3 Questions Every Prospect is Asking

Patrick McFadden • May 7, 2022

When someone lands on your website, they’re asking themselves the following questions:


  1. Does this company understand my problem?
  2. Can this company solve my problem?
  3. Has this company solved this problem for others?


You want to ensure that your site answers these questions. There are several ways to accomplish this.


Let’s look at a few of them.


Address The Real Problem Your Client Wants to be Solved

Oftentimes, your client isn’t entirely aware of the problem they have.


They may be unaware of what the real problem is, or they might have difficulty identifying what it is that truly ails them.


For example, let’s say you own a remodeling firm. Your ideal client might say that their problem is that they have an old, ugly, outdated kitchen. But in reality, their problem is that they don’t have a functional family gathering space.


They’re defining their problem in purely practical terms, but it’s really bigger than that.


What you bring to the table with your remodeling services is the opportunity for a better life, by creating a kitchen where a family can relax, spend time together, and create memories.


When thinking about the problem you need to address in your marketing, it’s important to look beyond that surface-level pain point.


Very frequently, what really plagues your client at their core is something emotional, not practical.


Make Your Customer’s Problem Your Marketing Message

The key to good marketing is in the planning.


If planned well, it’s a pain-free experience and — if you have a good solution or service — you’ll quickly see not only the positive results but why it’s an integral part of the business itself.


The most important starting point is working out your value proposition, or prime marketing message.


Put simply, this is the thing that differentiates you from your competitors.


The reason why your customers choose you above the others, distilled into a sound-bite.


Let’s say you own a home services business. Your potential customers will automatically operate under the assumption that you know how to remove trees, repair their HVAC system, unclog the toilet, mow their lawn, install new doors, etc.


But from my marketing experience that doesn’t really address what potential customers care about.


For most homeowners, their biggest problem associated with a home service provider is about something beyond the basic service the business provides.


Homeowners hate long service window times, or not getting phone calls returned. When they hire someone to handle their home needs, the tech leaves behind a mess, surprises them with unexplained fees or it’s difficult to get payment to them because they only accept checks. These are the real problems your clients have.


So your value proposition or prime marketing message is not, “We know how to mow your lawn, remove trees, unclog your toilet, repair the HVAC system ” — of course you do!


Instead, it’s “We explain all fees and show up on time.” Or “We return all calls and leave your home better than when we arrived.”


Stop Marketing What You Provide and Start Marketing What You Solve

Hard Truth! It’s lazy to assume that your customer wants the core service you provide whether that is accounting, consulting, landscaping, plumbing, coaching, training, etc.


Instead, speak with them to learn what they believe they will get, achieve, dodge, or acquire based on buying what you sell.


This will uncover the real reason they do business with you and the problem you really solve for them.


For example, we were working with a tree service that attracted a specific type of homeowner. After interviewing their customers we spotted the following in several summaries — “They never damage my yard and always clean up when they’re done.”


Turns out that their ideal customer had beautiful front and back yards and didn’t want any damage done to the monthly landscaping work they pay for.


While most of their competitor’s messaging focused on how they were award-winning, voted best, and having 60yrs experience at removing trees our client began to focus on — “We never damage your yard and always clean up when we’re done.” — getting prospective homeowners to pay a premium to solve that problem.


Solving Problems Must Be The Real Focus

Nobody wants the remodeling, training, consulting, coaching, mentoring, or repair services you sell.


What people want is for their problems to be solved. Solving problems must be the real focus of your marketing efforts.


CEOs, owners, and people buy better versions of their business, home, life, and bank account, not things. They want what they believe will help them feel good about themselves, achieve something higher, get relief from some level of pain or discomfort, avoid a sticky situation, or prepare themselves for the future.


It’s your job as a CEO or owner of a small business to understand the problems people are trying to solve and match your services to those very specific problems.


Very few people in the world want what you provide, they want what you solve.


Here’s how to develop your problem-solving message to attract ideal clients.

The Missing Layer in AI: Why Judgment, Not Just Data, Will Define the Next Era of Intelligence

By Patrick McFadden • May 2, 2025
Everyone is scaling outputs. Almost no one is scaling judgment.

Everyone Talks About AI Judgment. We Built It.

By Patrick McFadden • May 2, 2025
Ask anyone in tech where AI is headed, and they’ll tell you: “The next leap is reasoning.” “AI needs judgment.” “We need assistants that think, not just answer.” They’re right. But while everyone’s talking about it, almost no one is actually shipping it. So we did. We built Thinking OS™ —a system that doesn’t just help AI answer questions… It helps AI think like a strategist. It helps AI decide like an operator. It helps teams and platforms scale judgment, n ot just generate output. The Theory Isn’t New. The Implementation Is. The idea of layering strategic thinking and judgment into AI isn’t new in theory. The problem is, no one’s been able to implement it effectively at scale. Let’s look at the current landscape. 1. Big Tech Has the Muscle—But Not the Mind OpenAI / ChatGPT ✅ Strength: Best-in-class language generation ❌ Limitation: No built-in judgment or reasoning. You must provide the structure. Otherwise, it follows instructions, not strategy. Google DeepMind / Gemini ✅ Known for advanced decision-making (e.g., AlphaGo) ❌ But only in structured environments like games—not messy, real-world business scenarios. Anthropic (Claude), Meta (LLaMA), Microsoft Copilot ✅ Great at answering questions and following commands ❌ But they’re assistants, not advisors. They won’t reprioritize. They won’t challenge your assumptions. They don’t ask: “Is this the right move?” These tools are powerful—but they don’t think for outcomes the way a strategist or operator would. 2. Who’s Actually Building the Thinking Layer™? This is where it gets interesting—and thin. Startups and Indie Builders Some small teams are quietly: Creating custom GPTs that mimic how experts reason Layering in business context, priorities, and tradeoffs Embedding decision logic so AI can guide, not just execute But these efforts are: Highly manual Difficult to scale Fragmented and experimental Enterprise Experiments A few companies (Salesforce, HubSpot, and others) are exploring more “judgment-aware” AI copilots. These systems can: Flag inconsistencies Recommend next actions Occasionally surface priorities based on internal logic But most of it is still: In early R&D Custom-coded Unproven beyond narrow use cases That’s Why Thinking OS™ Is Different Instead of waiting for a lab to crack it, we built a modular thinking system that installs like infrastructure. Thinking OS™: Captures how real experts reason Embeds judgment into layers AI can use Deploys into tools like ChatGPT or enterprise systems Helps teams think together, consistently, at scale It’s not another assistant. It’s the missing layer that turns outputs into outcomes. So… Is This a New Innovation? Yes—in practice. Everyone says AI needs judgment. But judgment isn’t an idea. It’s a system. It requires: Persistent memory Contextual awareness Tradeoff evaluation Value-based decisions Strategy that evolves with goals Thinking OS™ delivers that. And unlike the R&D experiments in Big Tech, it’s built for: Operators Consultants Platform founders Growth-stage teams that need to scale decision quality, not just content creation If Someone Told You They’ve Built a Thinking + Judgment Layer™… They’ve built something only a handful of people in the world are even attempting. Because this isn’t just AI that speaks fluently. It’s AI that reasons, reflects , and chooses. And in a world that’s drowning in tools, judgment becomes the differentiator. That’s the OS We Built Thinking OS™ is not a prompt pack. It’s not a dashboard. It’s not a glorified chatbot. It’s a decision architecture you can license, embed, or deploy— To help your team, your platform, or your clients think better at scale. We’ve moved past content. We’re building cognition. Let’s talk.

We Found the Missing Layer AI Has Been Waiting For

By Patrick McFadden • May 2, 2025
In every era of innovation, there’s a silent bottleneck—something obvious in hindsight, but elusive until the moment it clicks. In today’s AI-driven world, that bottleneck is clear: AI has speed. It has scale. But it doesn’t have judgment . It doesn’t really think . What’s Actually Missing From AI? When experts talk about the “thinking and judgment layer” as the next leap for AI, they’re calling out a hard truth: Modern AI systems are powerful pattern machines. But they’re missing the human layer—the one that reasons, weighs tradeoffs, and makes strategic decisions in context. Let’s break that down: 1. The Thinking Layer = Reasoning with Purpose This layer doesn’t just process inputs— it structures logic. It’s the ability to: Ask the right questions before acting Break down complexity into solvable parts Adjust direction mid-course when reality changes Think beyond “what was asked” to uncover “what really matters” Today’s AI responds. But it rarely reflects. Unless told exactly what to do, it won’t work through problems the way a strategist or operator would. 2. The Judgment Layer = Decision-Making in the Gray Judgment is the ability to: Prioritize what matters most Choose between imperfect options Make decisions when there’s no clear answer Apply values, experience, and vision—not just data It’s why a founder might not pursue a lucrative deal. Why a marketer might ignore the click-through rate. Why a strategist knows when the timing isn’t right. AI doesn’t do this well. Not yet. Because judgment requires more than data—it requires discernment . Why This Is the Bottleneck Holding Back AI AI can write. It can summarize. It can automate. But it still can’t: Diagnose the real problem behind the question Evaluate tradeoffs like a founder or operator would Recommend a path based on context, constraints, and conviction AI today is still reactive. It follows instructions. But it doesn’t lead. It doesn’t guide. It doesn’t own the outcome. And for those building serious systems—whether you’re running a company, launching a platform, or leading a team—this is the wall you eventually hit. That’s Why We Built Thinking OS™ We stopped waiting for AI to learn judgment on its own. Instead, we created a system that embeds it—by design. Thinking OS™ is an installable decision layer that captures how top founders, strategists, and operators think… …and makes that thinking repeatable , scalable , and usable inside teams, tools, and platforms. It’s not a framework. It’s not a chatbot. It’s not another playbook. It’s the layer that knows how to: Think through complex decisions Apply judgment when rules don’t help Guide others —human or AI—toward strategic outcomes This Is the Missing Infrastructure Thinking OS™ isn’t just about better answers. It’s about better thinking—made operational. And that’s what’s been missing in AI, consulting, leadership development, and platform design. If you’re trying to scale expertise, install judgment, or move from tactical to strategic… You don’t need a faster AI. You need a thinking layer that knows what to do—and why. We built it. Let’s talk.
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