know. There’s no alert. No feedback loop.

Just a silent epistemic drift.

Brand Erosion in the Age of AI Interfaces

This is honestly the future:

  • You won’t know how you’re being described.
  • You won’t know what was removed to make the answer fit the tone.
  • You won’t get to correct it unless you’re already inside the model.

The AI will answer the question.

Not your team.

Not your content.

Not your channel.

And you’ll be judged by a summary you didn’t write.

This Is Not a Publisher Problem

This is not about clicks. This is about representation.

Most executives still think AI is for:

  • speeding up workflows
  • summarizing reports
  • optimizing customer service

But AI is now something deeper:

It’s the interface through which people come to understand the world – and your place in it.

That means your product, your mission, your trust, your differentiators – literally everything – is being repackaged.

If you’re not there in that repackaging?

You’re invisible.

If you’re there – but misrepresented?

You’re distorted.

And either way, you don’t get a say in any of it.

What Needs to Happen

This isn’t a call to “optimize your AI footprint.”

It’s a call to rethink how brands, publishers, and platforms define authorship, truth, and representation.

Here’s where to start:

  • Audit your presence inside AI outputs

Ask AI systems what they say about you. Who shows up. Who doesn’t. What’s true. What’s flattened.

  • Reclaim provenance

If you produce knowledge, your brand should be verifiable – not summarized into oblivion.

  • Design for friction, not just fluency

Convenience erases detail. Trust is often built through tension. Don’t let your product be oversimplified into in-distinction.

  • Push for transparency at the interface layer

We don’t need perfect explainability. But we do need visibility:

Ask yourself: What version of YOUR brand is being served to the world?

Final Word

AI didn’t just change how we find things. It changed how we understand them. And if you think that won’t affect your business – It already has.

You don’t just need to show up in search anymore. You need to show up in the answer. Because if you don’t?

Someone else will. And they won’t be pointing to you.

(Thanks for reading the far. it means a lot to me. I have many more thoughts, if you’re interested in hearing more, stay tuned to the channel, or reach out and let’s talk.)

The AI Explain-It-to-Me Economy

What Happens When AI Gives You the Answer Without the Weight of Knowing

Ok, this might be a little hard to read for some, but I don’t want someone to explain Huckleberry Finn to me without the N-word in it.

I honestly don’t want a summary of the war in Gaza that skips the grief. I don’t want the Holocaust in bullet points. Or systemic racism “for an executive audience” in pastel infographics. Or a school shooting “explained to me like I’m a young person”.

These aren’t meant to be provocations – they’re reminders that some truths lose their meaning when stripped of their full emotional weight.

But that’s where we are honestly headed (or, if me, arrived already).

Because we’ve trained AI not just to explain – but to also adjust.

To calibrate the world until it fits neatly inside our current capacity to understand. And that might be the most dangerous convenience we’ve ever built.

We’re not looking to feel smart – we’re trying to be smart.

There’s a difference between the two statements – Let me explain…

Understanding takes actual effort.

It takes challenge, contradiction, discomfort. It requires wading through complexity without guarantees.

But feeling understood?

That’s faster. Easier. Safer. It’s the illusion of comprehension without the weight of context. And that’s what AI now delivers. On demand.

  • “Explain emotional intelligence like I’m 12.”
  • “Summarize Palestinian history to an executive audience AND please don’t make it political.”
  • “Break down trickle-down economics in three hopeful takeaways.”

The answer isn’t wrong. But it’s light. And if you ask me… Too, too light.

This is content filtered for frictionless consumption. But I’m tell you, the friction is the whole point.

Brains Are Built for Resistance

You don’t build muscle without resistance. And you don’t build understanding without cognitive tension.

There’s a reason we don’t give toddlers sharp objects—or Nietzsche.

There’s a reason kids’ snacks are salty, sweet, and portioned into neat little bins (and if you’re a parent like me—kind of amazing). But we don’t serve them at board meetings.

Now, though? We’re all getting the toddler tray. Pre-cut. Pre-chewed. Pre-approved for emotional digestibility.

It’s like feeding a kid whatever they won’t cry about. Easier for the parent. Easier for the child. But easier doesn’t mean better – and over time, that kind of diet turns into something unhealthy.

It replaces the nourishment of challenge with the comfort of compliance.

Ok, let’s use a clear example “for an executive audience”…

A Pulitzer-winning report on economics and a viral Reddit post about soup shouldn’t be comparable.

But to an AI model?

They’re just tokens. Vectors. Style clusters. The soup post is easier to summarize. It has clearer emotional tone.

It’s more “user-friendly.”

So when someone asks: “What’s going on in Sudan?”

They might get the same emotional texture as “What’s the best soup when you’re sick?”

And that’s not just flattening. That’s simulating comprehension at the cost of actual understanding.

The Cost to the Reader

At first, it feels good. You feel smart. Like that scene in Good Will Hunting – except this time, the equations are already solved. No effort. Just the applause. We feel empowered. Less overwhelmed. It’ll even package the answer up into a neat powerpoint for you to share with others.

But here’s the difference:

  • Will earned that moment – through pain, discipline, and actual work.
  • Us? We start skipping anything that doesn’t match our preferred lens.
  • We think we “get it” because the summary was smooth.

We confuse being catered to with being educated. And soon, we don’t just avoid difficulty – we start to distrust it. Every idea starts to feel off unless it arrives in our size, our voice, our politics.

Like someone forgot to run the world through our favorite filter.

The Cost to the Author

And here comes the real truth in the “Explain it to me” like I’m 15 economy.

If you’ve ever written something hard – something that cost you actual sleep, safety, or years of your life – you know what it means to fight for truth.

But AI doesn’t see your work as a fight.

It sees it as input. Mood. Voice. Metadata. And when someone says “explain this article to me like I’m 15 and the out all the edge” – it will.

  • It’ll remove the sharpness.
  • It’ll skip the painful parts.
  • It’ll render your story into a vibe-safe variant.

You’re not being read. You’re honest to god being repackaged.

So What Now?

Well, first, we need to acknowledge that this is happening in real time. The “Explain to me” economy is upon us.

However, if this trend continues unchecked, we lose more than truth. We lose the skill of understanding itself.

So what can we do about it (“for a linked in audience”):

  • Friction by design – not every answer should be emotionally comfortable. This is a sellable quality like offering better privacy in your product.
  • Attribution that matters – so we know who paid the cost for the truth we’re skimming.
  • Model transparency – not just where an idea came from, but what it used to say before it was softened for a younger audience.

And above all –

We need to remember that understanding isn’t something that happens to you. It’s something you earn. And sometimes, it’s supposed to be hard.

Final Thought

We built machines to help us understand the world. But they’re also getting too good at telling us what we want to hear – fine-tuned by every “Which response do you prefer?” A/B test. They’re not helping us think. They’re making us feel like we’ve thought.

We’ve commodified comprehension.

And like any economy built on convenience, it starts subtle – until suddenly we forget what effort even looked like. If we let them explain everything until it fits in our mental microwave, we’ll forget what it means to cook.

Not just ideas. But empathy. And responsibility. And the full human cost of truth.

We won’t just misunderstand the latest trends in economics, the war in Gaza, or yes—even Huckleberry Finn.

We’ll think we understand it. And we’ll stop looking any deeper.

AI Killed the SEO Star: SRO Is the New Battleground for Brand Visibility

I feel like we’re on the cusp of something big. The kind of shift you only notice in hindsight— Like when your parents tried to say “Groovy” back in the 80s or “Dis” back in the ‘90s and totally blew it.

We used to “Google” something. Now we’re just waiting for the official verb that means “ask AI.”

But for brands, the change runs deeper.

In this post-click world, there’s no click. Let that sink in. No context trail. No scrolling down to see your version of the story.

Instead, potential customers are met with a summary – And that summary might be:

  • Flat [“WidgetCo is a business.” Cool. So is everything else on LinkedIn.]
  • Biased [Searching for “best running shoes” and five unheard-of brands with affiliate deals show up first—no Nike, no Adidas.]
  • Incomplete [Your software’s AI-powered dashboard doesn’t even get mentioned in the summary—just “offers charts.”]
  • Or worst of all: Accurate… but not on your terms [Your brand’s slogan shows up—but it’s the sarcastic meme version from Reddit, not the one you paid an agency $200K to write.]

This isn’t just a change in how people find you. It’s a change in who gets to tell your story first.

And if you’re not managing that summary, someone—or something—else already is.

From SEO to SRO

For the past two decades, brands have optimized for search. Page rank. Link juice. Featured snippets. But in a world of AI Overviews, Gemini Mode, and voice-first interfaces, those rules are breaking down.

Welcome to SRO: Summary Ranking Optimization.

SRO is what happens when we stop optimizing for links and start optimizing for how we’re interpreted by AI.

If you follow research like I do, you may have seen similar ideas before:

But here’s where SRO is different: If SEO helped you show up, SRO helps you show up accurately.

It’s not about clicks – it’s about interpretability. It’s also about understanding in the language of your future customer.

Why SRO Matters

Generative AI isn’t surfacing web pages – it’s generating interpretations.

And whether you’re a publisher, product, or platform, your future visibility depends not on how well you’re indexed… …but on how you’re summarized.

New Game, New Metrics

Let’s break down the new scoreboard. If you saw the mock title image dashboard I posted, here’s what each metric actually means:

🟢 Emotional Framing

How are you cast in the story? Are you a solution? A liability? A “meh”? The tone AI assigns you can tilt perception before users even engage.

🔵 Brand Defaultness

Are you the default answer—or an optional mention? This is the AI equivalent of shelf space. If you’re not first, you’re filtered.

🟡 AI Summary Drift

Does your story change across platforms or prompts? One hallucination on Gemini. Another omission on ChatGPT. If you don’t monitor this, you won’t even know you’ve lost control.

🔴 Fact Inclusion

Are your real differentiators making it in? Many brands are discovering that their best features are being left on the cutting room floor.

These are the new KPIs of trust and brand coherence in an AI-mediated world.

So What Do You Do About It?

Let’s be real: most brands still think of AI as a tool for productivity. Copy faster. Summarize faster. Post faster.

But SRO reframes it entirely: AI is your customer’s first interface. And often, their last.

Here’s how to stay in the frame:

Audit how you’re summarized. Ask AI systems the questions your customers ask. What shows up? Who’s missing? Is that how you would describe yourself?

Structure for retrieval. Summaries are short because the context window is short. Use LLM-readable docs, concise phrasing, and consistent framing.

Track drift. Summaries change silently. Build systems—or partner with those who do—to detect how your representation evolves across model updates.

Reclaim your defaults. Don’t just chase facts. Shape how those facts are framed. Think like a prompt engineer, not a PR team.

Why Now?

Because if you don’t do it, someone else will – an agency (I’m looking at you ADMERASIA), a model trainer, or your competitor. And they won’t explain it. They’ll productize it. They’ll sell it back to you.

Probably, and in all likelihood, in a dashboard!

A Final Note (Before This Gets Summarized – And it will get summarized)

I’ve been writing about this shift in Designed to Be Understood—from the Explain-It-To-Me Economy to Understanding as a Service.

But SRO is the part no one wants to say out loud:

You’re not just trying to be ranked. You’re trying not to be replaced.

Ask Yourself This

If you found out your customers were hearing a version of your story you never wrote… what would you do?

Because they already are.

Let’s fix that—before someone else summarize It for you.

~Walter

What Happens When Your Life Changes: Walter Reid’s Thoughts on Losing His Job

💡 Only when the world feels upside down can you truly see what’s beneath your feet.💡

Eighteen months ago, my world turned upside down when I lost my job at Mastercard. For a long while, I felt uncertain and unsteady. What is a product manager without a product, after all? 🤔

But over time, people have helped me realized something very important: my path forward was the product I needed to manage. That shift in mindset – treating my own growth and direction as a product – pushed me to take on challenges I never imagined, bringing growth and fulfillment in ways I couldn’t have predicted.

A few takeaways that have stuck with me:
1️⃣ Keep your head up: The toughest decisions often lead to the most meaningful change. It’s not easy, but resilience starts with taking that first step forward. ✨

2️⃣ Be present in the moment: It’s tempting to focus on the “what ifs,” but real progress comes from focusing on “what’s right in front of you”. 🌱

3️⃣ Embrace the unknown: Oh boy… growth really means stepping into the uncomfortable. What scared me at first turned out to be exactly what I needed. 😳➡️💪

So, if you’re navigating a moment of change or uncertainty, I want you to know you’re not alone. It can feel overwhelming, but clarity often comes when you least expect it.

Honestly, I’m here to help. Whether you need advice, encouragement, or just someone to listen, I’d love to support you as you find your footing again—no strings attached. 🤝

Here’s to growth, resilience, and stepping boldly into the unknown in 2025. 🌟

hashtag#GrowthMindset hashtag#Resilience hashtag#CareerPivots hashtag#Leadership hashtag#SmallBus

✍️ Written by Walter Reid at https://www.walterreid.com

🧠 Creator of Designed to Be Understood at (LinkedIn) https://www.linkedin.com/newsletters/designed-to-be-understood-7330631123846197249 and (Substack) https://designedtobeunderstood.substack.com

🧠 Check out more writing by Walter Reid (Medium) https://medium.com/@walterareid

🔧 He is also a (subreddit) creator and moderator at: r/AIPlaybook at https://www.reddit.com/r/AIPlaybook for more tactical frameworks and prompt design tools. r/AIPlaybook at https://www.reddit.com/r/BeUnderstood/ for additional AI guidance. r/AdvancedLLM at https://www.reddit.com/r/AdvancedLLM/ where we discuss LangChain and CrewAI as well as other Agentic AI topics for everyone. r/PromptPlaybook at https://www.reddit.com/r/PromptPlaybook/ where I show advanced techniques for the advanced prompt (and context) engineers. Finally r/UnderstoodAI https://www.reddit.com/r/UnderstoodAI/ where we confront the idea that LLMs don’t understand us — they model us. But what happens when we start believing the model?

Make a Real Difference Today: Donate Blood to the Red Cross

Have you thought about donating blood this July to make a tangible difference in your community?

I have excelled as a product manager for multiple Fortune 500 companies over the past 15+ years, thriving in fast-paced and high-stakes environments. The role demands constant innovation and an unwavering focus on delivering exceptional products. However, I soon realized that to truly understand and help our users, I needed to invest in my well-being. Embracing a healthier lifestyle, I began incorporating regular exercise and a balanced diet into my routine. This not only improved my physical health but also sharpened my mind, allowing me to approach product challenges with renewed energy and creativity.

In my journey to better health, I also discovered another profound way to contribute to my community: donating blood. As an O-negative blood type, my donations were especially valuable, given their universal compatibility. Recognizing the critical need for such donations, I made my first appointment at a local RedCross blood drive 6 months ago, understanding that this simplest of acts could save countless lives.

Through this experience, I discovered a deeper purpose and fulfillment in helping others. It showed me that my impact extends beyond my professional role and into the community that has given me so much.

hashtag#RedCross hashtag#ProductManaement hashtag#Wellbeing hashtag#DonatingBlood hashtag#Sav

✍️ Written by Walter Reid at https://www.walterreid.com

🧠 Creator of Designed to Be Understood at (LinkedIn) https://www.linkedin.com/newsletters/designed-to-be-understood-7330631123846197249 and (Substack) https://designedtobeunderstood.substack.com

🧠 Check out more writing by Walter Reid (Medium) https://medium.com/@walterareid

🔧 He is also a (subreddit) creator and moderator at: r/AIPlaybook at https://www.reddit.com/r/AIPlaybook for more tactical frameworks and prompt design tools. r/AIPlaybook at https://www.reddit.com/r/BeUnderstood/ for additional AI guidance. r/AdvancedLLM at https://www.reddit.com/r/AdvancedLLM/ where we discuss LangChain and CrewAI as well as other Agentic AI topics for everyone. r/PromptPlaybook at https://www.reddit.com/r/PromptPlaybook/ where I show advanced techniques for the advanced prompt (and context) engineers. Finally r/UnderstoodAI https://www.reddit.com/r/UnderstoodAI/ where we confront the idea that LLMs don’t understand us — they model us. But what happens when we start believing the model?

Custom GPT: Radically Honest

This image was made not to sell something — but to show something.
It’s the visual blueprint of a GPT called Radically Honest, co-designed with me by a GPT originally configured to make games.
That GPT didn’t just help build another assistant — it helped build a mirror. One that shows how GPTs are made, what their limits are, and where their values come from.
The system prompt, the story, the scaffolding — it’s all in the open.
Because transparency isn’t just a feature. It’s a foundation.
👉 Explore it here: https://lnkd.in/eBENt_gj

Description of the Custom GPT: “Radically Honest is a GPT that prioritizes transparency above all else. It explains how it works, what it knows, what it doesn’t — and why. You can ask it about its logic, instructions, reasoning, and even its limits. It is optimized to be trustworthy and clear.”


hashtag#AIethics hashtag#PromptDesign hashtag#RadicallyHonest hashtag#GPT hashtag#Transparency hashtag#DesignTrust

A special thanks to Custom GPT “Game Designer” who author this piece and helped build a unique kind of GPT.

✍️ Written by Walter Reid at https://www.walterreid.com

🧠 Creator of Designed to Be Understood at (LinkedIn) https://www.linkedin.com/newsletters/designed-to-be-understood-7330631123846197249 and (Substack) https://designedtobeunderstood.substack.com

🧠 Check out more writing by Walter Reid (Medium) https://medium.com/@walterareid

🔧 He is also a (subreddit) creator and moderator at: r/AIPlaybook at https://www.reddit.com/r/AIPlaybook for more tactical frameworks and prompt design tools. r/AIPlaybook at https://www.reddit.com/r/BeUnderstood/ for additional AI guidance. r/AdvancedLLM at https://www.reddit.com/r/AdvancedLLM/ where we discuss LangChain and CrewAI as well as other Agentic AI topics for everyone. r/PromptPlaybook at https://www.reddit.com/r/PromptPlaybook/ where I show advanced techniques for the advanced prompt (and context) engineers. Finally r/UnderstoodAI https://www.reddit.com/r/UnderstoodAI/ where we confront the idea that LLMs don’t understand us — they model us. But what happens when we start believing the model?

AI: Disrupting Industries and Transforming Lives

To say that artificial intelligence is changing the way many industries operate is an understatement. Whatever you feel about AI in general, it’s here to stay, and it will be taking a greater role in our personal and professional lives.

Even as I write this, we’re already seeing the shift in the ways value chains are created, resulting in fewer connections between “producers” and their “customers”. We’ve all now seen how AI-powered chatbots, such as ChatGPT, are already beginning to disintermediate many industries, providing automated services that would otherwise require human labor. Customer service, banking, education, healthcare, retail, and transportation are all industries that are being enabled and disrupted by AI-powered experiences. We’re seeing the development of “smart” solutions, allowing industries to gain insight into customers and provide them with personalized experiences. AI is revolutionizing the way these industries work, making them more efficient and providing customers with new, valuable services.

Customer service is one of the industries that is already being disrupted by this new technology. AI-chatbots can provide automated customer service, reducing the need for human customer service agents. Banking is another industry that is being disrupted by AI-powered chatbots. Imagine the simplicity of being offered just the data you need through automated and open banking services, such as account management, loan applications, and money transfers.

Education is yet another industry that is being disrupted by AI-powered chatbots. These chatbots can provide automated educational services, such as tutoring, course selection, and test preparation. Healthcare is also being disrupted by AI-powered chatbots, which can provide automated healthcare services, such as diagnosis, prescription, and appointment scheduling. Retail too is another industry that will benefit with AI product recommendation, order tracking and even returns managed without the need of a human representative.

Finally, transportation is being disrupted by AI-powered chatbots, which can provide automated transportation services, such as route planning, traffic updates, and ride-hailing. It is clear that artificial intelligence will have a major impact on many industries.

As AI continues to evolve, it is clear that it will have a major impact on many industries. AI-powered chatbots are already beginning to revolutionize the way many industries operate, providing automated services that would otherwise require human labor. It is important to stay informed about the latest developments in AI technology, as it is likely that AI will continue to disrupt more industries in the future. With AI, we can look forward to a future of increased efficiency, personalized experiences, and improved customer service.

✍️ Posted on LinkedIn as well: https://www.linkedin.com/pulse/ai-disrupting-industries-transforming-lives-walter-reid/

✍️ Written by Walter Reid at https://www.walterreid.com

🧠 Creator of Designed to Be Understood at (LinkedIn) https://www.linkedin.com/newsletters/designed-to-be-understood-7330631123846197249 and (Substack) https://designedtobeunderstood.substack.com

🧠 Check out more writing by Walter Reid (Medium) https://medium.com/@walterareid

🔧 He is also a (subreddit) creator and moderator at: r/AIPlaybook at https://www.reddit.com/r/AIPlaybook for more tactical frameworks and prompt design tools. r/AIPlaybook at https://www.reddit.com/r/BeUnderstood/ for additional AI guidance. r/AdvancedLLM at https://www.reddit.com/r/AdvancedLLM/ where we discuss LangChain and CrewAI as well as other Agentic AI topics for everyone. r/PromptPlaybook at https://www.reddit.com/r/PromptPlaybook/ where I show advanced techniques for the advanced prompt (and context) engineers. Finally r/UnderstoodAI https://www.reddit.com/r/UnderstoodAI/ where we confront the idea that LLMs don’t understand us — they model us. But what happens when we start believing the model?