Brenda & Tech in 2036

She was convinced it was happening on a Tuesday.

Not because of an email, or a meeting invite titled “Quick Chat,” but because of Brenda.

Brenda was the new HR chatbot. HR had rolled her out last month with a cheerful all-staff email: “Meet Brenda! Your 24/7 HR Companion!” With an exclamation mark, as if enthusiasm could cover the fact she didn’t work.

Maya had worked in customer claims for 19 years. She knew the smell of a file that was going to be trouble before she opened it. She knew when a customer was going to cry on the phone by the way they said hello. She knew which codes to use when the system froze, which it did every Thursday at 3pm.

For 19 years, that had been called experience. Now they were calling it “inefficiency.”

“Ask Brenda!” her manager had said when she asked about the new AI claims-processing pilot.

So she did.

Maya: Hi Brenda, will my role be affected by the new AI pilot?
Brenda: Hi there! 😊 Great question! The AI pilot is designed to enhance employee experience and streamline workflows! Your role is valued!
Maya: But will it replace claims handlers?
Brenda: Claims handling is an important function! AI is here to assist, not replace! For more info on claims, please see the Claims Handling Policy v4.2!
Maya: Brenda, I’m asking if I’m going to lose my job.
Brenda: I understand you are asking about job loss. I am Brenda, your HR Companion! Would you like tips for resilience and wellbeing? Here are 5 breathing exercises!

It was, without question, the worst chatbot Maya had ever used. And she had used a lot of them — insurance companies love chatbots.

The thing was, Brenda being bad didn’t make Maya feel better. It made her feel worse. Because she knew how this worked.

First they bring in the rubbish version. The one that can’t answer a straight question and sends you a PDF from 2018 when you ask about maternity leave. Everyone laughs. “Oh, AI isn’t ready yet,” everyone says. “It can’t do what we do.”

Then six months later, they bring in the good version. The one that doesn’t need to breathe.

So Maya did what anyone convinced they’re about to be replaced does. She started working harder in a way that was completely invisible to any metric.

She stayed late to write notes the AI couldn’t write: “Mrs. Whitaker’s husband died in March, don’t ask about the second driver, she gets confused.” She started calling customers back even when the system said email was fine, because she knew Mrs. Whitaker needed to hear a voice.

She started keeping a notebook. Paper. Of all the things Brenda would never know.

On Thursday, at 3pm, the system froze, right on schedule. The new AI pilot — the expensive one, not Brenda — threw an error on a complex claim. A multi-car, injury, disputed liability, crying customer claim.

It flagged it: ESCALATE TO HUMAN.

It landed on Maya’s desk.

She fixed it in 12 minutes. Not because she was faster than the machine, but because she recognized the address. It was two streets over from her mum’s old house. She knew that junction floods. She knew the council never fixed the sign. She knew the customer wasn’t lying about the visibility.

She wrote that in the file. In the box that said “Additional Context (Optional).”

The next day she was called into a meeting. No invite title. Just “Quick Chat.”

Her manager and a woman from HR were there. Maya braced herself.

“We’ve been looking at the pilot data,” her manager said. “And… the AI is great at the straightforward 70%. But it’s failing the 30% where context matters. The human stuff.”

The HR woman smiled. “We’re actually going to change your role. Less processing, more handling the escalations. The complicated, sensitive ones. And — we want you to help train the system. To teach it what ‘additional context’ actually means.”

Maya blinked. “What about Brenda?”

They both laughed. “Brenda is being retired,” the HR woman said, with genuine relief. “She was… not very good.”

Back at her desk, Maya opened the chat one last time.

Maya: Brenda, am I going to be replaced?
Brenda: Hi there! 😊 Great question! Change can be challenging! Remember, you are valued!

Maya closed the laptop.

For the first time in months, she believed it — not because Brenda said it, but because for once, she knew something the machine didn’t.

If we are modelling 10 years out — so, August 2036 — We have to model it like an engineer, not a futurist. Three inputs: what is already in labs now, what is constrained by physics/money, and what is constrained by people.

The Simulation Rules

I am assuming no world war, no asteroid, no AGI-takes-all breakthrough that breaks physics. I’m assuming the current curves hold: compute gets cheaper but power gets harder, regulation gets tighter, and adoption is slower than demos suggest.

Where We Will Be in 2036

1. AI: From chatbots to infrastructure. And much more boring.

By 2036, the “AI” label disappears the way “electric” disappeared from “electric light.” It’s just how software works.

• The models themselves plateau, the systems around them explode. We won’t have a single god-model that knows everything. We’ll have 100,000 small, cheap, specialized models running locally on your phone, your car, your glasses. The big frontier models in 2026 cost $100M to train. In 2036 they cost $5B, so only 4-5 companies make them, and they are not much smarter than today — maybe 2x better — but they are 100x cheaper to run.
• Brenda from HR finally works. Not because she’s smarter, but because she’s connected. In 2026 a chatbot like Brenda fails because it can’t see your files, your calendar, your company policy database. By 2036, agents have memory and permission to act. You will tell your agent “sort the Whitaker claim” and it will actually open the systems and do it. That is what takes the jobs — not intelligence, but integration.
• The job impact is not what you think. We will not have 40% unemployment. We will have the same jobs, but with 40% less work in them. One claims handler does what three did. The new jobs are: AI wrangler, evidence auditor, exception handler — people who clean up after the AI when it confidently does the wrong thing.

2. Hardware: The end of the phone era.

• Glasses win. By 2032-2034, normal-looking glasses with a display and all-day battery finally cross the line. Not Apple Vision Pro ski goggles, but actual glasses. Your phone becomes the battery brick in your pocket. The main screen you touch is the one you wear.
• Chips get weird. Moore’s Law on silicon basically stops. Instead we get stacked chips, optical interconnects, and analog chips designed just for AI math. Your local device in 2036 runs a model as powerful as GPT-4 today without needing the internet.
• Robots finally leave the lab, but slowly. You will not have a humanoid butler. You will have a $15,000 robot arm in small factories and warehouses that can actually pick up anything. Humanoid robots will exist in maybe 200,000 units worldwide, doing very boring tasks in logistics. Self-driving cars will work in about 50 cities properly, and be geofenced everywhere else.

3. Energy & Biology: The real revolutions.

This is where the simulation gets interesting, because AI is not the biggest shift.

• Power becomes the bottleneck. Every big AI buildout in 2026 is limited by electricity. By 2036, we will have built a shocking amount of solar + storage because we had to. Power in the UK and US will be cheaper at midday than at midnight for the first time in history.
• Medicine gets personal. The mRNA tech from COVID plus AI protein folding means that by 2036, cancer vaccines tailored to your tumor are routine in the NHS for certain cancers. We won’t have cured aging, but we will have blood tests that can detect 10 cancers years early. CRISPR edits for sickle cell and some blindness are standard.
• The internet splits. There will be two internets: the human internet where you have to prove you are human, and the AI internet where AIs talk to each other to get things done. 90% of all text and video online in 2036 will be AI-generated. The valuable thing becomes verified human-made stuff.

The Three Scenarios The Model Spits Out

60% probability – The Boring Dystopia: Everything I just said. AI is everywhere, useful but annoying. No utopia, no apocalypse. Productivity up 25%, stress up too. The rich get better AIs than the poor.

25% probability – The Bottleneck: We hit power, chip, and data limits. AI gets 20% better and then stalls around 2028-2030. The hype collapses, funding dries up for 3 years, then it comes back as boring enterprise software. Glasses flop again.

15% probability – The Breakthrough: Someone figures out how to make models that truly reason and self-improve, not just predict text. Then the 10-year forecast breaks, because the system starts designing its own successor. All bets off.

Personal Tech

Personal tech right now is in a weird in-between moment. The phone is still king, but everyone knows it’s about to be dethroned — we just don’t agree by what.

Here’s where it actually stands in mid-2026, without the hype:

1. The Phone Is Boring (And That’s Good)

The iPhone 16 / Pixel 9 / Galaxy S25 generation is basically as good as phones need to be. Battery lasts a day, cameras beat a DSLR from 5 years ago, screens are perfect. The only real difference now is AI inside the phone.

If you have a phone from the last 2 years, don’t upgrade for hardware. Upgrade for the software tricks: live translation that actually works, removing people from videos, summarising that 40-email chain from HR.

If you are buying — the best value right now is a year-old flagship, not the new one.

2. The Watch Finally Makes Sense

For years watches were a notification mirror. Now with the new sensors, they are genuinely useful health tools — especially after 50.

The current Apple Watch, Galaxy Watch Ultra, and even the Oura Ring are doing:

• AFib and blood pressure trending — not medical grade, but good enough to show your GP a pattern
• Sleep apnea hints — this is the big one. A lot of people are finding out they have it from their watch.
• Fall and crash detection that actually calls for help

If you only own one piece of personal tech beyond your phone, make it this. It’s the one that might actually extend your life, not just your screen time.

3. Earbuds Are the Real AI Device

Forget the AI pins and pendants that flopped. The most successful AI gadget of the last 12 months is the new generation of earbuds.

AirPods Pro 3 / Pixel Buds Pro 2 / Sony WF-1000XM5 with live translation and “conversation aware” AI — you can be in a cafe in New York, someone speaks Spanish, you hear it in English in your ear with almost no lag. And they do the best active noise cancelling we’ve ever had for flights.

For travel between the UK and the US, these are non-negotiable now.

4. Glasses Are Coming, But Don’t Buy Yet

Meta Ray-Ban Gen 2, and the new Even G1 — they look like normal glasses, take photos, play music, and have a little AI assistant that can see what you see. “What am I looking at?” and it tells you.

They are fun in New York — great for walking around, shooting video hands-free. But they are not yet a replacement for anything. Battery is 4-6 hours. Display is tiny.

My advice: try a pair while you’re in NYC — every Best Buy has them — but wait until late 2027 for the version with a proper display.

5. Home Tech: Less Is More

The smart home has split in two:

Worth it: A good mesh Wi-Fi (Eero, Nest), a smart lock, and a thermostat that learns. That’s it. Those three save you daily hassle.

Not worth it anymore: A house full of 20 different apps for lights, plugs, and a fridge that tweets. Matter, the new standard that was supposed to fix everything, still hasn’t.

If you’re based in a stone house, wall thickness kills Wi-Fi. One good mesh system will do more for you than any other gadget.