Dog Candles

#Bitcoin • $MSTR | $MTPLF • @_Checkmatey_ is my quant

[Dog Candles @DogCandles]

@saylor Turning into a slop cannon mate…

[Dog Candles @DogCandles]

Time to go long $MSTR call spreads. Been busy building, but I'm still here. I see what's going on.

Jun '27 $300-600
Jun '27 $500-860

Send it.

[Dog Candles @DogCandles]

@saylor Super cringe, please stop with the shitposting. Turning off long term shareholders.

[Dog Candles @DogCandles]

@nikitabier @DCinvestor @X Absolutely hate this change 😒

[Dog Candles @DogCandles]

@elonmusk @nikitabier could you guys fix bookmarks folders please? I scroll for a bit then the app quickly stops loading in older bookmarks

[Dog Candles @DogCandles]

@hillery_dan Dividends paid out

[Dog Candles @DogCandles]

I for one am relishing the opportunity for good entries in the weeks & months to come. Patience 🧘‍♂️

[Dog Candles @DogCandles]

@HermesLux Still think the company needs to generate income on top of this existing model?

[Dog Candles @DogCandles]

Fair, and you shouldn’t trust it, particularly on quantitative subjects like those you explore.

With a bit of investment into some custom tooling though… Two key components:
1. Analyse data using code (AI-generated or human-provided/templated).
2. Build components to verify your AI’s assertions and have it operate in a feedback loop to catch & correct its mistake, similarly to coding agents running with feedback from linters, compilers, automated tests, etc.

Let me know if checkonchain might want to expand 😆
https://t.co/PN6DWt6XCZ

[Andrej Karpathy @karpathy]

Sharing an interesting recent conversation on AI's impact on the economy.

AI has been compared to various historical precedents: electricity, industrial revolution, etc., I think the strongest analogy is that of AI as a new computing paradigm (Software 2.0) because both are fundamentally about the automation of digital information processing.

If you were to forecast the impact of computing on the job market in ~1980s, the most predictive feature of a task/job you'd look at is to what extent the algorithm of it is fixed, i.e. are you just mechanically transforming information according to rote, easy to specify rules (e.g. typing, bookkeeping, human calculators, etc.)? Back then, this was the class of programs that the computing capability of that era allowed us to write (by hand, manually).

With AI now, we are able to write new programs that we could never hope to write by hand before. We do it by specifying objectives (e.g. classification accuracy, reward functions), and we search the program space via gradient descent to find neural networks that work well against that objective. This is my Software 2.0 blog post from a while ago. In this new programming paradigm then, the new most predictive feature to look at is verifiability. If a task/job is verifiable, then it is optimizable directly or via reinforcement learning, and a neural net can be trained to work extremely well. It's about to what extent an AI can "practice" something. The environment has to be resettable (you can start a new attempt), efficient (a lot attempts can be made), and rewardable (there is some automated process to reward any specific attempt that was made).

The more a task/job is verifiable, the more amenable it is to automation in the new programming paradigm. If it is not verifiable, it has to fall out from neural net magic of generalization fingers crossed, or via weaker means like imitation. This is what's driving the "jagged" frontier of progress in LLMs. Tasks that are verifiable progress rapidly, including possibly beyond the ability of top experts (e.g. math, code, amount of time spent watching videos, anything that looks like puzzles with correct answers), while many others lag by comparison (creative, strategic, tasks that combine real-world knowledge, state, context and common sense).

Software 1.0 easily automates what you can specify.
Software 2.0 easily automates what you can verify.

[Dog Candles @DogCandles]

@_Checkmatey_ @ResearchBTCNow Indeed. Mine fiat or follow my intuition, that is the question.

[Dog Candles @DogCandles]

@_Checkmatey_ I’ve actually wanted to build something on top of your & @ResearchBTCNow’s data for a while but work’s been busy

[Dog Candles @DogCandles]

I really appreciate your work and the thoughtful perspectives you share each week.

But I’d recommend not dismissing AI outright. It can be a very powerful tool when used correctly (to enhance thinking, not replace it), and as an engineer in the field, I’m confident you could put it to good use without changing the nature of your content :)

[Dog Candles @DogCandles]

@LizardWizardBTC @JoshMandell6 Aged well, definitely didn’t give the current path a high enough probability

[Dog Candles @DogCandles]

@werkman @jonnypokerasia @saylor Best question by far, thanks!

[Dog Candles @DogCandles]

@ryQuant @Strategy You working on this? You shared that deck about VIX trading a couple months back 👀

[Dog Candles @DogCandles]

@ryQuant @BitcoinPierre @HashOverCash21 @Strategy @saylor @natbrunell @AdamBLiv @werkman @JoshMandell6 Very interesting idea

[Dog Candles @DogCandles]

Thank you for openly engaging with the community! Here are some of my questions.

Will the company acknowledge the inaccurate reporting of BTC Yield from pref issuance (yield reported assuming no future dilution)? Do they think it’s acceptable? Why? Surely the drag of servicing dividends needs to factor into reported KPIs somehow?

The market clearly has no interest in the P/E valuations Phong presented last earnings. Do they think the market is wrong? Do they really view BTC Income as equivalent to BTC Gain when it comes to representing pseudo-earnings? Do they intend to refine & iterate on how they present their business to the market, or just wait it out? Why not be a bit more creative and approach things from first principles? The hand-wavy P/E analogy feels extremely sloppy by the company’s own standards.

Does the company aim to outperform BTC over some defined minimum time frame? If so, what is that time frame? $MSTR is up 20% over past 12m vs 62% for BTC — how do they think about that? We were told not to compare performance over 1m, 3m, 6m… should we still not compare over 12m? Marketing MSTR as 2x Bitcoin is great, that’s what a lot of folks want, but that hasn’t been delivered over recent history, and the company owes it to shareholders to qualify this marketing statement with a duration. Even if that’s 10y, fine — just make your objective known so folks can act accordingly.

Is the company willing to provide some guidance on how they think about leverage/amplification, what they are aiming for, and how they plan to manage it over time subject to evolving market conditions?

Is the company willing to set & communicate targets for pref issuance? Can it sketch out the rough path from introducing a few prefs to capturing 1% of the $300T fixed income market? What are the key milestones? When are they aiming to hit them?

There’s been speculation lately about the company monetising its Bitcoin treasury to generate traditional income. Is this something they are looking into? I assume not based on previous statements, but it would be worth reiterating if that’s the case, because many believe this is essential for the pref model to work.

Thanks again, particularly if you read this wall of text. We have lots of questions 😅

[Dog Candles @DogCandles]

@ChromeHODLs @hillery_dan Probably listened to Michael Howell on Monetary Matters

[Dog Candles @DogCandles]

A huge milestone on what will clearly be a very long journey.

• 640k BTC viewed as risk exposure, not capital.
• B- issuer rating → prefs rated at CCC+ / CCC → no major institutional flows unlocked near term.
• Strong language against upgrade in next 12m.
• Wants Strategy to sit on fiat reserves... yeah, good luck with that.

Seems like science is not the only thing which advances one funeral at a time.

[Michael Saylor @saylor]

S&P Global Ratings has assigned Strategy Inc a 'B-' Issuer Credit Rating (Outlook Stable) — the first-ever rating of a Bitcoin Treasury Company by a major credit rating agency. https://t.co/WLMkFqkkCb

[Dog Candles @DogCandles]

@_Checkmatey_ in case you're not aware 😅