OpenAI just made their intentions embarrassingly clear. Sam Altman showed up to Dev Day wearing Steve Jobs’ signature black turtleneck, and they quietly acquired Johnny Ive’s design startup LoveForm to launch their hardware division called “io.” The message couldn’t be more obvious: OpenAI wants to be the next Apple.
This isn’t subtle strategy. This is full-blown imitation, right down to the wardrobe choices. And while imitation might be the sincerest form of flattery, it’s also often the clearest sign that a company has run out of original ideas.
Don’t get me wrong – there’s logic behind OpenAI’s Apple obsession. Apple proved that controlling the entire user experience, from hardware to software, creates a competitive moat that’s nearly impossible to breach. OpenAI clearly believes that AI needs custom hardware to reach its full potential, and they’re betting that consumers will pay premium prices for devices that seamlessly integrate their AI models.
But here’s where it gets interesting: copying Apple’s playbook has been tried countless times, and it almost never works.
The Johnny Ive Acquisition: Genius or Desperation?
Let’s talk about the LoveForm acquisition first. Johnny Ive is undeniably one of the most influential designers in tech history. He’s the brain behind the iPhone, iPad, MacBook Air, and pretty much every iconic Apple product from the last two decades. If you’re going to copy Apple, getting their former Chief Design Officer is about as close as you can get to the source.
LoveForm, Ive’s design consultancy, has been working on various projects since he left Apple in 2019. The company focuses on creating “objects and spaces that are made with care” – classic Ive language that prioritizes simplicity and user experience over flashy features.
OpenAI’s strategy: Copy Apple’s formula and hope for similar results
But here’s the problem with this acquisition: Johnny Ive hasn’t designed a truly groundbreaking consumer product since he left Apple. LoveForm has worked on luxury items and architectural projects, not mass-market technology. Can he still create products that define entire categories? That’s a multi-billion dollar question.
More importantly, Ive’s design philosophy worked at Apple because it was paired with incredible engineering talent, supply chain mastery, and Steve Jobs’ relentless focus on user experience. OpenAI has none of those advantages. They’re a software company trying to become a hardware company, which is like a chess master suddenly deciding to compete in Olympic gymnastics.
The Hardware Problem: Why Software Companies Fail at Physical Products
Let me be direct: most software companies that try to build hardware fail spectacularly. The graveyard is littered with expensive mistakes from companies that thought their software success would translate to physical products.
Hardware is brutally unforgiving. Unlike software, you can’t push an update to fix fundamental design flaws. If your device overheats, has terrible battery life, or breaks after six months, those units are already in customers’ hands. The feedback loop is measured in months or years, not days or weeks.
OpenAI’s challenge is even more complex because they’re not just building any hardware – they’re trying to create AI-specific devices that don’t exist yet. What does an AI device even look like? How do users interact with it? What problems does it solve that a smartphone can’t already handle?
These are the questions that will determine whether OpenAI’s hardware division becomes the next iPhone or the next Google Glass.
Sam Altman’s Steve Jobs Cosplay: Missing the Point Entirely
Let’s address the elephant in the room: Sam Altman showing up to Dev Day in Steve Jobs’ signature black turtleneck. This isn’t homage – it’s cosplay, and it reveals a fundamental misunderstanding of what made Jobs effective.
Steve Jobs wasn’t great because of his uniform. He was great because he understood that technology should be invisible to the user. The best products don’t make you think about the technology behind them; they just work so intuitively that the interface disappears.
Jobs’ genius wasn’t in the turtleneck or the keynote presentations (though he was masterful at those). It was in his obsessive focus on user experience, his ability to say no to features that didn’t serve the core vision, and his understanding that most people don’t want to customize their devices – they want them to work perfectly out of the box.
Altman’s costume change suggests OpenAI thinks the secret sauce is aesthetics and presentation style. That’s like thinking you can become a great chef by wearing the same apron as Gordon Ramsay. It completely misses the substance behind the style.
The Real Challenge: Making AI Actually Useful for Normal People
Here’s what OpenAI should be focusing on instead of fashion choices: making AI that actually works reliably for normal people doing normal things.
Right now, AI is impressive in demos and terrible in daily use. ChatGPT gives you different answers to the same question depending on the day. AI assistants can write decent emails but can’t reliably book a restaurant reservation. The technology is powerful but unreliable, which is the opposite of what mass-market hardware requires.
Apple succeeded because they took existing technologies and made them work better than anyone thought possible. The iPhone wasn’t the first smartphone, but it was the first one that didn’t make you want to throw it against a wall. The iPad wasn’t the first tablet, but it was the first one that felt magical rather than clunky.
If OpenAI wants to create successful AI hardware, they need to solve the reliability problem first. No amount of Johnny Ive’s design brilliance can save a device that gives unpredictable results or fails when users need it most.
What OpenAI Gets Right (And What They’re Missing)
To be fair, OpenAI isn’t completely wrong about the hardware strategy. There are compelling reasons why AI might need custom hardware:
Custom silicon could make AI processing faster and more energy-efficient. Dedicated hardware could enable features that aren’t possible on general-purpose devices. Controlling the entire stack could create a more seamless user experience.
But these advantages only matter if the software is already excellent. Hardware can amplify great software, but it can’t rescue mediocre software. OpenAI needs to perfect their AI models before they worry about the devices that run them.
The missing piece is OpenAI’s understanding of what consumers actually want from AI devices. Apple succeeded because they identified clear user problems and solved them elegantly. The iPhone solved the problem of terrible mobile internet browsing. The iPad solved the problem of computing that felt too much like computing.
What problem does an OpenAI device solve that an iPhone with ChatGPT can’t already handle? Until they can answer that question clearly, all the Johnny Ive design talent in the world won’t help them.
The Broader Implications: AI’s Hardware Future
OpenAI’s hardware ambitions represent a broader trend in AI development. As AI models become more powerful and computationally demanding, there’s a growing belief that specialized hardware will be necessary to deliver the best user experience.
This puts OpenAI in direct competition with Apple, Google, and other tech giants who are all developing their own AI hardware strategies. Apple has the M-series chips and Neural Engine. Google has Tensor processors. Amazon has their own custom silicon for Alexa devices.
The question is whether there’s room for a pure-play AI hardware company, or whether AI will simply become another feature integrated into existing devices. My bet is on integration rather than standalone AI devices, at least for the mass market.
Specialized AI hardware might find success in enterprise applications or specific use cases, but consumers are already overwhelmed with devices. Adding another gadget to charge, update, and carry around is a tough sell unless it provides dramatically better functionality than what they already have.
Why This Will Probably Fail (But Could Be Brilliant If It Doesn’t)
Let me be honest about my prediction: OpenAI’s hardware division will probably struggle, at least initially. The company has no experience with consumer hardware, supply chain management, or the regulatory challenges that come with physical products.
The acquisition of Johnny Ive’s team is smart, but design is only one piece of the hardware puzzle. OpenAI will need to build entire competencies around manufacturing, quality control, customer support, and retail distribution. These are completely different skills from training language models.
But here’s why I could be completely wrong: if OpenAI manages to create AI hardware that genuinely improves people’s lives in ways that smartphones can’t match, they could define an entirely new product category. The potential upside is enormous, which explains why they’re willing to take the risk.
The most likely scenario is that OpenAI’s first hardware products will be expensive, niche devices that appeal to early adopters and AI enthusiasts. If those products gain traction and prove the concept, then we might see mass-market versions that could challenge existing device categories.
The key will be patience and iteration, which are not traditionally OpenAI’s strengths. The company has moved fast and broken things in software, but that approach doesn’t work with hardware. Physical products require a different mindset and timeline.
The Bottom Line: Copying Apple Requires More Than Costumes
OpenAI’s attempt to become the next Apple is ambitious, expensive, and probably premature. The company is trying to solve hardware problems before they’ve fully solved software problems, which is like trying to build a skyscraper on a foundation that’s still being poured.
Sam Altman’s Steve Jobs cosplay reveals the fundamental misunderstanding at the heart of this strategy. OpenAI thinks they can copy Apple’s success by copying Apple’s aesthetics and hiring Apple’s former designers. But Apple’s success came from relentless focus on user experience, not from turtlenecks and keynote presentations.
If OpenAI wants to succeed in hardware, they need to stop trying to be Apple and start trying to be the best version of themselves. That means focusing on making AI reliable, useful, and accessible before they worry about making it beautiful.
The irony is that OpenAI already has something Apple doesn’t: the most advanced AI technology in the world. Instead of copying Apple’s playbook, they should be writing their own. The future of AI might not look anything like the iPhone, and that’s exactly why it could be revolutionary.
But until OpenAI figures out what that future actually looks like, Sam Altman might want to put the turtleneck back in the closet and focus on building AI that works as well as it demos.