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Introduction: The Billion-Dollar Cost of Getting the Job Wrong
Even trillion-dollar companies make fundamental strategic errors. It’s a sobering thought for any founder, but it’s also an instructive one. When a giant stumbles, it’s rarely for a lack of resources, talent, or technological prowess. It’s almost always for a lack of clarity.
Meta’s AI Glasses are a world-class example of this phenomenon. They are a marvel of engineering, a glimpse into a potential future, and a product backed by an astronomical budget. They are also a solution in search of a real, high-value problem. They are a product built for a poorly understood, low-value job.
The core premise offered by Meta is that you should buy these to “capture your life, hands-free.” It’s a seductive, tech-forward pitch. But it’s a pitch that mistakes a superficial task for a deep, human job.
This is the single most dangerous mistake an innovator can make. And the cost of getting it wrong is measured in billions of dollars of wasted capital and years of squandered effort.
The good news is that there’s a better way. The single most important task for you as an innovator—more important than your technology, your funding, or your go-to-market plan—is to correctly identify and define the customer’s Job-to-be-Done (JTBD). This framework is not about what your product does; it’s about what your customer is trying to achieve.
This article is a step-by-step guide on how to do this. We’ll use the deconstruction of Meta’s AI Glasses as a live case study to illustrate the process, expose the flaws in their approach, and reveal the massive opportunities that emerge from getting the job right.
Deconstruction: Why ‘Hands-Free Capture’ is a Low-Value Job
Before you can find the right job, you have to rigorously dismantle the wrong one. Big Tech’s “solution-first” approach starts with a capability (”we can put AI and a camera in a pair of glasses”) and then hunts for a problem to solve with it. This backward process leads to products built on a foundation of unexamined assumptions. Let’s apply some intellectual rigor.
A First Principles Takedown of ‘Capture’
First Principles Thinking demands we break a thing down to its foundational truths. So, what is “capturing a moment” really about?
Using Socratic Questioning, we can challenge the premise:
What is a memory? Is it a perfect, high-fidelity video file stored on a server? Or is it an emotional and sensory imprint—a feeling, a sound, a smell—that resides within us?
What is the goal of recalling a memory? Is it to review a factual record of events, like security footage? Or is it to re-experience the feeling of that moment?
Does perfect data capture lead to perfect emotional recall? Think about your most cherished memories. Do you remember them because you have a flawless video, or because of how you felt? Often, the act of recording actively pulls you out of the moment, diminishing the very feeling you hope to preserve.
This line of questioning reveals a foundational truth: Meta is selling a tool to create better data files, but customers are trying to achieve better emotional states. The assumption that one leads to the other is a massive, unproven leap of faith.
The Functional Trap
The AI glasses are a classic example of falling into the functional trap. The features are designed to solve simple, functional tasks:
Task: Take a picture without using my hands. Solution: A camera in the frame.
Task: Identify a landmark. Solution: AI-powered visual analysis.
Task: Listen to music. Solution: Speakers in the arms.
These are technically complex solutions to simple problems. But they largely ignore the far more important emotional and social dimensions of the contexts they’re meant to be used in. Wearing a device that is passively recording creates social friction and awkwardness. The fear of missing a moment by fumbling with a phone is replaced by the anxiety of not being truly present in the moment. You’ve solved a minor functional inconvenience by creating a much larger social and emotional problem.
Why It’s a Low-Value Job
In the landscape of Jobs-to-be-Done, not all jobs are created equal. The most attractive jobs for an innovator are the ones that are important to the customer but are poorly satisfied by existing solutions.
“Hands-free capture” is a demonstrably low-value job because:
“Good enough” solutions are everywhere. Your smartphone is within arm’s reach 99% of the time. While not “hands-free,” it’s a familiar, socially accepted, and incredibly powerful tool that gets the functional job of capture done well enough for most people, most of the time.
The adoption hurdles are immense. To get this job done, a user must overcome significant friction: a high price point, privacy concerns (for both the wearer and those around them), social awkwardness, and the need to keep another device charged. The struggle with the current solution (using your phone) is simply not painful enough to justify overcoming these hurdles.
Meta is trying to sell a premium solution to a low-value job. That’s a recipe for commercial failure. The real opportunity isn’t to solve this job better; it’s to find a completely different, high-value job that is being ignored.
Reconstruction: A Forensic Guide to Finding the REAL Job
This is where we pivot from criticism to creation. The Jobs-to-be-Done framework provides the lens we need to find these high-value opportunities. The core idea is that customers don’t “buy” products; they “hire” them to get a job done. Our goal is to become ethnographers of our customers’ struggles.
The Art of the ‘Job Interview’
To find the real job, you have to talk to people—but not about your product idea. You need to investigate their struggles. A Job Interview isn’t a focus group; it’s a forensic investigation into a past decision. You might start with a simple prompt like, “Tell me about the last time you tried to learn a new hands-on skill.”
You’re listening for:
Struggling Moments: Where did they get frustrated? What was the real source of the anxiety?
Compensating Behaviors: What weird workarounds did they invent? Are they using duct tape and string (metaphorically) to solve a problem because no good solution exists?
The Push and Pull: What was pushing them away from their old situation? What was pulling them toward a new solution? What anxieties and habits were holding them back?
This is the raw material of innovation.
Crafting High-Fidelity Job Statements
Once you’ve identified a struggle, you need to define it with precision. A well-formed job statement is a guidepost for your entire product development process. The structure from our knowledge base is clear and powerful:
[Verb] + [Object of the Verb] + [Contextual Clarifier].
Let’s apply this to two high-value jobs that Meta’s glasses could have been designed for, but weren’t.
Context 1: The Struggling Apprentice (Learning a Skill)
Imagine someone trying to learn a complex, physical skill—like repairing a bicycle, mastering a guitar chord, or even performing a medical procedure. Their hands are busy. Their visual focus is on the task. Looking at a YouTube video on a separate screen is a clumsy, flow-breaking workaround.
The job isn’t to “watch a video.” The real job is:
Acquire + a new physical skill + with expert guidance.
This is a high-value job. Getting it right leads to mastery, confidence, and career progression. The current solutions are terrible. The struggle is immense. This is an opportunity.
Context 2: The Stressed Technician (Diagnosing a Problem)
Picture a field technician responsible for maintaining complex industrial machinery. A machine goes down, and every minute of downtime costs the company thousands of dollars. The technician is under immense pressure, working in a loud environment, trying to consult a technical manual while simultaneously inspecting the equipment.
The job isn’t to “look up information.” The real job is:
Diagnose + equipment malfunctions + accurately under pressure.
Getting this job done means being the hero who saves the day. Getting it wrong could mean costly delays or even safety hazards. This is a critical, high-value job where existing solutions (laptops, ruggedized tablets) are often cumbersome and inefficient.
These two job statements are clear, stable, and solution-agnostic. They are the kind of solid foundation upon which you can build a category-defining company.
From Concept to Moat: Building a Business Around the ‘Right’ Job
Now for the exciting part. Once you have the right job, you can design a purpose-built solution and, more importantly, a defensible business strategy around it.
Elevating the Level of Abstraction: Designing Novel Solutions
Let’s brainstorm solutions for our two high-value jobs. Notice how, by focusing on the job, we generate ideas that are radically different—and better—than just putting a camera on a pair of glasses.
For the Job: “Acquire a new physical skill with expert guidance”
A visual overlay is distracting. The user needs to keep their eyes on their hands, on the object they’re working on. What if the solution wasn’t visual at all?
Novel Concept: A system of haptic feedback wearables. Imagine a pair of gloves or armbands that provide gentle, precise vibrations to guide your hands through the correct motions. The expert guidance is translated into a physical sensation, building muscle memory directly. There’s no screen, no voice commands to process. The user’s visual and auditory fields are left completely free to focus on the task. It gets the job done better, at a lower cognitive cost, with fewer visible features.
For the Job: “Diagnose equipment malfunctions accurately under pressure”
Visual clutter is the enemy. The technician doesn’t need to see the internet; they need to identify a specific anomaly. What if the solution was about augmenting their hearing, not their sight?
Novel Concept: An augmented audio reality earpiece. The device listens to the machine’s sounds and compares them to a library of healthy operating signatures. It can directionally highlight the location of an anomalous sound (a worn bearing, an electrical arc) and feed the technician simple, clear audio cues like, “Abnormal friction detected in the main drive shaft.” This allows the technician to use their expert senses, enhanced by AI, without ever taking their eyes off the equipment.
Creativity Triggers Reference Table
These novel ideas weren’t pulled from thin air. They are the result of applying specific creative thinking patterns to the problem.
Choosing a North Star: The Organic Growth Paths Framework
With a novel solution in hand, you must choose a grand strategy. Where will you play? The Organic Growth Paths Framework gives us a map. Meta, with its glasses, is stuck in “Incremental Improvement” over the smartphone camera.
For our new concepts, the strategic choice is clear: Core Market Disruption. We are not trying to build a better camera. We are creating a new market for “haptic skill training” or “diagnostic audio augmentation.” These solutions attack the job from a completely different vector, rendering existing solutions (like carrying a laptop to the factory floor) obsolete. This is how you change the game instead of just competing in it.
Executing with Doblin’s 10 Types of Innovation
Finally, you need to build a moat—a sustainable, defensible competitive advantage. A great product is a start, but it’s not enough. You must innovate across the entire business. We’ll use Doblin’s 10 Types of Innovation as our tactical playbook for the Haptic Skill Training concept.
Profit Model (Configuration): Instead of a one-time hardware sale, offer “Mastery-as-a-Service.” A physical therapist’s office could subscribe to a “Post-Op Rehabilitation” module. An engineering school could license a “Basic Welding” module. The revenue is tied directly to the outcome the customer achieves.
Process (Configuration): Develop a patented, proprietary process for translating expert movements into haptic signals. This becomes the core, defensible IP—the “secret sauce” that competitors can’t easily replicate.
Product Performance (Offering): The performance of the haptic system—its accuracy, responsiveness, and comfort—must be best-in-class. This is table stakes.
Product System (Offering): Create an ecosystem. The hardware (gloves) is one part. The other is a platform where experts can create and upload new skill modules, creating a marketplace that generates powerful network effects.
Service (Experience): Offer world-class onboarding and support. A “Remote Master” service could allow an expert to guide a student in real-time from anywhere in the world, providing a level of support that transforms the customer experience.
Brand (Experience): Build a brand that stands for mastery, confidence, and human potential. It’s not a tech brand; it’s an empowerment brand. This emotional connection creates a deep moat that is very difficult for a component-focused competitor to cross.
By combining innovations in Profit Model, Process, Service, and Brand, you create a multi-layered moat that is far more defensible than simply having a piece of clever hardware.
Conclusion: An Innovator’s Real Job
Meta’s failure with its AI Glasses is not a failure of engineering. It’s a failure of inquiry. They built a technologically impressive answer to a question that few customers were asking. They focused on the shiny new capability instead of the deep, unchanging human job.
The lesson for every founder, product leader, and investor is this: the most valuable work you will ever do happens before you write a line of code or design a circuit board. It’s the deep, sometimes tedious, but always essential work of understanding the customer’s struggle so completely that the right solution becomes obvious.
Your job as an innovator is not to build solutions. It’s to find the right job.
Stop asking, “What can we build with this amazing new technology?”
Start, and never stop, relentlessly asking, “What is the real job our customer is trying to get done?”
I make content like this for a reason. It’s not just to predict the future; it’s to show you how to think about it from first principles. The concepts in this blueprint are hypotheses—powerful starting points. But in the real world, I work with my clients to de-risk this process, turning big ideas into capital-efficient investment decisions, every single time.
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