Buying Your Time

Occasional analysis 👇

[Buying Your Time @BuyingYourTime]

https://t.co/eJVxaxgdZf

[Buying Your Time @BuyingYourTime]

@shayy_lior Headbangers

[Buying Your Time @BuyingYourTime]

@bryan_johnson Somebody has to take it "too far". How would you ever know. That's the fun irrespective of the outcome.

You try, some shit doesn't go the way you expect and some shit does. Fuck it. Keep going

[Buying Your Time @BuyingYourTime]

@amelia_tweetz Time is so limited when on holiday. I don't want to be tidying up and doing chores.

Maximise time spent doing fun things and let someone else take care of the cleaning, cooking, etc

[Buying Your Time @BuyingYourTime]

@capitalflows @Crumb_hunter I ponder this more than I should but then again there are worse things to ponder over

[Buying Your Time @BuyingYourTime]

@capitalflows @dailydirtnap 😂😂

[Hamilton @capitalflows]

https://t.co/fizyhyliJr

[Buying Your Time @BuyingYourTime]

@ACInvestorBlog On the list. Thank you 🙌🏽

[Buying Your Time @BuyingYourTime]

There are two narratives at play: One is the fuel i.e. transition to Electric from fossil fuels and affordability/value.

On the value front, we're witnessing what the Japanese car industry did in the US during the 80's - better value for money.

I see a lot of the following cars in Scotland, where I'm from, alongside the more well known Tesla & BYD

https://t.co/AliEt9WSz8

[Buying Your Time @BuyingYourTime]

@dannycheng2022 $NVDA 2016

[Buying Your Time @BuyingYourTime]

Monetisation may still be early, but management is leaning hard into advertising with multiple levers to expand ARPU. Plus tools like Reddit Pro bringing brands directly onto the platform (Wendy’s, Taco Bell, NFL, WSJ already participating).

The real strategic asset is Reddit’s 20-year archive of discussion data, longitudinal consumer intent and product sentiment that’s incredibly valuable for advertisers.

$RDDT has more going on than people realise.

[Buying Your Time @BuyingYourTime]

Reddit’s user growth story is real.

But there’s an important nuance in the DAUq data.

Most of the growth is coming from international users → where ARPU is materially lower.

That dynamic creates an interesting tension between scale and monetisation.

Full analysis in the report → https://t.co/FkDSImxoNs

[Buying Your Time @BuyingYourTime]

Reddit might be the most misunderstood internet company right now.

People see memes and forums.

Investors should see:
• Structured discussion data
• High-intent product conversations
• A capital-light platform
• Early-stage monetisation

I broke down the business model.

Full write-up on Substack → https://t.co/uFRklTISaQ

[Buying Your Time @BuyingYourTime]

A capital-light internet platform that grew revenue 70% YoY. Yet most investors still think it’s just a message board.

It’s not.

It’s sitting on 20 years of structured human conversation - one of the most valuable datasets in the AI era.

Full analysis on Substack: https://t.co/RXQ07DZokv

[Buying Your Time @BuyingYourTime]

@BRICSinfo @grok List all the other banks on order of size if this is the second biggest

[Buying Your Time @BuyingYourTime]

@Heartflow Can you shed more light on your ‘Plaque Tracker’ solution and how it aids the CCTA diagnostic pathway?

[Buying Your Time @BuyingYourTime]

I’ve never been an investor in NOW; however, it’s always been of interest. I hold a small position in PATH and, putting aside differences of approach, I’ll just say you’ve outlined exactly what my thoughts are around the agentification of enterprises.

The contextual visualisation of business processes and then identifying how and what can be agentified in a secure and compliant way is key. It seems that NOW understands that and, rather than solely developing in-house (despite having significant internal build capability), the smart choice in certain instances is to acquire in order to gain that knowledge and expertise more rapidly and defensibly.

An example I often tout is that the exec or higher management within a company has probably used ChatGPT (or Claude/Gemini) and realised that “AI,” in some capacity, can make their organisation more efficient and productive. However, they won’t fundamentally understand the intricate mechanics that weave together orchestration (systems integration), compliance, security, and outcome.

So, through a potentially arduous and/or unsuccessful process of agentic transformation, they inevitably realise they require the structured, secure, and enterprise-grade framework that NOW or PATH provide, not experimentation, but infrastructure.

[Buying Your Time @BuyingYourTime]

The diagnostic pathway must be changed and part of that requires educating the involved physicians (cardiologists/radiologists/interventionists).

Favourable reimbursement can be achieved through evidence and results based outcomes just as it was for the Class designation for 'Plaque Analysis'.

[Buying Your Time @BuyingYourTime]

If you missed it, here's the new Mauboussin paper on the AI build-out and here's a summary below if you don't want to read the whole thing 👇

Basically, what it’s saying is that for companies of comparable initial size, no public US company in the last 75 years has achieved the kind of 5-year revenue growth that OpenAI (and Oracle Cloud) are forecasting from the AI rollout. Whether the starting base is $2–5B of revenue or $8–12B+, hitting those targets would be a statistical outlier, basically “history says: almost never.”

OpenAI’s plan implies extreme compounding (their 2024 $3.7B to 2029 $145B forecast implies a 108% CAGR). That has never been observed in the dataset, which doesn’t mean it can’t happen, but it would be a first, not a “normal” outcome.

Of course, adoption is the big counterweight. The paper highlights that ChatGPT reached 100M users in 2 months, compared with 9 months for TikTok, 28 months for Instagram, and 4.5 years for Facebook, and much longer for older technologies such as the telephone and mobile phones. So, diffusion is undeniably fast, even if users don’t translate 1:1 into paid revenue.

Then it zooms out to the big-project history: fewer than half finish on budget; fewer than 9% finish on budget and on time; and only 0.5% finish on budget, on time, and deliver the promised benefits. That matters because AI is increasingly a “build massive infrastructure” game, in which power, chips, cooling, and timelines become the bottlenecks.

With incumbents such as Amazon, Alphabet, and Microsoft able to spend enormous sums, it can resemble past capex booms in which everyone overbuilds to avoid losing the future. The punchline: speed and competition don’t repeal base rates, and an arms race mindset tends to trade caution for momentum.

https://t.co/FsJkNsLWEP