Technology that drives your business forward
One partner across every layer of your technology — design & build, manage, and grow.
The physical foundation.
Structured cabling, low-voltage, audiovisual, surveillance and network infrastructure — engineered, installed and documented to standard.
Run, secured, supported.
End-to-end managed IT, cybersecurity and cloud — proactive monitoring, compliance-aligned operations and a responsive help desk that resolves issues before they reach your team.
Built to grow.
Custom software, automation and AI built on the infrastructure we already manage — turning a dependable foundation into a competitive advantage.
Hardwired Technologies partners with the construction industry to improve efficiency, productivity, and growth through tailored technology solutions and IT infrastructure services — network infrastructure, cloud platforms, data management, surveillance, and ruggedized field support.
Secure, scalable technology and IT services that enhance learning, instruction, and administration — network deployment, managed IT support, device management, and AV systems for classrooms and lecture halls, with FERPA and E-Rate compliance.
Secure, compliant healthcare IT and managed services for medical environments — HIPAA-compliant network infrastructure, clinical workstation integration, EMR/EHR support, facility surveillance and access control that saves time and allows focus on patient care.
Secure, compliant IT for firms that run on confidentiality — law offices, accounting and financial practices. Cyber secure networks, document security, reliable backup, and management that keeps billable work moving.
What Clients Say
Hardwired Technologies provided dependable helpdesk support and technical troubleshooting across a wide range of end users in NYC and Long Island. What stood out most was their professionalism — their technicians communicated clearly with non-technical users and were patient in guiding staff through solutions. They proved to be a reliable partner in maintaining our technology operations.
Hardwired Technologies demonstrated professionalism, responsiveness, and strong technical capability in supporting our users and IT environment. Their technicians consistently resolved user issues efficiently and communicated clearly with our users. I would confidently recommend Hardwired Technologies for IT helpdesk support services.
Hardwired Technologies proved to be a reliable technology partner. Their team demonstrated strong technical troubleshooting skills, excellent communication, and a proactive approach to resolving issues before they impacted operations. We confidently recommend Hardwired Technologies for organizations seeking dependable IT helpdesk and technical support services.
Jose is proactive and dependable. He established a maintenance schedule and I do not need to reach out — it’s one less thing I must remember, so I can focus on my primary task: providing medical care… He knows the workings of my electronic medical records and the multiple bridging aspects better than the company dedicated to maintaining the program… He has made my life simpler by removing entirely the burden of my tech systems. His performance is consistently above and beyond. I give my highest recommendation to this company.
Finding a good, reliable IT company can be hard. Deciding to use Hardwired Tech was a no brainer. Jay is completely professional and the best in the biz. He works with you to ensure you’re getting the best services possible. He lays out problems he sees and outlines the best way to fix them. He is always communicative and on time. You won’t be disappointed using HT.
If you work in customer service, chances are Hardwired Technologies would be part of the definition. I own a private investigation company and thought my computer had crashed or been hacked with sensitive information. I called Hardwired Technologies during the Corona crisis and, without thinking twice, a team of experts responded and corrected the issues that had occurred. Hardwired Technologies, I owe you big time — thank you for your quick response and professionalism.
Proud to be a NYC certified small business
Committed to building meaningful, high-quality solutions. We value community, integrity, and the opportunity to make a lasting impact through everything we do.
Get in touch
Tell us your technology challenges and we'll get back to you within one business day. Prefer to talk it through? Call or email us directly.
We'll get back to you within one business day. Need us sooner? Call 646-222-9690.
The physical layer everything else runs on. We plan, install, and document the cabling, AV, surveillance, and network infrastructure your operation depends on — one accountable team from site survey to sign-off.
The scope
Delivered together as a single project or brought in on their own — every piece engineered to standard and documented on the way out.
The certified copper and fiber backbone your whole network plugs into.
HoverClick for full scopeWe survey the space, design the pathways, and pull certified copper and fiber — then terminate, test, and label every run so what’s behind the wall is as clean as what’s in front of it.
Displays, sound, and conferencing built around how the room is used.
HoverClick for full scopeFrom huddle rooms to boardrooms, we spec displays, sound, and control to the space and the workflow — then mount, wire, calibrate, and train your team so it just works on day one.
Coverage-first camera and access systems, installed clean and compliant.
HoverClick for full scopeWe plan camera coverage against real sightlines, install IP cameras and access control cleanly, and set up recording and remote access — compliant, documented, and ready to monitor.
Doors and entry points secured with credentials, readers, and audit trails.
HoverClick for full scopeWe design access control around how people actually move through the building — readers, controllers, and locks wired in, credentials issued, and every entry logged and auditable.
FAQ
Still have a question? Talk with our team →
The team that keeps everything running. We monitor, secure, and support your entire IT environment — help desk, networks, cloud, and compliance — so issues get resolved before they reach your people. One accountable partner, on call.
The scope
The day-to-day handled end to end — proactively monitored, documented, and backed by a help desk your team can actually reach.
A responsive help desk your team can actually reach.
HoverClick for full scopeReal people who pick up — remote and on-site support that resolves issues fast, communicates clearly with non-technical users, and keeps a record of everything so nothing slips.
Switching, Wi-Fi, and racks sized and documented for uptime.
HoverClick for full scopeWe size, deploy, and maintain the switching, wireless, and racks your operation runs on — segmented, secured, and fully documented so every connection stays fast and easy to support.
Layered protection — and the paperwork to prove it.
HoverClick for full scopeEndpoint protection, email security, MFA, and monitoring, plus the policies and reporting to satisfy clients, insurers, and regulators. Security that’s maintained, not set-and-forget.
Backups you can actually restore; cloud that stays up.
HoverClick for full scopeMicrosoft 365 and cloud management with tested backups and disaster recovery, so a bad day never becomes a bad week. We verify restores — not just backups — and document the plan.
FAQ
Still have a question? Talk with our team →
Technology that moves your business forward. We design and build the custom software, automation, and AI that turn manual work into leverage — integrated with the systems you already run, and built to grow with you.
The scope
Software, automation, and AI that fit your operation — designed, built, and integrated to create real, measurable leverage.
Automate the busywork; put AI where it earns its keep.
HoverClick for full scopeWe find the repetitive, error-prone work and automate it — with practical AI and workflow automation that saves hours, cuts mistakes, and frees your team for higher-value work.
Tools built around your workflow — not the other way around.
HoverClick for full scopeWeb and internal applications designed around how your team actually works, replacing spreadsheets and manual steps with software that fits, scales, and is documented for the long run.
Turn scattered data into decisions you can act on.
HoverClick for full scopeWe connect your data sources and build the dashboards and reporting that show what’s actually happening — clean, trustworthy numbers your team can act on, updated automatically.
Make the tools you already use talk to each other.
HoverClick for full scopeWe connect the platforms your business runs on — CRM, accounting, operations — so data flows automatically instead of being re-keyed, with the whole thing documented and monitored.
FAQ
Still have a question? Talk with our team →
The Hardwired blog
Practical advice and technology guides from our team.
Tim Cook has handed Apple to its hardware engineering chief. What Cook built, who Ternus actually is, and the Siri problem now sitting on his desk.
Why your AI forgets, why one model costs $0.20 per million and another $30, and what a context window actually buys you.
Technology is our craft.
Partnership is our focus.
Backed by more than two decades of hands-on experience, we help organizations across the New York metro area build and manage the technology environments that drive their growth — one accountable partner across every layer of the stack.
What we stand for
Technology only matters if the people using it are better off. We start with how your team actually works — then build to that.
By the numbers
Minority-owned and fully certified, delivering design & installation, managed IT, and digital innovation under one roof.
Years of experience
Integrated service divisions
Monitoring & support
Accountable partner, every layer
From the founder
“We built Hardwired to be the partner we always wished our clients had — one team that owns the whole stack, answers when you call, and treats your technology like it’s our own.”
Jay founded Hardwired Technologies in 2019, bringing more than twenty years in the field to a simple idea: businesses shouldn’t need a different vendor for every layer of their technology. What started as hands-on cabling and support work has grown into a full-stack partner serving companies across New York, New Jersey, Connecticut and beyond — but the approach hasn’t changed. Show up, do it right, and stand behind the work.
Get in touch
Tell us your technology challenges and we'll get back to you within one business day. Prefer to talk it through? Call or email us directly.
We'll get back to you within one business day. Need us sooner? Call 646-222-9690.
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Hardwired Technologies Inc.
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Just a few short years ago, the only people who ever said the word “token” were arcade owners and subway riders. Today it is on your invoice. It is in your subscription plan. It is the reason your AI assistant suddenly “forgot” what you told it forty messages ago, and it is the reason one model costs $0.20 per million and another costs $30.
We have all seen it; you open a billing dashboard or a plan comparison page and there it is — 1M token context window, $5/MTok input, 128k max output — presented as though everyone already knows what that means. Most people don’t. And that’s a shame, because tokens are not complicated. Once the concept clicks, an enormous amount of AI jargon stops being jargon and starts being obvious.
So let’s demystify it. No math degree required.
Here is the first thing to understand: language models do not read the way you and I read. They do not see letters. They do not really see words, either. They see tokens — chunks of text that sit somewhere in between.
Anthropic’s own documentation defines tokens as “the smallest individual units of a language model,” which “can correspond to words, subwords, characters, or even bytes.” For Claude, a single token works out to roughly 3.5 English characters. Google’s teams use a rounder rule of thumb: about 750,000 words per million tokens.
Common words tend to be one token all by themselves — the, and, technology. Rarer words get chopped into pieces. Punctuation and spaces count. Even the invisible scaffolding of a conversation counts.
In its simplest form, tokens = the syllables of machine language. And just like syllables, they are the unit the system actually counts, bills, and budgets against.
If you want a perfect demonstration of why this matters, ask a chatbot how many R’s are in the word “strawberry.” For a long stretch, the most advanced models on Earth got that wrong — confidently.
The reason is beautifully mundane. GPT-4 doesn’t see s-t-r-a-w-b-e-r-r-y. It sees three tokens: str, aw, and berry — internally just the ID numbers 496, 675, and 15717. Asking it to count letters is like handing someone who doesn’t read Chinese a character and asking them to count the brush strokes; the information is technically there, but not in a form the reader can act on.
Make no mistake — this is not a sign that the model is stupid. It is a sign that the model’s eyes work differently than yours. Understanding that single fact explains an entire category of weird AI behavior, from spelling puzzles to arithmetic quirks to why some languages cost more to process than English.
Now for the term that actually affects your day-to-day: the context window.
The context window is the total number of tokens a model can hold in its head at once — the system’s instructions, your entire conversation history, any files or images you attached, the tool results it fetched, and the answer it is currently writing. Anthropic describes it as the model’s “working memory,” which is exactly right, and it’s importantly different from what the model learned during training. Training is what it knows. Context is what it’s currently holding.
And here is the part that surprises people: the context window refills from scratch on every single turn. When you send message number twelve, the model is re-reading messages one through eleven — every word, plus every one of its own replies — and then answering. The conversation doesn’t stream past it; it stacks up. That is why long chats get slower and pricier as they go, and why an assistant eventually starts dropping details from early on.
The good news is that the ceilings have gotten enormous. Claude Opus 5, Sonnet 5, and the entire current lineup run a 1 million token context window with up to 128,000 tokens of output. Google’s Gemini 3.1 Pro and the Flash models sit at 1 million as well, with roughly 64,000 tokens of output. A million tokens is about 750,000 words — call it a 1,500-page technical manual, an entire mid-sized codebase, or somewhere north of seven full-length novels. In one prompt. That is a remarkable place to be, considering models were choking on 8,000 tokens not that long ago.
Tokens aren’t just a memory unit — they are the billing unit, and this is where the concept pays for itself. Providers charge separately for tokens going in (what you send) and tokens coming out (what the model writes), and output is always the expensive half.
As of August 2026, on the Claude API: Opus 5 runs $5 per million input tokens and $25 per million output. Sonnet 5 is $2 in / $10 out — that introductory rate is now permanent. Haiku 4.5 is $1 in / $5 out.
On Google’s side, Gemini 3.1 Pro is $2 in / $12 out, Gemini 3 Flash is $0.50 / $3.00, and Flash-Lite bottoms out at $0.25 / $1.50.
OpenAI’s current flagships price similarly by tier: gpt-5.6-sol at $5 in / $30 out, gpt-5.6-terra at $2 / $12, and gpt-5.6-luna at a whopping-in-the-other-direction $0.20 / $1.20 — with batch processing knocking roughly 50% off if you can tolerate waiting.
Put a real number on it. A 3,000-word document is somewhere around 4,000 tokens. Sending it to Opus 5 costs you two cents. Sending it two hundred and fifty times still costs less than lunch. The reason enterprise AI bills get scary isn’t any one request — it is thousands of requests, each one dragging a growing conversation history behind it. The tokens you forgot you were re-sending are the ones that get you.
One more wrinkle worth knowing: tokenizers change. Anthropic notes that Claude 4.7 and later use a newer tokenizer that produces roughly 30% more tokens than earlier versions for the same text. Same document, same price per token, different token count. If you ever upgrade models and your bill moves without your usage moving, that’s why.
Tokens are not a text-only tax. Everything you feed a modern model gets converted into tokens first.
Claude, for instance, chews images into patches of 28×28 pixels, each patch becoming a visual token. The math is refreshingly simple: divide the width by 28, divide the height by 28, round both up, multiply. A 1000×1000 pixel image? 1,296 tokens. A 4K screenshot on a high-resolution model? Up to 4,784 tokens — though the models automatically downscale oversized images, which mercifully caps the damage.
So that PDF you dropped in “real quick”? It has a token count. That folder of screenshots? Token count. The tool that went and fetched a webpage for you? Every character of that page came back as tokens and took a seat in your context window.
Here’s the counterintuitive one, and it may be the most practically useful idea in this entire piece.
A bigger context window is not automatically a better answer. As the token count climbs, accuracy and recall measurably degrade — a phenomenon the industry has taken to calling context rot. Anthropic puts it plainly: curating what goes into the context matters as much as how much space you have.
Think of it like a desk. A bigger desk is genuinely useful. But a bigger desk buried under 400 pages of paper is worse than a small desk holding the three documents you actually need. Just because you can paste a million tokens in doesn’t mean you should.
Which is why the practical advice is almost embarrassingly old-fashioned: give it the relevant material, not all the material. Start a fresh conversation when the topic genuinely changes. And if a long thread starts feeling foggy, it probably is — summarize where you landed, open a new chat, and paste the summary in. You’ll get sharper answers AND a smaller bill.
Will tokens still be the unit of measure in five years? Probably — BUT the way we experience them is already changing fast. Context windows went from 8,000 tokens to 1,000,000 in about three years, and the frontier labs are openly experimenting with the tier above that. Prompt caching now lets you re-send the same background material at a steep discount instead of paying full freight every turn. Server-side compaction quietly summarizes the early parts of a long conversation so it can keep going past the ceiling. And research into byte-level and patch-based models is chipping away at tokenization itself — the day a model can simply see the letters in “strawberry” is coming.
More often than not, the technologies that end up mattering most are the ones that eventually become invisible. Nobody thinks about the megabytes in an email attachment anymore, and eventually nobody will think about tokens either. Until that day, though, understanding them is undoubtedly the cheapest upgrade you can give yourself — it makes you better at prompting, better at budgeting, and much harder to confuse with a pricing page.
The path there will certainly be fascinating to watch.
We build practical AI automation and custom software — and we'll tell you plainly where it pays off and where it doesn't.
Book a free assessment →Yesterday, September 1, 2026, the most valuable company on the planet changed hands. Tim Cook — the man who ran Apple for fifteen years, longer than Steve Jobs ran it in his second act — stepped aside, and John Ternus, Apple’s senior vice president of hardware engineering, became just the third CEO Apple has had this millennium. The board approved it unanimously back on April 20th, gave the two men a summer to hand off the controls, and then flipped the switch on a Tuesday morning with all the drama of a software update.
Make no mistake, though; this is a bigger moment than the press release lets on. Apple didn’t just swap a name on an org chart — it changed what kind of person runs the company. For fifteen years, Apple was led by an operations savant who turned a device maker into a services machine. Starting yesterday, it is led by an engineer who spent his first year at the company arguing with a supplier about how many grooves were cut into the head of a screw. And he takes over eight days before an iPhone launch event, in the middle of the most consequential technology race since the smartphone itself.
So let’s talk about what Cook built, who Ternus actually is, and the very large problem now sitting on his desk.
Start with the scoreboard, because the scoreboard is astonishing. When Cook took over on August 24, 2011, Apple’s market capitalization was roughly $347 billion and its full-year revenue for fiscal 2011 was $108 billion. As of his last week in the chair, Apple’s market cap sits around $4.6 trillion — and it briefly crossed $5 trillion in July, only the second company in history to touch that number. Bank of America ran the math and figured that under Cook, Apple’s market value grew by about $32 million per hour, for fifteen straight years.
For shareholders it was, dollar for dollar, one of the great runs in corporate history. Apple’s share price climbed roughly 2,230% from Cook’s first day through early August 2026, and with buybacks and dividends folded in, the total return lands near 2,680%. In practical terms: $10,000 put into AAPL the day Cook started would be worth about $278,250 today; the same $10,000 in the S&P 500 would be worth roughly $86,600.
And the operating business is not coasting. In the June quarter — Q3 of fiscal 2026, Cook’s final full quarter — Apple posted $109.4 billion in revenue, up 16% year over year and a June-quarter record. Read that again: Apple now earns in a single quarter what it earned in all of 2011. iPhone revenue alone was $54.25 billion, up nearly 22% on strong iPhone 17 demand, with June-quarter records in every geography. Services brought in $30.74 billion, up 12% (though it did miss Wall Street’s estimate, which Apple pinned on currency headwinds). The active installed base is now north of 2.5 billion devices.
That services line is the real Cook invention. Jobs built the products; Cook built the annuity. App Store fees, iCloud, Apple Music, Apple TV, Apple Pay, Apple News+ — a recurring-revenue business layered on top of the hardware so the company stopped living and dying by the product cycle. That is an operations person’s masterpiece, and it is why Apple sailed through flat iPhone years without flinching.
Here’s where an honest assessment has to slow down. For all the financial fireworks, the back half of Cook’s tenure drew a persistent criticism: Apple got extraordinarily good at monetizing what it already had, and noticeably slower at inventing the next thing. The Apple Watch and AirPods are genuine hits — multibillion-dollar categories conjured out of nothing. But Vision Pro landed as a stunning piece of engineering in search of a market, the car project consumed years and produced nothing shippable, and then generative AI arrived and Apple was simply late.
Not a little late. The Siri overhaul promised at WWDC 2024 slipped, slipped again, and became the most public product embarrassment of the Cook era. In a two-year window where the entire industry reorganized itself around large language models, the company with the most-used voice assistant on Earth was still shipping a warmed-over version of a 2011 product.
So Cook’s legacy is genuinely two-sided, and both sides are true at once: the most financially successful CEO tenure in the history of the technology industry, and a company that arrived at the AI era holding a hardware hand it hadn’t yet figured out how to play. He stays on as executive chairman of the board, where he’ll remain involved in the parts of the job he was always uncommonly good at — global policy, governments, trade, the diplomatic work of running a $4 trillion company in a fractured world.
Ternus is 51, which makes him fifteen years younger than Cook and strongly suggests Apple went looking for someone who could hold the job for a decade or more. He has been at Apple for 25 years — nearly half his life. It was only his second job out of college; the first was at a small virtual-reality outfit called Virtual Research Systems.
He came out of the University of Pennsylvania’s engineering school, swam on the Penn team, and built — for his senior project — a feeding arm that a person with quadriplegia could control with head movements. He joined Apple’s product design team in 2001, was a VP of hardware engineering by 2013, and took the SVP role in 2021.
The story that tells you the most about him he told himself, at Penn’s 2024 commencement. First year at Apple, past midnight, at a supplier facility far from home, holding a magnifying glass and counting grooves on a screw head for the Apple Cinema Display — arguing, because the parts had 35 grooves and the spec called for 25. “What the hell am I doing? Is this normal?” he remembers thinking. At Apple, it was.
His portfolio since then reads like a tour of the modern Apple ecosystem: AirPods, Apple Watch, Vision Pro, and — the big one — the transition off Intel onto Apple silicon, arguably the most successful platform migration any computer company has ever executed. Most recently he shepherded the MacBook Neo, Apple’s $599 answer to the Chromebook, which hits that price by doing something clever rather than something cheap: powering a laptop with an iPhone-class chip. “We never want to ship junk,” he told Tom’s Guide about it. “We want to ship great products that have that Apple experience, that Apple quality.”
Ask him about Steve Jobs and he doesn’t reach for a keynote moment; he reaches for a chest of drawers. Jobs pulled one away from a wall, looked at the back panel, and reflected on a carpenter who had made the part nobody would ever see beautiful anyway. Ternus says he thinks about that all the time. Cook’s parting note to staff hit the same theme: “Few people understand what it takes to build products that change the world the way John does.”
And now, the inheritance. Apple’s answer to its AI problem is a rebuilt Siri running on Google’s Gemini as its foundation, for a reported ~$1 billion per year. On its face it is a shrewd trade — Apple gets frontier-model capability now instead of in 2029, and it sidesteps the capital bonfire its rivals are standing around. Microsoft, Google, Amazon and Meta are each spending north of $100 billion on AI infrastructure. Apple is spending roughly one percent of that and licensing the output.
BUT — and it’s a large BUT — Apple’s entire competitive religion for twenty years has been owning the whole stack. Silicon, OS, services, retail, all of it, welded together until the seams disappear. If the intelligence layer of the next computing paradigm arrives from Mountain View on a renewable contract, Apple has voluntarily rented out the most strategically important component in its own product. Analysts have been blunt about the risk: the tight hardware-software integration that is Apple’s advantage now has a rented middle.
Then there’s the bill nobody has solved. On his final earnings call, Cook admitted Apple does not yet have “a complete plan” for what AI compute will cost once 2.5 billion devices’ worth of users actually start hammering it. Inference isn’t a one-time engineering expense; it’s a meter that spins every single time someone asks Siri a question. Apple’s mid-40s gross margins were built in a world where software shipped once and cost effectively nothing to run. That world is over, and the transition happens on Ternus’s watch.
Ternus also inherits a substantially new leadership team, because Apple just went through its biggest executive turnover in years. Jeff Williams retired as COO and was succeeded by Sabih Khan. AI chief John Giannandrea announced his retirement. Alan Dye, the longtime head of user interface design, left for Meta. Lisa Jackson and general counsel Kate Adams are both on their way out. Amar Subramanya — a Google and Microsoft veteran — now runs Apple Foundation Models, machine learning research and AI safety, reporting to Craig Federighi. And Johny Srouji, the architect of Apple silicon, was elevated to a newly created chief hardware officer role.
Then, in the final days of Cook’s premiership, came the one that really lands for anyone who has watched an Apple keynote in the last quarter century: Phil Schiller is stepping back. Per a Bloomberg report on August 31st, Schiller — 66 years old, Apple’s SVP of worldwide marketing for two decades and an Apple Fellow since 2020 — is no longer running the App Store or the product events team. To be precise, he is not leaving the company; he’s scaling back to work on unspecified initiatives, which more often than not is how a long goodbye starts. The App Store returns to Eddy Cue, who ran it until Schiller took it over in 2015 and who now oversees services broadly. Schiller’s deputy Nola Weinstein takes the events team, reporting to communications VP Kristin Huguet Quayle. Apple never announced any of it publicly.
Understand what that means symbolically. Schiller was the guy on stage saying “Can’t innovate anymore, my ass” about the Mac Pro; he was the voice of Apple marketing through the iPod, the iPhone, and the entire App Store economy, and he was Apple’s chief witness in the Epic trial. He is the last of the Jobs-era stage presence to step away from operating responsibility. The generation that built the iPhone is handing off to the generation that will have to build whatever comes after it — and that handoff finished, quietly and without a press release, the week Ternus took the chair.
That is either a dangerous amount of change all at once, or exactly the clean slate a new CEO wants. More often than not, it’s both.
The first real test arrives fast: September 9th, the iPhone 18 event, Ternus’s debut as the guy the whole thing rolls up to. Expect the hardware to be excellent — that has never been the question with this man — and watch instead for how confidently Apple talks about intelligence it doesn’t own.
The deeper question is what an engineer-CEO does differently over five years. My read: Ternus pushes hard on the things Apple can win by building rather than buying — on-device inference, custom silicon with far more headroom for neural work, in-house modems, Apple’s own server silicon for Private Cloud Compute — so that the Gemini deal becomes a bridge rather than a dependency. A hardware person’s instinct, handed a rented component, is to go build the thing. Apple has $4.6 trillion of market cap and the best chip team on Earth with which to try.
Will it work? Nobody knows yet, and anyone who tells you otherwise is guessing. What we do know is that Apple just handed itself to someone whose entire career has been about the unglamorous discipline of making the back of the drawer beautiful. After a decade of being accused of coasting on the iPhone, that is a genuinely interesting bet — and the road ahead is going to be fascinating to watch.
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