💡 Part 2: The Brilliance Is There.
Now Build the Product It Deserves.

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In Part 1, we talked about the friction—UX gaps, memory lapses, sandbox volatility, and the sheer number of moments where ChatGPT undermines itself by being almost right... until it isn’t. I recommend starting there if you haven’t read it, because while this isn’t about nitpicking features, it does set the stage for what could be next. It’s about missed expectations, lost trust, and a growing pattern that threatens long-term adoption.

So let’s zoom out.

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🧭 Strategy Matters (Or, How to Win Customers and Influence Users)

Here’s the uncomfortable truth: groundbreaking tech doesn’t succeed by default. Being the smartest guy in the room isn’t a guarantee you’ll win. Systems thinking, vision, and user trust do.

What’s missing right now isn’t innovation—it’s integration. ChatGPT is brilliant. But brilliance without scaffolding becomes chaos. You can’t patch real-world usability with vibes and a new button. That’s how you end up with UX whiplash and a support inbox full of "what just happened?"

The tool is not the product.
The model is not the solution.
And AI is not magic unless you design like it is. And plan like it isn’t.

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🪬 The Curse of Genius Products

Lots of great products have been the technical pinnacle of their arena and still had their asses handed to them. Let’s all hope OpenAI doesn’t follow this pattern.

• Betamax, which outperformed VHS on quality but got bodied by better licensing.
• Google Glass, which promised the future and forgot social design.
• Palm Pilot, which was functionally revolutionary and strategically obsolete.

None of them failed because they weren’t smart.
They failed because being smart isn’t enough.

The more powerful the tech, the more critical the execution. And right now? OpenAI is building the equivalent of the world’s smartest assistant. Then handing it to users with no pen, no clipboard, no notebook, and no filing cabinet.

Power and technical superiority don’t beat usability. Clarity and adoption do.
(Unless you’re Oracle. Then you win by attrition, fear, and a little Stockholm syndrome baked into the pricing.)

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❌ What OpenAI Is Getting Wrong

Let’s be clear: these aren’t wild, impossible requests. They’re product basics for power users and enterprise scale.

• Persistent workspace: Nonexistent. Files, folders, progress… evaporate with session resets. Projects are a step, but not a solution.
• Reliable long-term memory: MIA. Even conversations labeled for memory often lose context, tone, or task continuity.
• Stable, predictable tables and pattern-tracking: Broken. Even obvious formats can’t be counted on to carry over reliably. And the worst part, this one used to work.
• File handling with accountability: You can upload (to a point). You can prompt. But can you trust it to handle ongoing work without losing track? Not really.
• Error messages that actually mean something: "Code Interpreter session expired" isn’t helpful. It's the technical equivalent of, “Too bad, so sad.”
• Pricing that matches the quality of the product being delivered: Jumping from $20 to $200 a month isn’t a pricing strategy, unless the strategy is to price most users right out of the platform. It’s ridiculous and ignores the reality of user budgets at the same time it offers no clarity on what you’re getting for 10x the cost. It’s a paywall in a trenchcoat, flashing unlabeled features with a sly wink and asking for $200. No refund. No clue.

These are not model failures. These are product strategy failures. And they’re making ChatGPT feel less like a trusted tool and more like a roulette wheel with a slick UI.

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⏰ Why This Matters Now

Because while the race isn’t won, the window to get ahead is closing.

For all of OpenAI’s technical dominance, competitors are gaining ground, not by out-researching, but by out-shipping. Anthropic is building tools for teams. Google’s bundling into workflows. Microsoft is plugging Copilot into legacy business infrastructure like a doomsday device made of Teams calls and shareholder promises (which it might be).

OpenAI doesn’t need to chase those plays, but it does need to recognize the game is changing. Corporate adoption demands trust. Trust demands consistency. And consistency demands a product roadmap grounded in user feedback and consistent delivery.

Because if ChatGPT keeps unraveling its own brilliance, then no amount of jaw-dropping model performance will matter. Power users will leave. Enterprise buyers will hesitate. And the model that changed the world will end up being remembered as Claude or Copilot’s stepping stone.

• The AI race is still in its early days, and right now it’s about trust, workflow fit, and user loyalty. It’s still anybody’s game.
• A brilliant tool nobody wants to use is a demo, not a product.
• Perhaps more significantly, a tool enterprises ignore is just a diversion with good PR, not a long-lasting worldwide phenomenon.

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🏆 What Winning Looks Like

Here’s the future OpenAI could build:

• A persistent creative space where users can store, retrieve, and refine work over time, one that spans sessions instead of resetting every time you open a new one.
• A memory model that’s not just opt-in, but user-tuned, where preferences evolve and precision increases.
• File handling that doesn’t just upload and forget, but lets the assistant become a true collaborator with version control, clarity, and continuity.
• An error reporting system that delivers clear, actionable messages instead of cryptic shrugs.
• A workflow-aware interface that distinguishes between one-off queries and ongoing projects, and supports both.
• A model that knows when to ask, “Should I save this?” and how to help without being prompted.

This isn’t sci-fi. This is product discipline.

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✅ In other words, it’s achievable!

This is all within reach, despite the long list of issues I lamented in part 1. All it requires is a shift in delivery thinking. A few small changes in their approach to product strategy could change everything.

• Use cross-functional product management teams that understand both AI and human behavior. (Ideally supported by stakeholders who understand the realities of corporate and budget-driven decision-making.)
• Approach your design iteratively and transparently, and provide lots of opportunities for user feedback.
• Create power features for power users—without dumbing things down for everyone else.

If you can give them what they want, early adopters and power users will drive broader product usage by singing your praises to the rooftops, the neighbors, that creepy guy at the grocery store, and everyone else in earshot. But only if you’re really considering their needs and delivering on them.

(Don’t believe me? I once convinced my physical therapist to write me a surgery recommendation letter by suggesting she have ChatGPT write it for her. She did. Surgery approved. You’re welcome, healthcare system.)

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🏁 Bottom Line: The Best AI Doesn’t Win. The Best Product Does.

OpenAI won’t fail because ChatGPT isn’t smart enough. But they might fail because they’re focused on model performance instead of how real people use tools.

They won’t lose to smarter competitors, but they could lose to simpler tools that just work.

If OpenAI wants long-term success—not just research acclaim, but real-world adoption—it’s time to ship grown-up products that meet users where they are.

You’re not losing to better models. You’re losing by default.

This isn’t about out-modeling Claude or Gemini or whoever’s trending next. You’ve already built what everyone else is chasing.

Now ship it like you mean it.

You’ve built the most extraordinary tool in the world. The only thing holding it back... is how you're packaging it.

Start building like you know what you have. And like you know what it could be.

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Or don’t. And watch Clippy win.