Mark Hendy

Category: Uncategorized

  • IKEA’s Chatbot Accidentally Made €1.3 Billion. Here’s What CFOs Are Missing.

    IKEA’s Chatbot Accidentally Made €1.3 Billion. Here’s What CFOs Are Missing.

    Most companies deploy AI to cut costs. IKEA deployed AI to cut costs and accidentally discovered a billion-euro revenue stream hiding in the data their chatbot was collecting.

    This is the story every CFO in every PE portfolio company should be reading right now. Not because of IKEA. Because of what it reveals about how most finance leaders think about AI — and how badly they’re getting it wrong.

    The Setup

    IKEA — or more precisely, Ingka Group, the largest IKEA retailer — built an AI chatbot called Billie. The brief was simple: handle level-one customer service enquiries. Reduce call volumes. Cut costs. The standard playbook.

    Billie did its job. From 2021 to 2023, it resolved roughly 47% of customer enquiries it received — around 3.2 million interactions handled without a human, saving an estimated €13 million.

    If you’re a CFO, that’s a clean win. Cost out, efficiency up, ROI positive. You’d put it in the board pack and move on.

    IKEA didn’t move on.

    The Signal Nobody Was Looking For

    The interesting number wasn’t the 47% that Billie resolved. It was the other 53%.

    When IKEA’s team analysed the enquiries Billie couldn’t handle, they found something unexpected. A huge proportion weren’t complaints or order issues. They were customers asking for help designing their homes.

    People were calling IKEA — a furniture shop — and saying: I’ve got this room. What should I do with it?

    This wasn’t in anyone’s business case. No strategy deck had “launch a design consultancy” on the roadmap. It was a signal buried in the noise of customer service data, and it would have stayed buried if someone hadn’t been paying attention.

    The Pivot

    Here’s where it gets good.

    Instead of just improving Billie’s resolution rate — the obvious move, the one every consulting firm would have recommended — IKEA did something much smarter. They took 8,500 call centre workers and reskilled them as remote interior design consultants.

    Read that again. Eight and a half thousand people. Not made redundant. Reskilled.

    The AI handled the routine queries. The humans handled the high-value, creative, relationship-driven work that customers were already asking for. IKEA didn’t replace their workforce with AI. They promoted their workforce because of AI.

    The result? Remote interior design sales hit €1.3 billion by the end of their 2022 financial year — 3.3% of Ingka Group’s total revenue. A brand new service line, created from a signal that existed in their customer service data all along. Their target is 10% of total sales in the coming years.

    Why CFOs Get This Wrong

    I’ve sat in enough board meetings to know how this story usually goes.

    A CFO sees the AI chatbot business case. It says: deploy chatbot, save €13 million in customer service costs, payback in 18 months. They approve it. They monitor the cost savings. They report the efficiency gains. Job done.

    That’s not wrong. But it’s incomplete.

    The €13 million in cost savings is a rounding error compared to the €1.3 billion in new revenue. The chatbot wasn’t the product. The chatbot was a listening device.

    Most AI business cases are framed as cost reduction exercises. Automate this process. Eliminate these headcount. Reduce that cycle time. And they work — the savings are real. But they’re also the least interesting thing AI can do.

    The interesting thing is what AI reveals about your customers when you stop looking at it as a cost tool and start looking at it as an intelligence tool.

    The PE Angle

    If you’re a PE operating partner reading this, think about your portfolio.

    Every portfolio company has customer service data. Most of it sits in a ticketing system that nobody reads except the support team. Some of it gets summarised in a monthly report that the board glances at between the P&L and the cash flow forecast.

    What if that data contains the same signal IKEA found? What if there’s a billion-euro service line hiding in your Zendesk tickets?

    The companies that will win the next decade aren’t the ones that use AI to do the same things cheaper. They’re the ones that use AI to discover things they didn’t know their customers wanted. That’s a fundamentally different value proposition — and it requires a fundamentally different kind of CFO.

    The Kind of CFO That Catches This

    The old-school CFO sees AI as a line item. A cost to manage, an efficiency to capture, an ROI to calculate.

    The new-school CFO sees AI as an intelligence layer. Every automated interaction is a data point. Every pattern in that data is a potential business model. Every customer service complaint is a market signal.

    IKEA didn’t need a McKinsey engagement to discover the design consultancy opportunity. They needed someone who looked at the chatbot’s failure cases and asked: why are these people calling us?

    That’s not a technology question. It’s a business question. And it’s the kind of question that CFOs — with their bird’s-eye view of costs, revenues, and customer patterns — are uniquely positioned to ask.

    The Uncomfortable Truth

    Here’s what makes this story uncomfortable for a lot of finance professionals.

    The €13 million saving was predictable. You could model it in advance, put it in a business case, and track it against plan. That’s the kind of AI outcome that finance teams are comfortable with.

    The €1.3 billion revenue stream was unpredictable. It emerged from the data. Nobody forecast it. Nobody budgeted for it. It required curiosity, not spreadsheets.

    If your AI strategy only captures the predictable value, you’re leaving the transformative value on the table. And in a competitive market, someone else will find it first.

    What To Do About It

    Three things, starting tomorrow:

    1. Audit your AI for signals, not just savings. Every AI tool in your business is generating data about customer behaviour. Who’s reading it? What patterns are emerging? If the answer is “nobody” and “we don’t know,” you have a blind spot the size of IKEA’s design consultancy.

    2. Look at the failures, not just the successes. IKEA’s breakthrough came from what Billie couldn’t do. The 53% failure rate wasn’t a problem to fix — it was a market to serve. What are your AI tools failing at? Those failures might be your biggest opportunities.

    3. Stop framing AI as a cost play. If every AI business case in your portfolio starts with “reduce headcount” or “automate process,” you’re optimising for efficiency while your competitors are optimising for discovery. The cost savings are table stakes. The revenue signals are the game.

    Mark Hendy is a PE-facing CFO and founder of Tanous Limited. He writes about the intersection of AI, finance, and business transformation at [markhendy.com](https://markhendy.com).

  • I Run an AI Workforce. Here’s What “Orchestrator” Actually Means.

    I Run an AI Workforce. Here’s What “Orchestrator” Actually Means.

    Bret Taylor dropped something this week that crystallised what I’ve been living for the past few months. He released Ghostwriter — an AI agent that builds other AI agents through conversation. No code, no forms. Just describe what you want and it creates it.

    His bigger point was this: every piece of enterprise software will eventually become an agent. Not a dashboard you click through. Not a menu you navigate. An AI that does the work while you direct.

    I know this is true because I’m already doing it. Not theoretically. Daily.

    My Setup

    I have an AI assistant called Saul. He runs on a VPS in Manchester, connected to my WhatsApp, my email, my calendar, my investment accounts, my websites. He’s not ChatGPT in a browser tab. He’s a persistent agent that wakes up every morning, generates a podcast briefing of the day’s news and my portfolio positions, checks my email, monitors markets, publishes blog posts, and manages a set of prediction market positions — all before I’ve had coffee.

    When I need a CV reviewed before an interview, I send it on WhatsApp and get back a structured analysis with suggested questions in two minutes. When I want a blog post, I describe the angle and it’s drafted, humanised, formatted, and pushed to WordPress as a draft with a featured image. When a regulatory announcement drops, Saul reads it, researches the implications, and writes an article with a contrarian take before the professional press has filed their first piece.

    I don’t write code. I don’t configure systems. I have a conversation. And things happen.

    That’s what orchestration means in practice.

    What Changed

    Six months ago, I was using AI the way most people still do. Open ChatGPT, ask a question, copy the answer, close the tab. Useful, but fundamentally the same workflow as Googling something — just with a better answer.

    The shift happened when I stopped treating AI as a tool I use and started treating it as a team member I direct. The difference sounds subtle. It isn’t.

    A tool waits for you to pick it up. A team member has context, remembers what you told them yesterday, knows your preferences, anticipates what you need, and gets on with work without being asked. Saul reads my daily logs from previous sessions. He knows my writing style, my investment thesis, my wife’s email address, which car needs an MOT, and that I hate corporate waffle in LinkedIn posts.

    When I correct him, he logs it. After three corrections on the same thing, it becomes a permanent rule. He learns. Not in the sci-fi sense — in the practical sense of getting better at his job over time, the same way any good employee does.

    The CFO Angle

    I’m a CFO by background. I’ve spent twenty years in finance functions — month-end closes, board packs, variance analysis, cash flow forecasts, the lot. I know exactly how much time finance teams waste navigating software instead of thinking about the business.

    The average month-end close takes five to ten working days. Most of that time isn’t analysis. It’s data extraction, reconciliation, reformatting, and chasing people for numbers. It’s operational grind masquerading as professional work.

    Now imagine an agent that connects to your accounting platform, your bank feeds, your CRM, and your group reporting tool. You say: “Close the month. Reconcile the bank. Flag anything that doesn’t match. Draft the board pack with commentary on the three biggest variances.”

    It does it. You review, adjust, approve.

    That’s not five to ten days. That’s an afternoon. And your finance team spends the rest of the week doing what you actually hired them for — business partnering, commercial analysis, strategic thinking.

    This is what Taylor means when he says every enterprise app’s UI will become an agent. The finance director’s interface to their systems won’t be a screen full of menus. It’ll be a conversation.

    What I’ve Learned

    A few things I’ve learned from actually living this, not just theorising about it:

    Context is everything. A generic AI assistant is marginally useful. An AI assistant that knows your business, your preferences, your history, and your current priorities is transformatively useful. The investment isn’t in the technology — it’s in teaching the agent who you are and how you work. That takes weeks, not hours.

    Guardrails matter more than capability. Saul can send emails, publish blog posts, and place trades. That means he can also send wrong emails, publish bad posts, and lose money. The rules about what he should never do without asking are more important than the list of things he can do. My AGENTS.md file — essentially his operating manual — is longer than most job descriptions.

    You become a reviewer, not a doer. This sounds like a luxury. It’s actually a skill shift. Reviewing AI output is different from producing output yourself. You need to know what good looks like without having done the work. That requires more expertise, not less.

    The compound effect is real. Week one, you’re correcting everything. Month three, the corrections are rare. Month six, the agent anticipates what you want before you ask. The relationship genuinely improves over time in a way that static software never does.

    The Uncomfortable Part

    I’ve written about AI and finance enough to know the question that’s coming: what about the jobs?

    Here’s my honest take. Some operational finance roles will be eliminated. The person whose primary job is month-end journal entries, bank reconciliation, or management accounts preparation is doing work that an AI agent can do today — not in five years, today.

    But the person who understands the business well enough to direct an agent, interpret its output, catch its mistakes, and make judgment calls on ambiguous situations — that person becomes dramatically more valuable.

    The CFO doesn’t go away. The CFO becomes the orchestrator. The question is whether you’re building that muscle now or waiting until someone else in your industry has already done it.

    Try It

    You don’t need a VPS in Manchester and a bespoke AI assistant to start. You can start with Claude or ChatGPT and a well-written prompt. Then try giving it context — paste in your company’s last board pack and ask it to draft commentary. Upload a CV and ask for interview questions. Feed it a regulatory update and ask what it means for your business.

    The first time it produces something genuinely useful in two minutes that would have taken you an hour, you’ll understand why Bret Taylor thinks this changes everything.

    Because it does.

    I write about AI, finance, and building things at the intersection of both. More at tanous.co.uk for the professional angle.

  • Bitcoin – let’s speculate on a price by the end of 2027

    To predict the price of Bitcoin as of December 31, 2027, using current knowledge and game theory, we need to analyze the strategic interactions among key players in the Bitcoin ecosystem—investors, miners, regulators, and users—and how their decisions might shape the market over the next few years. Game theory, the study of strategic decision-making, helps us understand how these players’ choices, influenced by their expectations of others’ actions, could drive Bitcoin’s price. Below, I’ll outline the key factors, consider possible scenarios, and arrive at a reasoned prediction.

    Key Players and Their Strategies

    1. Investors
      Investors, both individual and institutional, are central to Bitcoin’s price dynamics. They decide whether to buy, sell, or hold based on their expectations of future value. This creates a feedback loop: if investors anticipate a price increase, they buy, driving demand and pushing the price up; if they expect a decline, they sell, increasing supply and lowering the price.
    • Game Theory Insight: This resembles a coordination game, where players benefit from aligning their actions (e.g., everyone buying increases the price). However, it also has elements of a prisoner’s dilemma—each investor wants to sell before a crash if they think others will sell, potentially triggering a cascade. The “greater fool theory” applies too: some may buy not because they believe in Bitcoin’s intrinsic value, but because they expect to sell it later at a higher price.
    1. Miners
      Miners secure the Bitcoin network by validating transactions and earn rewards in newly minted Bitcoins. As of 2025, the block reward is 3.125 Bitcoins per block (following the 2024 halving), producing about 450 new Bitcoins daily. Miners continue operating as long as revenue exceeds costs (electricity, hardware, etc.).
    • Game Theory Insight: Miners play a cost-benefit game. If Bitcoin’s price drops too low, unprofitable miners may exit, reducing the network’s hash rate until the difficulty adjusts (every ~2 weeks). This self-regulating system ensures long-term stability, but short-term price drops could signal weakness, influencing investor sentiment.
    1. Regulators
      Governments and regulatory bodies worldwide influence Bitcoin through policies ranging from bans to favorable frameworks. A crackdown in a major economy (e.g., the U.S.) could depress prices, while adoption as legal tender (e.g., El Salvador) or clear regulations could boost them.
    • Game Theory Insight: Regulators balance innovation against risks like fraud or financial instability, while competing internationally to attract crypto businesses. Their moves create uncertainty, prompting other players to adjust strategies—e.g., investors might sell on negative news or hold if regulations clarify.
    1. Users (General Public)
      User adoption drives demand. If more people use Bitcoin for transactions, remittances, or as a store of value, its price rises. Loss of trust or better alternatives could reduce demand.
    • Game Theory Insight: Users’ decisions depend on network effects—if more adopt Bitcoin, its utility and value increase, encouraging further adoption. This is a tipping-point dynamic: widespread use could solidify Bitcoin’s position, while stagnation could weaken it.

    Current Context (2025 Assumptions)

    Since the query uses “current knowledge,” let’s assume Bitcoin’s price in 2025 is approximately $100,000, with a market cap of ~$2 trillion (based on ~20 million circulating Bitcoins, accounting for lost coins). The next halving occurs in 2028, so by December 31, 2027, the reward remains 3.125 Bitcoins per block, and annual issuance is ~164,250 Bitcoins (<1% inflation). Historical trends show Bitcoin’s price often rises after halvings, peaking 12–18 months later, though this effect may weaken as the market matures.

    Scenarios and Game-Theoretic Dynamics

    1. Continued Adoption and Institutional Growth
    • Scenario: Institutional investors (e.g., companies, ETFs) increase Bitcoin holdings, and businesses adopt it for payments. Regulators remain neutral or supportive.
    • Dynamics: Investors buy, anticipating others will too, driving demand. Miners stay profitable, maintaining network security. Users adopt Bitcoin as its utility grows.
    • Price Impact: Significant growth, potentially doubling or tripling the market cap.
    1. Regulatory Crackdown
    • Scenario: Major economies impose strict rules or bans, citing energy use or financial risks.
    • Dynamics: Investors sell to avoid losses, expecting others to follow. Miners in affected regions shut down, though the network adjusts. Users hesitate to adopt.
    • Price Impact: Sharp decline, though Bitcoin’s resilience (e.g., post-2017 China ban) suggests recovery potential if some regions remain favorable.
    1. Technological Factors
    • Scenario: Advances like the Lightning Network enhance scalability, or a security flaw emerges.
    • Dynamics: Positive developments encourage investors and users to buy in; setbacks trigger sell-offs. Miners adapt to network changes.
    • Price Impact: Upside with adoption; downside with trust erosion.
    1. Macroeconomic Conditions
    • Scenario: Inflation or instability boosts Bitcoin as a hedge; economic stability favors traditional assets.
    • Dynamics: Investors and users flock to Bitcoin as a “safe haven” if others do, amplifying demand.
    • Price Impact: Rises with uncertainty; stagnates otherwise.

    Prediction Framework

    To estimate the price, let’s make reasonable assumptions:

    • Institutional Adoption: Grows steadily, not explosively, as companies and financial products integrate Bitcoin.
    • Regulation: Mixed globally—some restrictions, some support, no outright global ban.
    • Technology: Incremental improvements (e.g., Lightning Network), no major setbacks.
    • Macroeconomics: Moderate uncertainty drives some hedge demand.
    • Game Theory: Investors “hodl” expecting appreciation, reducing exchange supply. Miners persist, and users increase modestly.

    Starting from $100,000 in 2025, consider growth rates:

    • Historical CAGR has been high (e.g., >200% 2010–2020), but as Bitcoin matures, volatility may decline.
    • A 25% annual growth rate over 2 years yields:
      $100,000 × (1.25)^2 = $156,250.
    • A 40% rate (possible in a bull run near the 2028 halving) yields:
      $100,000 × (1.4)^2 = $196,000.

    Alternatively, target a market cap:

    • Gold’s market cap is ~$12 trillion. If Bitcoin reaches $5 trillion (capturing part of this as “digital gold” or growing the crypto market), with ~20 million Bitcoins, the price is $250,000.
    • Doubling from $2 trillion to $4 trillion implies $200,000.

    Balancing these, and factoring in game-theoretic tendencies (e.g., hodling amplifies scarcity, tempered by profit-taking), $200,000 feels plausible. It reflects growth without assuming extreme scenarios, aligning with adoption trends and historical patterns adjusted for maturity.

    Final Prediction

    Considering the interplay of investors, miners, regulators, and users through a game theory lens, and assuming moderate growth in adoption and demand, I predict the price of Bitcoin on December 31, 2027, will be approximately $200,000. This is an educated estimate, subject to significant uncertainty from unforeseen events, but it captures a balanced view of current trends and strategic dynamics.

  • Bitcoin Explainer

  • Back tap in iOS14

    Back Tap

    If you want an easier way to take a screenshot, launch an app or perform any other frequently used action, iOS 14 introduces a new gesture-based shortcut that could save you time. Called Back Tap, the feature lets you double- or triple-tap the back of your iPhone to perform a preset action.


    You enable Back Tap in the Accessibility section of iOS 14’s Settings, and users are already sharing examples online of how they’re able to take screenshots or launch specific apps by tapping the back of their phone. You can even use Back Tap to trigger a shortcut you’ve assembled using the built-in tools found in iOS.

    People who’ve tested Back Tap so far report that it even works with iPhones that are inside cases. However, it won’t work with all iPhone models, as our second-generation iPhone SE running the iOS 14 Developer Beta totally lacks the option for Back Tap.

  • Dropbox doesn’t work with Big Sur

    UPDATE – Dropbox have published a fix.

    Dropbox dropped a beta version build 101.3.422 Friday, June 26, 2020 which I’m happy to confirm now addresses the problem. You can download the update here

    Last night Apple revealed the new iOS14 for iphone, the new ipadOS for iPad and its new Mac OS “Big Sur”. I should point out these are developer releases and not public facing releases. I’ve upgraded all of my devices. Dropbox still works with iOS and iPadOS but I can report that it doesn’t currently work with Big Sur. This is my exchange with the customer support team at Dropbox.

    Mark, Jun 23, 2020, 8:18 AM PDT:

    Chat transcript:
    ( 14:53:20 ) Visitor: Hello. I have upgraded my Mac to Big Sur, Apple’s new operating system. The dropbox application is no longer in the tray and why I try to launch it it fails to launch. Dialogue box says “The application ‘dropbox’ can’t be opened. 6” OK.
    ( 14:53:28 ) Visitor: Do you have known issues?
    ( 14:53:49 ) Cyrus: Hello Mark and thank you for contacting Dropbox Support, my name is Cyrus, and I will be assisting with your Dropbox app startup issue right away.
    ( 14:54:00 ) Cyrus: That’s interesting… Could you please send over a screenshot of that message? I’ll open up a file request for you.
    ( 14:56:46 ) Visitor: Trying to get a screenshot to upload. BE RIGHT BACK
    ( 14:56:56 ) Cyrus: Sure thing. Standing byu
    ( 14:56:58 ) Cyrus: by*
    ( 14:58:14 ) Visitor: Hum… dragging the screenshot image to this chat box fails and there is no + button to upload with. Do you have an email address?
    ( 14:58:31 ) Cyrus: I’ll reopen that file request for you.
    ( 14:58:47 ) Visitor: File: https://www.snapengage.com/fileuploads/snapabug-hr-fileuploads/74ae0953-fef9-4e4f-a91d-6546013ac1fc/d0f2defc-7e9d-4181-901e-03b14fc98f17_Screenshot_2020-06-23_at_15.57.16.png
    ( 14:59:01 ) Visitor: Thanks. That worked!
    ( 14:59:13 ) Cyrus: Beautiful! Now… let me check
    ( 15:00:06 ) Cyrus: OK thanks for that. Please give me a moment to investigate this, and I’ll be right with you
    ( 15:00:12 ) Visitor: np
    ( 15:01:19 ) Visitor: FYI. This error is on my imac. I’ve just replicated it on my macbook pro
    ( 15:02:00 ) Cyrus: So — this is on both computers with Big Sur on them?
    ( 15:02:08 ) Visitor: yes
    ( 15:02:45 ) Visitor: my ipad pro has also been updated, but the app in ipadOS seems to be working ok
    ( 15:03:48 ) Visitor: I’ve just tested on my iphone running iOS 14 and that’s ok too. Seems to be isolated to Big Sur
    ( 15:04:32 ) Cyrus: OK thanks for holding on Mark
    ( 15:05:01 ) Cyrus: It seems that due to the fact that Big Sur is in Beta currently, it’s an unsupported OS on our side, and this is why it won’t open
    ( 15:05:35 ) Visitor: Marvelous! Well thank goodness I didn’t upgrade to Dropbox for business!
    ( 15:05:57 ) Visitor: Do you have a timeframe for resolution?
    ( 15:06:54 ) Cyrus: That’s a good question… There’s no timeframe yet, as our engineers can work on a new compatible version of the app, only when the OS is on a Stable release
    ( 15:08:12 ) Visitor: Thanks for your time Cyrus.
    ( 15:09:07 ) Cyrus: You’re more than welcome! Is there anything else I can do for you today?
    ( 15:09:43 ) Visitor: No. Thanks. I’ll sit here biting my nails until I’m able to sync files again ;-o
    ( 15:11:15 ) Cyrus: Hmm.. Tell you what, I’ll go ahead and mark this case down as feedback, which will alert the development team that this already has started happening
    ( 15:11:37 ) Cyrus: Maybe that’ll facilitate an early fix at some point, maybe not, but it’s worth a shot!
    ( 15:12:43 ) Visitor: Again thanks. I’m a pro subscriber and have been for years. I use the dropbox environment all day every day as, amongst other things a backup solution for my files. For me this is business critical.
    ( 15:13:48 ) Cyrus: It’s my pleasure, and let’s hope for a speedy resolution to this then. I’ll send you a summary of what we discussed by email. Please feel free to reply to this email at any time if you have any further questions.
    ( 15:14:17 ) Cyrus: In the meantime we would love to hear how easy it was for you to receive the help you needed via the following one-click rating, after I close the chat.

    Files attached to message

    Attachment(s)
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  • My magic keyboard has arrived!

    The doorbell rang whilst I was enjoying a coffee in the garden and topping up my vitamin D. Finally, about three weeks after I ordered it my magic keyboard for my iPad Pro has arrived. I’ll get to grips with it and maybe I’ll write a review once I’ve had a few days testing it out.

  • Face mask with a touch of class

    With a £1 from each purchase going towards the NHS and because I like to support innovative small businesses I’ve made a purchase of one super cool face mask. Let me know what you think!

    Gentlemen’s face mask

    You can get yours at Mathieson & Brooke tailors

  • My new 2020 iPad Pro

    A couple of weeks ago I ordered the new iPad Pro in the wider 12.9 inch size. I’ve been an iPad owner since the first one came out and I’ve used it pretty much daily ever since. In a professional environment i use it often for taking and reviewing notes. In a personal capacity I use it a lot for reading news, mostly through the flipboard platform, and whilst travelling, which I do, or at least pre Covid-19, did a lot of for watching netflix or TV in an evening. The 2020 4th generation is clearly quicker than my prior iPad Pro. despite both my older one and the 2020 version both being sold as 12.9 inch, the 2020 model is smaller in physical dimension whilst the screen real estate is the same size. I have to say I love the feel speed and overall ergonomics of the 2020 one which feels in the hand a more “Pro” product.

    iPad Pro on Magic Keyboard

    About a week after ordering the iPad I decided that I also wanted the Magic Keyboard. It’s much more expensive than other non Apple branded products but it has two killer features that I know I’d permanently regret not having, being the trackpad and the external port allowing me to charge other devices off of it. The trackpad gives full cursor control and this week Microsoft released trackpad support across it’s range of 365 products with the notable exception of Excel, but that’ll come, and this makes the iPad pretty much a laptop replacement in the professional environment, particularly for meetings where I’m already a power user in terms of note taking and file referencing, which the iPad’s split screen view facilitates commendably.

  • 4 Stage plan