Search results for: “printing”

Outside Perspective talk on The Dot LLM era
I gave a talk to strategists and planners from the Outside Perspective group on my recent paper The Dot LLM era? The talk looked to summarise some of the key takeaways that I had written and also reflects a slight refinement on my thinking given current events since I had drafted the paper over the Christmas holidays.

About Outside Perspective

Outside Perspective is a community of brand planners and strategists. All of the members of Outside Perspective are freelance or self-employed. The members clients are drawn from all around the world and all sectors.

My presentation was the first Outside Perspective huddle of the year, where strategists share expertise and areas of interest with their peers.

I have put in the slides at the appropriate places alongside my notes.

Dot LLM era for Outside Perspective

Good afternoon everyone. I hope I’m not depriving you too much from lunch. If I am, just tuck in, just go on mute if you are tucking in because otherwise it’ll make me hungry.

So The Dot LL era came from a question that I posed to myself. I was working at the time for a client who is a major AI company. I was looking at all of the stuff happening around me and thought that the company that I’m working for it’s probably going to be all right. But we do feel like as if we’re in a bubble. So I then started to think about the bubble and eventually pulled it into a paper.

We (the Outside Perspective) will share the PDF of this presentation and you can get the paper from the QR code later on. My thinking has been refined slightly, as I’ve thought about this presentation, just nuances here and there based on what’s been happening since I originally published the paper.

Key points in the presentation

One of the first things I was taught when I present was tell them what you will be presenting, present it, and then tell them what you told them. So this is me telling me what I’m going to tell you.

So as a technology, LLMs (large language models), what people call AI at the moment, are making lasting changes from business to culture. It’s changing aesthetics, even though might have a negative impact like AI slop. The cultural effects are going to stay with us and evolve, just like previous technologies have done from the printing press on.

Now looking at the economics, the question is what’s really going to happen? Because the AI sector has a valuation in trillions which is an insane amount of money to think about. There are two main challenges from an economic perspective which is where I actually really looked at this from:
- The amortisation risk so the speed at which the hardware becomes obsolete or literally burnt out is three to five years versus the likely time to pay off because of the trillions of dollars involved.
- The self-defeating economics of AI as I’ll go through in a bit more detail. Economics are a limitation as to how fast AI can actually be adopted without actually destroying the AI providers themselves.
Both factors give a very narrow margin of success for Dot LLM era players from a business perspective, they need to thread themselves through to land at just the in order to succeed.

The Long Boom

When I came up with the term dot LLM era I was thinking about parallels to the dot com era. I’ll talk a little bit about the dot com era as well because I realise some people might not be terribly au fait with it. By comparison, I lived it and have the scars of my professional involvement with it.

The dot com era happened at a time that Wired magazine termed the long boom. During this time you had US preeminence as the Warsaw Pact had collapsed and China wasn’t yet a member of the WTO. During the Clinton presidency there was a US government budget surplus, so the US had headroom for monetary policy interventions if needed.

So if something like COVID epidemic had happened back then, they would have had much more economic flexibility to actually deal with it than we had coming into 2020.

Today in the US at least, much more like the Reagan era that preceded the long boom.

The West is on the back foot, there’s a resurgent Russia waging an invasion in Ukraine and ‘active measures‘ in the rest of Europe. China which is resurgent economically and militarily and from an innovation perspective which I’ll touch on a little bit later. There is high government debt particularly in the US, but also in Europe and much of the developed world as well.

There is sticky inflation and the overall inflation figures that are quoted in the business press are actually lower than what people are actually seeing in the shops. Consumer sentiment about the economy is much worse than the headline inflation number would suggest.

Finally, there’s a slackening labour market. That isn’t about AI at the moment. Companies say, oh, well, due to AI, we’re making layoffs. Usually they’re making layoffs through cost cutting, outsourcing and offshoring roles, they might be doing a little bit of AI in the background because we’ve given employees access to Microsoft Copilot or similar. That doesn’t mean to say that AI won’t have an impact in the near future.

The Dot Com Bubble

When we talk about the dot-com boom, we tend to think about is one thing but it was actually three interrelated bubbles that were going on.

There was an online business bubble which was relatively low capital but had a high burn rate through that capital in an attempt to build a moat. This is what most people think of when they think about the dot com era. t

There was a smaller, less visible bubble related to open source software. With the internet, it suddenly became much more important because you had a way of contributing to open source projects and collaborating in a way that wasn’t available between different individuals or organisations previously. While open source made software development collaboration easier, and provided good quality software to download for free, businesses struggled to build a profitable open source business model.

Finally, there was a telecoms bubble which was capital intensive. There was a huge amount of infrastructure built out. There was vendor financing by manufacturers of networking equipment. There was industry incumbents, so companies like the BT in the UK or the Bells in the US. And then there was also new telecoms companies like Enron Broadband Services, MCI WorldCom and Qwest.

More on them in a bit later on. But with the graph on the right, what in fact you see is the peak that was reached on the NASDAQ in March 2020 was in It took the NASDAQ 15 years to hit that peak again after the dot-com bust later that year. This is considered to be not as bad as what happened during the 2008 financial crisis. But it gives you an idea of the way things can go.

Hyman Minsky financial instability hypothesis

I want to introduce an idea of Minsky moments.

Hyman Minsky, economist, he came up with his financial instability thesis. He considered this to be bound to three different steps that needed to occur.

First a self-reinforcing boom driven by easy credit. Our interest rates are higher than they’ve been, but they’re still relatively low from a historical point of view.

If you actually look at the amount of money and the valuations that are going into the likes of OpenAI and CoreWeave in January alone, you can clearly see that the self-reinforcing boom is under way.

The second step Minsky mentioned is a shock where investors re-examine cash flows and this is what’s often termed as a ‘emperor’s new clothes‘-type moment. They suddenly start asking questions like when are we actually going to get our money repaid let alone are we going to make an obscene amount of profit on that money. We’re not quite there yet, but there has been some signs of concern from investors, (for instance when Microsoft announced its recent quarterly results). There were always those dissenting voices, but they’re actually proved prescient only in hindsight.

Lastly, there’s a de-risking stage through rapid acid sales. So investors and management realise they’ve got a flaming bag of crap and want to hand it off to someone else. They want rid of it.

So let’s next think about those earlier three bubbles and think about how good analogy are they for our present era of technology.

Online commerce

So like the early web, pure-play LLMs like Anthropic and Open AI’s GPT are currently providing tokens at below their marginal cost. The cost you’re paying for to do AI actions is actually less than the cost those AI actions actually take to create. And that’s not thinking about the research and cost of capital invested in the company.

They’re losing money to build an AI moat just in the same way as e-tailers and service providers back in the dot-com era lost money in order to build a moat in a particular sector. For instance like Amazon did in books. Move forward 25 years and AI companies are so they’re trying to do the same for various different service models. The burn rates of dot-com failures mirror loss making AI businesses. But only at a surface level, dot-coms were capital light in comparison to their modern Dot LLM era counterparts.

Look at the dog sock puppet on the right, he was the mascot and brand spokesanimal from Pets.com. Pets.com had a horrendous burn rate for the time and went bankrupt. The cause of their bankruptcy was down to two reasons:
- The logistics of actually sending out bags of dog meal and rabbit bedding were expensive compared to the amount that was being charged. It took Amazon the best part of a decade to radically reduce the cost of logistics for its own business. Even now, Amazon benefits from Chinese government overseas postal subsidies given to China-based businesses on Amazon.
- The large amount of money they put into advertising and brand building. Around a dog sock pocket with attitude. Great marketing, but if the consumer proposition isn’t right the marketing can’t save your business.
Open source sofware

The open source bubble saw the rise of what’s known as LAMP. That stands for:
- The Linux operating system
- Apache HTTP web server
- MySQL as a database management system
- P was for the Perl, PHP and Python programming languages
If you’ve ever run a WordPress blog, all of that language probably sounds vaguely familiar to you because it is. Because that supports a lot of the web. Linux extended into laptops, tablets and cellphones including smartphones. (Apple products are based on a similar UNIX style software based on the Mach micro-kernel used in various BSD distributions).

During the dot com era there were numerous companies in this space. Red Hat was the outlier success with their enterprise grade support offering. Red Hat managed to sell themselves for $34 billion to IBM in 2019. Red Hat was the most successful exit and profitable business out of its peers, becoming the first of its kind to generate $1 billion in revenue.

Now you can see Chinese companies are competing against US rivals and winning a lot of users in the global south by providing open source and open weight models like Alibaba’s Qwen and Kimi K2.

These Chinese models provide perfectly usable models at lower costs. You can run the models on your own machines. They use a lot less processing power than US AI models, and are challenging closed AI models. Huawei have built a lot of infrastructure in the developing world, so you’ve got a lot of opportunity there that’s now closed off from American AI companies.

US organisations like Airbnb and Silicon Valley based VC companies are running these Chinese models for their own uses.

AirBnB is an interesting case; CEO Brian Chesky is a really good friend of Sam Altman, yet he’s still using to use open source software rather than use OpenAI because it makes commercial sense.

The telecoms bubble

The telecoms boom. There’s been a similar kind of optimism build out of massive infrastructure as happened during the telecoms boom. Back then, they invested about half a trillion in fibre-optic networks based on misreading of traffic growth data. In the dot-LLM era, we’re seeing orders of magnitude more investment across computing power, networking within the data centre and even data centre power generation.

The graph on the right just gives you an idea of how much AI capital expenditure has taken off.

Amortisation risk

I want to introduce you to some of the concepts. One I’ve alluded to already is this idea of hardware amortisation.

During the telecoms bust, there was dark fibre, so optical fibre networks that weren’t lit. Dark fibre that was laid in the 1990s had a useful life of at least a decade.

In the current dot LLM era the equivalent surplus would be GPUs and TPUs – the processors and the network internet connect hardware within the data centre that’s particularly used for training models has a useful life that becomes technically obsolete between three to five years. It’s usually more towards three years because they are used so intensively that a lot of the processors get damaged by the amount of heat generated from the extreme amount of processing they do.

With your laptop, even though things might run slow sometimes, 95% of the time your laptop processor is running idle in terms of what does unless you’re doing some like really hardcore 3d rendering, video editing or complex work in Photoshop.

Your computer’s processor aren’t running at full at full performance all day, all night. By comparison AI training processors wear out within three to five years depending whose numbers you believe.

The chart on the right gives you an idea of how over time a lot of the major hyperscalers have actually been increasing the amount of years that they actually write down their processor’s depreciation. While the the processors have stayed pretty constant in terms of that three-to-five year window that they have a life of before they need depreciation to zero.

A second aspect of this deprecation is that the amount of energy per token is dropping substantially with each new generation of chip. So a five year old chip, if it’s working is the cloud computing equivalent of an old decrepit gas-guzzler of a car.

Financial picture

From a financial perspective, the change in hardware amortisation has caught the attention of short sellers. The reason why, is that the AI hardware is collateral against loans for some AI companies. They have a mortgage out on their chips. So the length of time that those things have a useful life is really important. If you had a house that lasted three years and you’ve got a mortgage for five years, it’s not a great position to be in.

(The most high profile short seller is Michael Burry who runs a Substack newsletter. He’s the chap portrayed by Christian Bale in the film adaption of The Big Short. Extremely smart guy, not as arrogant as he appears in the Christian Bale portrayal. Really great Substack, recommend that you read it.)

There’s also been a number of financing accounting changes going on. So we’ve talked about the lengthening lives of the AI hardware. You’re also seeing off balance sheet deals being done to help finance data centre development. A number of the hyperscalers like Meta, Google, Amazon and Microsoft have been very cash generative businesses. This has been because software and online advertising are high margin businesses that generate a lot of cash.

Meta and Microsoft have teamed up with private equity companies to co-finance their data centre build out and their acquisition of processors. These loans those are in special financial vehicles that keeps them off Microsoft and Meta’s balance sheet. Short sellers are alarmed by this as it is similar to what we saw that in the telecoms business from the likes of Enron and MCI WorldCom during the dot com bubble.

There are also accusations of circular financing as well. So the chart on the right hand side came from Bloomberg in September of last year. This started to get people worried about the idea of an AI bubble because a lot of it is financed by loans to and from the major technology vendors to the AI players.

Short sellers allege that the values and the profits are being artificially over stated by the hardware depreciation costs and this circular financing. They wonder where are the real transactions? If you look at the circular financing there isn’t meaningful revenue at the moment.

Looking at recent market valuations when I wrote this paper at the end of the year the magnificent 10 (a lot of the hyperscalers, including Meta, the Amazon, Alphabet and Nvidia), had a price to earnings (P/E) ratio of 35x.

So that would mean that it would take 35 years of earnings to actually pay off the share. The S&P the 500 dot-com peak had a P/E ratio of 33 times earnings.

Those values then assume that LLMs would drive one to four trillion in revenue growth or cost savings for dot LLM companies in the next two years, which is a huge amount of money.

$1 trillion revenue target

So how are businesses going to get there? So I started to do a thought experiment:

Advertising will only contribute a relatively small amount. It’ll be big numbers for the rest of us here, but if we think about that target that needs to be hit, it’ll only contribute a small amount of the revenue needed.

Advertising is an industry. It’s about 1% of GDP globally. Also while AI can increase efficiency of advertising, which might be a reason to go there, it may even decrease effectiveness of advertising further.

If you look particularly for large brands, they’re not getting the returns out of digital advertising already that they should be. If you look for growth and increased earnings over the past 15 years or so.

So what about business efficiencies? Yes, it can automate tasks, might be able to reduce jobs. The way it’s optimally pitched is what Microsoft Research described as a wingman approach.

Then the third option which is a lower probability because it rules on a certain amount of serendipity and AI companies have a lot less control.

What does $1 trillion in job cuts look like?

Which raise the question what does a notional $1 trillion, in savings due to job cuts mean?

As a thought experiment it scared the living getting lights out of me. It equates to about 10.5 million jobs in the US. I used two economic models.
- The Phillip curve, which models inflation.
- Okun’s law, which looks at the impact of job losses on GDP.
A trillion dollars in job cuts, wipes $four trillion GDP and 3% deflation to start with. There would likely be additional secondary effects that I didn’t even attempt to calculate

It creates an efficiency paradox, that would destroy the dot LLM ecosystem financially. They rely on being able to get money to invest and that would drop through the floor. You would have less businesses and fund managers investing and less retail investors.

Rather than being able to gradually increase prices over time with a moat, AI companies would be having to continually decrease in prices due to deflation.

The efficiency paradox means there’s a sweet spot between the degree of productivity benefits that they actually provide within a market without destroying AI as a business.

This all assumes that we’re actually operating within the closed system of the American AI market. But it’s worse because it isn’t closed.

The China factor

The US doesn’t have global AI dominance. Some experts think that China may be ahead. I don’t necessarily think that that’s the right framing to use because I think that China’s running a slightly different race. It’s taking a very different approach to the US about these things.

Competition is not only economic, it’s geostrategic and that actually might change and impact the economics of what we talk about.

The Chinese models are about 10 times more power and processor efficient than their American counterparts. They’re already being used with million+ downloads. They obviously do a good enough job that some Silicon Valley companies trust them.

Seven Scenarios

I thought about scenarios, about how the dot LLM era is going to happen, and I represented everything on a continuum of economic transformation to total collapse. The more I thought about it, I saw that we’re going to have overlapping scenarios rather than a single outcome.

On the left hand side was what the AI product was trying to do. New value creation or drive efficiency, along the top what the net impact was likely to be in terms of either negative or zero value creation or a positive to transformation value creation effect.

A probability based approach

The moral hazard happens because AI no longer just economic in nature, but also becomes geopolitical and a national security issue. I rated it at 95% because China is already there in terms of treating vast amounts of its economy from food to technology as a national security issue. AI is no exception. I read a paper by a Canadian think tank equated every US AI company data centre as equivalent to having a US military base on your territory.

The AI players are too big to fail. There’s a national security imperative, and a government’s backstop for them. Taxpayers will have to foot the bill. The AI companies don’t necessarily have to innovate as hard. They can take financial risks, similar to banks pre-2008.

The wingman economy, we’re already seeing this in the way Google, Microsoft and Adobe position their AI offerings.

The idea is that you actually get avoid catastrophic job losses by striking a balance between growth and efficiency to land in just the right place.

The Red Hat model. The idea of that pure play AI businesses struggle to find probability. You get LLM model proliferation, like what I talked about with open source models. The open source models, like Qwen, already have people using it around the world. Then value starts to shift to enterprise support or integration. Like Airbnb who are integrating these models already into their services.

Telecoms bust. You only have to look at things like private equity Blue Owl pulling out of a funding round for an Oracle data centre. It could be basically how they feel about Oracle in particular’s AI offering, which a lot of money has been going into, but not a lot of results have been coming out of, or it could also be sentiment around the dot LLM eco-system in general.

The last three options are much lower probability events.

The new economy model. The idea that AI will make transactions frictionless, with agentic automation , a lot of things will happen. There’s an uncertainty around the economics of this at the moment and there’s numerous concerns like the AI might actually drift away from the original human intent over time. There are also bottlenecks with legal and regulatory issues.

The breakthrough is a black swan event by its very nature. So this would be like a major scientific breakthrough, but then it would likely take 10 years to commercialise. Think about new drugs like Wegovy or Ozempic. They were an innovation that launched during the COVID period. The actual discovery was done back in 1979.

It took decades to get them to be commercial as a weight management product.

With other technologies, that period might be down a bit. So a new oil field might be only a 10 year project from discovery to commercialisation. Either way, it won’t pay off in a two year period.

Where we’re at?

I do believe that the dot LLM era is a financial bubble and a technological shift. The shift will continue to happen and evolve. It will continue to influence culture and business.

The financial bubble may destroy economies. It will keep driving national rivalries.

There is likely to be, and at least in the major players like Google and Amazon, a wariness of self-defeating economics where efficiency seeking destroys consumer base. Even if there’s not worries within AI companies, governments will hit them pretty hard because if you actually see a four trillion drop in GDP in the US and a 10 million strong decline in employment rates, even the current Trump administration would have to step in and regulate.

they’ would regulate is they’d probably overcompensate on economic impact.

So a lot of the major companies, possibly with the exception of Elon Musk, will be thinking about these factors to a certain extent. I think we’re in phase one to the boom and go to the next stage at any time. We’ve got the seeds of a lot scenarios including moral hazards.

It’s the geopolitical things that are really complicating things at the moment.

Eventually we’ll get to a new normal. How long it will take depends on the amount of government intervention that actually happens from an economic point of view. It will also depend on geopolitical factors.

You get a Taiwan invasion, that will impact manufacture of GPUs and TPUs because they’re all made on the island of by TSMC.

Large hyperscalers like Alphabet , Amazon and Microsoft are the most likely to survive the bust as they have multiple revenue streams and can integrate their AI capabilities into these products.

A special thank you to Matthew Knight of Outside Perspective for organising and facilitating the session.
February 4, 2026
Your Life is Manufactured
Your Life is Manufactured is written by Tim Minshall. Minshall is the professor of innovation at the University of Cambridge. He runs the Engineering department’s manufacturing research centre, so has a mastery of his domain. This is immediately obvious from his book, which he manages to write as an exceptionally accessible guide to what manufacturing is, how it is done and hints at why it’s important.

Before getting into the book to understand why it was so popular, I had a number of questions about the book:

What was Your Life is Manufactured purpose as a book?

Your Life is Manufactured looked to demystify how stuff is made. The book whilst accessible is aimed at adults and older children. Minshall keeps things very simple, only once touching on subject matter knowledge name-checking Japanese academic Noriaki Kano‘s work with a very simplified explanation of some of the principles of the Kano model of customer satisfaction.

His explanation as to why manufacturing is important is basically because everything around us is made. He avoids the economic reasons including:
- Increased economic productivity
- Increased growth
- Widespread employment for skilled workers
- The national security adjacent area of resilience
All of which are very important, pertinent points for the UK. Minshall’s choices about what he left out of Your Life is Manufactured is as interesting as what he left in. Whilst the book deplatforms the romantic notions of many environmentalists, Minshall assiduously avoids political territories.

Why is it needed?

When I was a child, I remember other children in my primary school didn’t know that milk came from a cow. They had no idea what happened before the jug of milk appeared in the fridge of their local supermarket. Urban living had divorced many people from nature.

I spent a good deal of my time on a small holding in the west of Ireland as a child, so got to see a cow being milked and the creamery tanker taking away from the milk from the churn to be processed. For those who hadn’t seen this process, city farms started to spring up as educational aids giving a basic if romantic view of farming life.

But we all had an intuitive view of what manufacturing was. While it seems arcane now Unilever’s local factory used to blow a steam whistle signalling the changing of a shift across its large industrial site. It marked the time when I set out around the corner to infant school.

Early on Sunday morning, there was a sharp blast which signalled the weekly cleaning out of the boilers, steam and smoke bellowed into the sky followed by the distinctive smell of the boilers contents.

There were similar sirens at the local shipyards and at other factories. Ships carrying cargo would regularly sound their fog horns. Lorries trundled in and out of factory gates and along nearby roads.

Large factories like the Shell Stanlow oil refinery, the Bowater paper mill and the Vauxhall car plant held open days where workers would take friends and family around the plant showing them what it did and inspiring young minds. Years later, as a student, one of my jobs was running the visitors centre for a terminal that processed natural gas.

There was innate curiosity about how things were made. I still have my collection of ‘How It Works’ encyclopedia that I had as a child. My parents sold the original early 1970s part works series in a cardboard box that my Dad had collected and sparked my interest in the version I now have, which we upgrade to when I was still in primary school.

During my career, I have seen several manufacturing processes including a giant printing works in Shenzhen, the infamous Foxconn factory complex and Global Foundries Dresden semiconductor fab.

Now with globalisation and delivery to the door many children of all ages are completely divorced from the means of production. Your Life is Manufactured is a small step in what would need to be a larger process to ground the general public in manufacturing and why it’s important, yet fragile.

Overall thoughts

That Your Life is Manufactured is considered a business book of note, says a lot about how deeply the British people are separated from how things are made – and that’s a frightening thought. Minshall’s book is a good first step in opening up British minds about manufacturing and its requirement of a place in our society. It’s immensely readable and woke me up to the collective ignorance surrounding me.

You can find more book reviews here.
September 25, 2025
Ideas for being a good strategist
A big shout out first of all to Rob Estreitinho who inspired this post full of ideas for strategists. I have built on his work. Some of the suggestions are what works for me or Rob and may not work for you – but give them a try.

Ideas
1. Read widely – thank goodness my Irish emigrant parents instilled in me the Irish love of reading. My Dad was an apprentice at 14, but has never given up a love of books if he had the chance. My Mum reads less with the lethargy of age creeping up on her, but they both seeded the idea of reading widely to me.
2. Get an RSS reader – find middle-aged people who used the net back in the early 2000s to early 2010s seriously and mention Google Reader to them and watch them go misty-eyed longing for forgotten online halcyon days. It didn’t make you depressed or hate yourself. While Google Reader is long gone, the underlying technology that enabled it is very much alive. It’s called RSS and Atom – same, same but different. All the RSS readers work along similar ideas; over time you find good sites, you follow them and get more good content from as they update. My tool of choice is Newsblur. But if you want to continue to rely TikTok, Twitter and Truth Social – you do you.
3. Your bookmarks are gold – on the bookmark bar of my browser I have a range of tools. I use Pinboard to keep every bookmark I have used in my work life for a long time. I go back through them to find quality content to start from for insights when kicking off a project. Anything you get elsewhere will be filtered through context and algorithm rather than quality. I also have a hard drive of old reports that I can go through and over-stuffed bookshelves.
4. Read weirdly – As a child I read everything in my Uncle’s farm house from the Connacht Tribune , Irish Farmers Journal to Old Moore’s Almanac and Ireland’s Own. Later on, one of the great privileges for me of going to college and then going to university, was the opportunity pick up odd books that would never have otherwise read. I would also browse County Books – a discount book store which allowed me to pick up unrelated academic books like Paul Stoneman’s Handbook of the Economics of Innovation and Technological Change – which is still invaluable today. Using an RSS reader and following other’s recommendations provides a similar opportunity. Finally, subscribe to Matt Muir’s Web Curios to get the edges of the web.
5. Make your arguments simple. – Going through this filtration process helps make ideas stronger as well as more accessible. My Myer-Briggs type is apparently INTJ ‘the architect’ – I have a clear vision of the thing. But going simpler allows you take stakeholders with you. Ideas only gain power as they pass from person-to-person.
6. Now make them simpler than that. When I thought about this, it reminded me of Matt Holt, who talked about good strategy being pain. This squeezing process is more than an expression, but a process that forms the quality of an idea.
7. Use simple words your mum would understand, or use simple words your mum’s mum would understand – as suggestions go were curiously Ogilvian in nature. However I when thought it, they were less helpful pieces of advice than they appear. Older people tend to be more articulate and may have more arcane terms. One thing generative AI does allow us to do is test how an idea would be expressed based on a notional character. So think about simplicity, through the lens of possible audiences.
8. Always start with a written document – I have found the notes.app on my Mac liberating. I can take my notes with me on my iPhone. I dump in links, language, ideas in to be played with and moved around. Insights and ideation become hybridised as a process.
9. Know a good meme account for the category you work with. If you don’t know one start with Reddit threads and you start to get a good feel for the themes and memes coming through.
10. Know a really good podcast your audience would listen to. Searching for podcast recommendations and listening to them can help you get into the right headspace for a given project.
11. Assume every problem has a fascinating side to it. If you work in strategy there are a few parts of the job to inspire your love of it. The ability to read around a subject, discover the problem at the centre of the challenge you are working, wrestle with that kernel of truth to give creatives something to work with. The process of wrestling the problem usually unearths the fascination at the centre.
12. Start your presentations with a twist. If you don’t have audience interested at the beginning, you won’t hold it until the end of your presentation. In terms of my personal writing, I use the background behind the number marking the edition of the newsletter to engage the curiosity of the reader.
13. End your presentations with a lesson. I like this as it reminds me of the old presentation training maxim: tell’em what you are going to tell’em, tell’em it, tell’em what you just told them. Ideas like advertising get better through repetition. The end summary can be just verbal, it doesn’t need to be in slideware.
14. If you’re feeling spicy, end your presentations with a cautionary note. Being provocative and interesting is good, BUT know your audience before attempting this.
15. Don’t obsess with strategy frameworks. Strategy frameworks have their place. They are great for establishing a common language – the classic example being the marketing funnel. They’re also good at dealing with the mental blankness that comes from an empty page or screen. But they can also be modified, built-upon or thrown away depending on what solving the problem needs.
16. Don’t bore your client with strategy frameworks. I’d argue, don’t bore your client. Their problems should be interesting, otherwise why would they get someone like you or me to try and solve them? If we are boring the client, there’s one of three things happening: you’re not solving their problem, you’ve gone off-mission away from the problem and the likely solution or the solution doesn’t solve the problem.
17. Remember the audience will never read your strategy. The only exception to this is the occasional Venn diagram-based advert creative.
18. Don’t interrupt people, especially when they’re demonstrating passion. Do remember to record it, otherwise you might be lost in the flow and lose the insights.
19. Notice what people say and play it back to them. This is a classic technique that is taught to salespeople and was in Dale Carnegie’s How To Win Friends and Influence People. It provides a number of benefits:
  - Ensures that you’ve understood what they wanted to say and you’re clear about it. It’s easier to get an explanation now, rather than later on.
  - Carnegie liked it because he recognised that people liked to be understood.
  - Allows you to build a common vocabulary with the other person.
20. Start sentences with “I wonder if”. Use this sparingly, but at the right time it is a powerful way of testing ideas and directions.
21. Observe people, but do so discreetly and don’t weird them out:
  - In coffee shops
  - At a greasy spoon cafe or the Motorway services station
  - On public transport
  - At trade shows. What stuff gets dumped from the collection of brochures they have. What way to people navigate a client’s stand. What seems to be attracting the most attention and the least? .
22. Say “I don’t know yet” when you don’t know… yet.
23. Don’t worry about memorising everything you read. If you can retain it all brilliant, but it’s not an exam, you can go back and check references if you are unsure. Instead it’s much more important to understand the topology of the problem and the direction that a solution would need to take.
24. Do use index cards – one of my favourite things on Amazon is sets of index cards and steel rings to hold them together in one corner. I use this to build my written memory on a clients business and products. I find the act of writing it down helps to build memory structures. I was inspired in this by Umberto Eco’s How To Write A Thesis.
25. Study ways to find out about things. I am a bit of a pack rat when it comes to tools, reports etc – as are other people I know. One of the areas that strategists have been ignoring up until now, but could learn a lot on in the hobbyist world of OSINT and your local library.
26. Use Claude AI to explain your own argument back to you – was a recommendation of Rob, I am using Gemini at the moment and it performs a similar role. However I do see the benefit of getting a couple of sets of viewpoints to pressure test your thinking. Previously, I would have done this with colleagues like Rob Fuller or Zoe Healey – generative AI kind of fills the gap and has some serendipity in its inherent weirdness. Whatever way you do it, stress-test your ideas.
27. Believe people when they say you did great, if it’s written down keep a record of it for your appraisal. But don’t let your personal sense of worth be defined by your career – you are more than your job.
28. Write with a thicker pen – it forces your handwriting to be clearer, letter shapes better defined. But use a thinner pen when thinking about structure and interconnections. I am a great believer when listening to talks or thinking about presenting a subject to mind map it out on engineering squared paper first. From the flow of interconnections, a natural order emerges.
29. Write with a bigger typeface – I would focus on legibility rather than size. And no comic sans – not even in irony.
30. Always change to 1.5 line spacing.
31. Don’t cheat on your one-pagers by making the typeface smaller. With generative AI now, why would you even do this?
32. Have strategy pals – but not to the exclusion of types of people. Try and have a diverse social network. It’s very easy to live in an advertising and media industry eco-system and out of touch with the general public.
33. Cmd+S every other minute. It’s a good idea to build this up as muscle memory, even if unnecessary in services like Google Docs and Office 365. Latency rather than a software crash are the most likely killer of documents nowadays.
34. Take care to manage your browser tabs, if you use a social bookmarking service, you can always go back to them later.
35. Buy a random magazine. Your clients might be all about social platforms but magazines, have been, and still are great windows into culture. I have a stack of Japanese style magazines for inspiration and try and buy a local magazine to leaf through when travelling. They are a fountain of future ideas.
36. Do a walking meeting. I miss doing walking meetings, at the time I had a colleague that lived within walking distance which made the process ideal. I also realise that this is often hard to do, when your project manager has filled you up on back-to-back calls. One thing I remember doing at Unilever was dialling into conference calls on my phone and listening in while walking around my office floor at 100 Victoria Embankment. Admittedly it’s not practical to do when presentations are being shared, or when your contribution is required to be engaged as a note taker.
37. Breathe while you talk. You have nervous energy, you want to get it all out. Breathing slows your thinking down so those finer elements won’t slip out of your grasp. I know people who swear by Toastmasters as a help to master this.
38. Daydream for no good reason. We live by the tyranny of the calendar on our phones or laptops and have lost sight of the time needed to think and let ideas worm their way out of our subconscious to the conscious mind at the front of our thoughts.
39. Have the basics of understanding wetware. The currency of being a strategist is people. We are the voice of the customer (people), clients (who also happen to be people) rely on us to solve problems, creatives rely on our translation of noise into something they, as people, can relate to. We don’t do all that alone, so thank people who’ve helped you and be generous with compliments. It won’t kill you, generally others won’t remember what you’ve done as much as how you made them feel.
40. Be specific. This manifests itself in lots of ways from reflecting the client’s problem back to being single-minded in a brief given to creatives. Specificity is its own form of clarity.
41. Listen more than you speak. Good advice for life, not just strategy.
42. Write a list. Lists are useful brainstorming device, but they are also really useful for self-organisation. Post-it notes are your friends.
43. Write a stream of consciousness and be prepared to cut and paste it around to organise your thoughts rather like ‘fridge magnet poetry’.
44. Give yourself 10 minutes to write the clearest answer you can think of. Simplify it in a few seconds with generative AI. Then feel ok that you’ll probably need time to get to a simpler one and remain better when the obvious simplification comes from colleagues.
45. If it feels obvious, stick with it. This reminded me of Dieter Rams principles of design which extend well beyond design and into problem solving and life in general:
  - Good design is innovative
  - Good design makes a product useful
  - Good design is aesthetic
  - Good design makes a product understandable
  - Good design is unobtrusive
  - Good design is honest
  - Good design is long-lasting
  - Good design is thorough down to the last detail
  - Good design is as little design as possible
46. Say your argument out loud. This is part of pressure-testing your own thinking. It’s also something that generative AI services can help with as both devil’s advocate and to ‘steel man’ your own ideas.
47. Admit when you are wrong. Being wrong isn’t bad, it’s part of the learning process and will help you get to better ideas. A former colleague of mine used to talk about being interesting as more important than being right – there are traps in that statement but also something powerful in it.
48. Say “sorry” when you have to. Sorry is a powerful disarming tool. It helps you get to both interesting and right faster.
49. Assume the work has been thought through. Just because you don’t get it, it doesn’t mean that others haven’t come up with some interesting ideas. And even if it hasn’t been thought through quite as well as you like, what’s the lesson that can be derived from it all?
50. Ask questions without judgement. There are no dumb questions, just people who are left dumber due to unanswered questions.
51. Find reasons to build on things. I found this a bit weird when I first entered agency life. Previously I had worked in the chemical industry, which was regimented and compartmentalised in the way work was done. College was very much about individual effort to complete assignments and essays. Build on this was something that I found female colleagues used to do really well. I remember being sat in a meeting and watch each person play a reverse ‘pass the parcel’ game with an idea. When it came to say their bit in a ‘brainstorm’ they would acknowledge what had been previously said and provide their own innovation as an additional wrapper. It won pitches and increased group cohesion.
52. Focus on agreeing a direction, not winning arguments. While you were winning the argument, you could have been getting insights to help set that direction in the ideas.
53. Build a robust strategy rather than a perfect strategy. A strategy that isn’t implemented for a client, may as well not exist. A robust strategy can be optimised based on what happens in the market. The perfect strategy may not even get to market.
54. Be useful. If a meeting needs coffee or printing off handouts and you can do them. People may not remember what you’ve done but how you make them feel and putting them at ease when hellsapoppin’.
55. Say you have a clash – leave it at that. Much of what happens inside agencies runs on implicit guilt. Avoid that guilt by saying less, being prepared to not fill silences and don’t explain diary clashes.
56. When you have nothing to do, read. Well learn at the very least, our world and what’s demanded of us is always changing. Do a course read an article, a book chapter or listen to an audio book.
57. If you’re tired of reading, write. I find writing very powerful. The process of writing helps me work things out from opinions to problem solving.
58. If you’re tired of writing, go for a walk. I was working on a brief prior to writing this post and walked from Whitechapel station home. I let my mind wander and I got the central concept of the insight by not thinking about it during that hour’s walk.
59. If you’re tired of walking, take a nap. Burn out is real, it’s got even worse with project management tools that overburden strategy teams.
60. If in doubt, try out the Oblique Strategies. Back in 1975, electronic musician Brian Eno and multimedia artist Peter Schmidt came up with what we’d call in advertising provocations. They are particularly useful in trying to break through a mental block. You have a 100 cards about the size of a playing card in a box. Read it, think about it, have a break and come back to it and ask how it can be applied to your problem. There is also an iPhone version of it, but there is something about the tactility of the cards.
61. Have a healthy snack of choice – our changing workloads chained to messaging apps rather than getting out and interviewing people in focus groups has amplified the need for this advice. I would go further and say avoid the ‘pitch pizza’ – the lowest common denominator selections provided by agencies to fuel the late night efforts of its pitch teams. I have turned to trail mix, zero sugar energy drinks and even Huel at a push instead.
62. Break your own rules. A former colleague that I worked with at Yahoo! used to talk about ‘guidelines, not tramlines’. Breaking your own rules is about understanding why you have the rule and making a creative choice. Usually rules speed up decision-making.
63. Make different mistakes. We learn from mistakes, there is a value in them if you think about things in terms of a scientific methodology. But, there is nothing to be gained from making the same mistakes.
64. Interesting is more important than right, I alluded to this earlier but it deserves its own explanation. Interesting sparks discussions that help get to further insights. This comes from remaining constantly curious and holding a strong point-of-view. As for views, hold on tightly unless there is good evidence to the contrary and then be prepared to let go lightly. This is where I again tell you are more than your job, one of the main ideas it is important to convey in a list like this.
65. Have a copywriter as an ally. Working on my last brief I had got to the the human insight, but I couldn’t land the concept in a sufficiently resonant way. Going back-and-forth with the copywriter got us there.
66. Have other strategists as allies. They have walked similar journeys to you and might see things that you are too close on to notice. One of the greatest aspects of working with great strategists is the collegiate attitude to ideas and generosity of thoughts.
67. Network internally. You would think that work would shine through, but the reality is most people won’t remember what you did. Secondly, that internal networking helps understand the context that your work exists within. Finally, the internal network you have will eventually become scattered across the industry and even client side, opening up potential future opportunities.
68. Develop an aesthetic. I was fortunate to grow up in a house that wasn’t wealthy in terms of money, but was wealthy in terms of ideas. Part of it was down to reading and part of it was down my Dad’s deep sense of quality. I would love to say that we had less but better in terms of consumption, but we didn’t – there are no Vitra or Eames designed furnishings at my parents house. The closest I have to it is the refurbished first generation Herman Miller Aeron chair I am sitting on and vintage Ikea birch bookcase – rather than their more commonplace MDF pieces. Much of my furniture is gifted or upcycled. My sofa, was originally from the 1970s, my Dad reupholstered it and rebuilt the frame based on materials he had left over from doing his own motor caravan conversion of a Volkswagen (Typ 28) LT-35 van. The sense of quality gave me the confidence to explore my own taste in design, art, literature and cinema. Taste and a sense of what’s important is becoming more important in strategy and the creative industries.
August 16, 2025
Business cards

The Financial Times opined on the obsolescence of business cards. This has been a common theme for the past quarter of a century, so whether or not it’s actually news is up for debate.

Business cards have been a surprisingly accurate marker of my career’s evolution. Before college, when I was working in laboratories to save up, business cards were strictly for management. If anyone needed to reach me, they’d receive my name and extension number scribbled on a company compliments slip.

Fast forward to my early agency days, and changing my business cards became the immediate priority after receiving a promotion letter. I vividly recall discussing new cards with our office manager, Angie, to reflect my new title: from Account Executive to Senior Account Executive. While that promotion enabled me to buy my first home, it was the tangible act of updating my business cards that truly solidified that future title for me in my memory.

Building a network was an important part of development in the early part of my career and my manager at the time would ask us each week how many business cards we’d given out as a way of quantifying that development.

Business cards had a symbolism and status that was captured famously in Brett Easton Ellis’ American Psycho and in memorable scene of its its subsequent film adaptation.

Even today in Asian countries, business cards come loaded with cultural symbolism and a distinct etiquette of exchange. The exchange of them is handy as it allows to lay out a model of who is around a meeting table based on the card collection, facilitating easier meeting communications.

Personal organisers

In the mid-1990s, the personal organiser was a staple, its prevalence varying depending on location and budget. These organisers typically featured loose-leaf pages for schedules, an address book, and a system for storing and archiving business cards, even those of people who had moved on. However, by 2001, the media was already concerned about the impending demise of the personal organiser and its potential impact on the business card’s future.

Filofax

Filofax has the reputation for being the most British of brands. It originally started off as an importer of an American product Lefax. Lefax was a Philadelphia-based business which made organisers popular within industry including power plant engineers in the early 20th century.

At that time electricity was considered to be the enabler that the internet is now, and Lefax helped to run power plants effectively and reliably. Filofax eventually acquired Lefax in 1992. During the 1980s, the Filofax became a symbol of professionalism and aspirational upward mobility. I was given one as soon as I started work, I still have it at my parents home. It’s leather cover didn’t even develop a patina, despite the beating it took in various parts of my work life: in night clubs, chemical plants and agency life. Filofax even became part of cinematic culture in the James Belushi film Taking Care of Business also known as Filofax in many markets.

Day-Timer

In the US, there was the Day-Timer system, which came out of the requirements of US lawyers in the early 1950s and became a personal management tool for white collar workers in large corporates like Motorola – who appreciated their whole system approach. Day-Timer was as much a lifestyle, in the same way that David Allen’s Getting Things Done® (GTD®) methodology became in the mid-2000s to 2010s. Customers used to go and visit the personal organiser factory and printing works for fun. Along the way, other products such as At-A-Glance and Day Runner had appeared as substitute products. Day-Timer inspired the Franklin Planner system; a similar mix of personal organiser and personal management philosophy launched in 1984.

By the mid-1990s, Day-Timer had skeuomorphic PC programme that mirrored the real-world version of the Day-Timer. At the time this and competitor applications would allow print-outs that would fit in the real world Day-Timer organiser. Day-Timer’s move to mobile apps didn’t so well and now it exists in a paper-only form catering to people wanting to organise their personal lives and home-workers.

Rolodex

While the Filofax allowed you take to your world with you, the Rolodex allowed you to quickly thumb through contacts and find the appropriate name.

Back when I first started my first agency job, I was given my first Rolodex frame. I spent a small fortune on special Rolodex business card holders. At my peak usage of Rolodex as a repository for my business contacts, I had two frames that I used to rifle through names of clients, suppliers and other industry contacts.

Rolodex became a synonym for your personal network, you even heard of people being hired for ‘their Rolodex’. For instance, here’s a quote from film industry trade magazine Hollywood Reporter: Former British Vogue Chief Eyes September for Launch of New Print Magazine, Platform (May 8, 2025):

…to blend “the timeless depth of print with the dynamism of digital” with coverage of top creative forces, no doubt leaning into Edward Enninful’s enviable Rolodex of A-list stars, designers and creators gathered through years spent in the fashion and media space with tenures at British Vogue and as European editorial director of Vogue.

If I was thinking about moving role, the first thing I would do is take my Rolodex frames home on a Friday evening. The fan of business cards is as delicate as it is useful. It doesn’t do well being lugged around in a bag or rucksack. Each frame would go home in a dedicated supermarket shopping bag.

The Rolodex was anchored to the idea of the desk worker. The knowledge worker had a workstation that they used everyday. Hot-desking as much the computer is the enemy of the Rolodex. My Rolodex usage stopped when I moved to Hong Kong. My frames are now in boxes somewhere in my parents garage. Doomed not by their usefulness, but their lack of portability.

Personal information management

The roots of personal information management software goes back ideas in information theory, cognitive psychology and computing that gained currency after the second world war.

As the idea of personal computers gained currency in the 1970s and early 1980s, personal information software appeared to manage appointments and scheduling, to-do lists, phone numbers, and addresses. The details of business cards would be held electronically.

At this time laptops were a niche computing device. Like the Rolodex, the software stayed at the office or in the den at home. NoteCards used software to provide a hybridisation of hypertext linkages with the personal information models of the real world. NoteCards was developed and launched in 1987, prefiguring applications like DevonTHINK, Evernote and Notion by decades.

As well as providing new links to data, computers also allowed one’s contacts to become portable. It started off with luggable and portable laptop computers.

Putting this power into devices that can fit in the hand and a coat pocket supercharged this whole process.

Personal digital assistants

Personal digital assistants (PDA) filled a moment in time. Mobile computer data connections were very slow and very niche on GSM networks. Mobile carrier pricing meant that it only worked for certain niche uses, such as sports photographers sending their images though to their agency for distribution to picture desks at newspapers and magazines. While the transfer rate was painfully slow, it was still faster than burning the images on to CD and using a motorcycle courier to their picture agency.

The PDA offered the knowledge worker their address book, calendar, email and other apps in their pocket. It was kept up to date by a cradle connected to their computer. When the PDA went into the cradle information went both ways, contacts and calendars updated, emails sent, content to be read on the PDA pushed from the computer. IBM and others created basic productivity apps for the Palm PDA.

IrDA

By 1994, several proprietary infra red data transmission formats existed, none of which spoke to each other. This was pre-standardisation on USB cables. IrDA was a standard created by an industry group, looking to combat all the proprietary systems. The following year, Microsoft announced support in Windows, allowing laptops to talk with other devices and the creation of a simple personal area network.

This opened the possibility of having mice and other input devices unconstrained by connecting cables. It also allowed PDAs to beam data to each other via ‘line of sight’ connections. The reality of this was frustrating. You would often have to devices an inch from each other and hold them there for an eternity for the data to crawl across. It wasn’t until 1999 that the first devices with Bluetooth or wi-fi appeared and a couple more years for them to become ubiquitous. Unsolicited messages over Bluetooth aka bluejacking started to appear in the early 2000s.

But IrDA provided a mode of communication between devices.

versit Consortium

versit Consortium sorted another part of the puzzle. In the early 1990s the blending of computer systems with telephony networks as gaining pace. A number of companies including Apple, IBM and Siemens came together to help put together common standards to help computer systems and telephony. In 1995, they had come up with the versitcard format for address book contacts, better known now as ‘vCards’. These were digital business cards that could be exchanged by different personal information management software on phones, computers and PDAs. For a while in the late 1990s and early 2000s I would attach my vCard on emails to new contacts. I still do so, but much less often.

The following year the same thing happened with calendar events as well.

Over time, the digital business card came to dominate, via device-to-device exchanges until the rise of LinkedIn – the professional social network.

Faster data networks allowed the digital business card sharing to become more fluid.

A future renaissance for the business card?

While business cards are currently seen outdated in the west, could they enjoy a renaissance? There are key changes in behaviour that indicate trends which would support a revitalisation of business cards.

Digital detox

While information overload has been a turn that has been with us since personal computers, digital detox is a new phenomenon that first started to gain currency in 2008 according to Google Books data. Digital detox as a concept has continued to climb. It has manifested itself with people talking a break from their screens including smartphones. Digital detox has continued to gain common currency.

Creating a need for tangible contact details in the form of a business card in certain contexts.

The pivot of personal organisers

Day-Timer and Filofax didn’t disappear completely. While Day-Timer is no longer a professional ‘cult’, it now helps remote workers organise their own work day at home. They also tap into the needs of people organising their own wedding. The paper plans also gives them a memento of this event in a largely digital world.

If personal organisers continue to exist then real-world business cards would also make sense in those contexts.

Bullet-journaling

Ryder Carroll is known as the ‘father’ of the bullet journal which was a home-made organisation method which was similar to the kind of task lists I was taught to pull together in my first agency role. There were aspects of it that would be familiar to Day-Timer advocates as well.

When the world was going digital Carroll used paper to help organise himself. Carroll tapped into the fact that even computer programmers use paper including notebooks and post-it notes to manage projects and personal tasks within those projects. Carroll took his ‘system’ public via Kickstarter project in 2013.

Bullet journaling provided its users with simplicity, clarity and an increased sense of control in their life. What is of interest for this post, is the move from the virtual back into paper organisation.

Changing nature of work

Hybrid working, remote working and increasing freelance communities in industry such as advertising has affected one’s professional identity. This has huge implications for personal standing and even mental health. Human connection becomes more important via virtual groups and real-world meet-ups. Controlling one’s own identity via a business card at these meet-ups starts to make an increasing amount of sense.

The poisoning of the LinkedIn well

On the face of it LinkedIn has been a wonderful idea. Have a profile that’s part CV / portfolio which allows your social graph of professional connections to move with you through your career. Services were bolted on like advertising, job applications and corporate pages to attract commercial interest and drive revenue.

Over time, LinkedIn has increased the amount of its creator functions, driving thought leadership content that is a prime example of enshitification. 2025 saw ‘thought leaders’ publishing generative AI created posts as entirely their own work.

LinkedIn has become devalued as a digital alternative to the humble business card.

More related posts can be found here.

July 11, 2025
Liberation day + more things

Liberation day

Liberation Day was a glorified press conference where the Trump administration revealed their tariff scale on every country around the world. Weirdly enough, Russia wasn’t tariffed. Here’s some of the interesting analysis I saw prior to, and after the event.

The Trump administration leant into an aesthetic influenced by patriotic memes, the steeliness of The Apprentice and generative AI – a look I call Midjourney Modern. Liberation Day was no exception.

The Economist did a hot take that calls the whole thing a ‘fantasy’.

America’s Cultural Revolution – by Stephen Roach – Conflict – Stephen Roach was an Asian focused chief economist at Morgan Stanley. The American Cultural Revolution narrative is something I have heard from a few contacts in China and Roach echoes that perspective in this article.

China says weaponising agriculture in US trade war should be off-limits | South China Morning Post – agricultural price shocks in the past have led to civil disruption in China

Liberation Day and The New World Order | Fabricated Knowledge

Opinion | I Just Saw the Future. It Was Not in America. – The New York Times – President Trump is focused on what teams American transgender athletes can race on, and China is focused on transforming its factories with A.I. so it can outrace all our factories. Trump’s “Liberation Day” strategy is to double down on tariffs while gutting our national scientific institutions and work force that spur U.S. innovation. China’s liberation strategy is to open more research campuses and double down on A.I.-driven innovation to be permanently liberated from Trump’s tariffs.

Beijing’s message to America: We’re not afraid of you. You aren’t who you think you are — and we aren’t who you think we are. – Thomas Friedman – Overall, I would agree with the sentiment, BUT, you have to remember what he’s been shown is the best view of what China can do and reality is much more complex. I still think that there is a lot of the future being made in places like France, Finland, Latvia, Japan, Singapore, South Korea and Taiwan – as well as China. What China does best is quantity that has a scale all of its own, something America has historically excelled at.

Consumer behaviour

Bachelors Without Bachelor’s: Gender Gaps in Education and Declining Marriage Rates by Clara Chambers, Benjamin Goldman, Joseph Winkelmann :: SSRN

Culture

Montreal DJs move clubbing from midnight to morning, adding coffee and croissants | Trendwatching – early morning clubbing, reminds of Marky J‘s mornings at the Baa Bar in Liverpool.

Health

Is Gen Z more mentally ill, or do they just talk about it more? | Doomscrollers

Europe Rapidly Falling Behind China in Pharma, Astra Chief Warns – Bloomberg

Ideas

I’m Tired of Pretending Tech is Making the World Better | Joan Westenberg

Innovation

Samsung Develops Groundbreaking Achromatic Metalens With POSTECH – Samsung Global Newsroom

Korea

South Korean movie theater launches monthly knit-while-you-watch screenings | Trend-Watching

Luxury

Counterfeit luxury goods: London raids miss the target | Dark Luxury

Vogue Business Index top 10: Preppy is back and so is Ralph Lauren | Vogue Business

Polène: The global success of the French handbag made with love | Le Monde

Marketing

X-tortion: How Advertisers Are Losing Control Of Media Choice | Forrester – I am surprised how ‘on the nose’ Forrester is in this post.

Technicolor, Parent Company of The Mill, MPC, and Mikros, Facing Potential Closure | LBBOnline – this hit the creative industries like a lightning bolt.

Influencer Marketing: The quiet reset in the influencer economy, ET BrandEquity – the total number of influencers has shot up from 9,62,000 in 2020 to 4.06 million influencers in 2024, reflecting a staggering 322% growth.

Materials

DIY Birkin? China’s Gen Z 3D print dupes, share on RedNote | Jing Daily – Armed with affordable 3D printers and free design templates, young consumers are crafting their own versions of iconic luxury accessories. – Homage flowerpots or penholders rather than ‘dupes’ but 3D printing feels mainstream

Online

Revealed: Google facilitated Russia and China’s censorship requests | Censorship | The Guardian – After requests from the governments of Russia and China, Google has removed content such as YouTube videos of anti-state protesters or content that criticises and alleges corruption among their politicians. Google’s own data reveals that, globally, there are 5.6m items of content it has “named for removal” after government requests. Worldwide requests to Google for content removals have more than doubled since 2020, according to cybersecurity company Surfshark.

The reason you feel alienated and alone | Madeline Holden – your Dunbar number is filled with para-social relationship rather than social relationships.

China’s fragile online spaces for debate | Merics

AI Discoverability: Amazon’s Mistakes NN Group

Retailing

Lidl TikTok Shop launch sells out in under 20 minutes | Retail Gazette – I am curious about Lidl fulfilment approach

Security

Military delegates lose sway at China’s signature political gathering | FT

Putin is Unlikely to Demobilize in the Event of a Ceasefire Because He is Afraid of His Veterans | Institute for the Study of War – which poses economic challenges in Russia and a greater incentive to attack outside Ukraine once the conflict winds down

Exclusive: Secretive Chinese network tries to lure fired federal workers, research shows | Reuters

FBI raids home of prominent computer scientist who has gone incommunicado – Ars Technica

Technology

Google’s Sergey Brin Asks Workers to Spend More Time In the Office – The New York Times – 60 hour weeks are productivity sweet spot according to Sergey Brin. Silicon Valley looks more-and-more like Huangzhou.

Alibaba exec warns of overheating AI infrastructure market • The Register

Telecoms

SoftBank and Ericsson agree to collaborate on next-gen telco tech

Web-of-no-web

Meta announces experimental Aria Gen 2 research smart glasses | CNBC

WeRide to open driverless taxi service in Zurich | EE News – Chinese operator is set to launch a fully unmanned taxi service in Zurich in the next few months. This follows the launch of its latest generation Robotaxi, the GXR, for fully unmanned paid autonomous ride-hailing services in Beijing. The GXR, with a L4-level redundant drive-by-wire chassis architecture, is WeRide’s second Robotaxi model to achieve fully driverless commercial operations in the city following pilot trials.

Wireless

London’s poor 5G blamed on spectrum, investment, Huawei ban • The Register – the comments nail it

April 6, 2025

More posts