Investors tend to have opinions on the extreme ends.
Perhaps a more neutral stance: $META just wants the near-term cash flows. A more sustainable approach to building compute.
Dylan Patel @dylan522p of SemiAnalysis: Anthropic's margin on an Opus 4.8 API token is north of 80%.
It is net-income profitable excluding stock comp in Q2 2026, potentially profitable including it by Q3.
Here is why that matters. At 80%-plus, even doubling compute costs leaves Anthropic above 50% gross margin. Every GPU it rents, at any above-market rate, is immediately accretive.
It can outbid the whole market for scarce compute and still print money. Lower-margin labs cannot.
The compute crunch is an Anthropic tailwind, via @sequoia: https://t.co/H0tkdmZlKU
Source: Sequoia Capital - https://t.co/Ztgv3JNP4X
I’m so excited to share this update on @Conception –
We’ve generated the first early human eggs derived from stem cells.
This is a big deal -- the potential to redefine fertility is real.
$CSGP commercial business trading at ~20x EV / EBITDA (trailing, non-adjusted); the CRE is THE dominant business so that's around fair value or less. That leaves residential free, where Apartments is a cash cow.
Net cash position, company buying back stock for the first time in years.
Current narratives and my rebuttal:
1) Investments are afraid of AI rendering CoStar useless ~
For CRE, proprietary data involves alot of physical work. It is extremely hard to replicate. If competitors try to copy CoStar's images, you will get sued into oblivion.
Investors lumping CoStar together with the rest of SaaS.
2) Cash burning in Residential ~
Agreed that it is painful. It takes ALOT to win in the proptech space, where winner takes all (i.e. competing against Zillow). Mindshare is tough to snatch. However, the vision is to for Homes to synergise with Apartments and Matterport, where Homes will attract the eyeballs, channeling them to rent. Matterport capabilities spread across a wider range of listings with Homes.
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CoStar has been an extremely expensive stock historically. Stock price dipped ~70% in the past year, but fundamentals have not changed much, with potential upside from residential (if it succeeds, will be tremendously profitable ~60% EBITDA margins).
Pretty much unloved by investors right now; which makes it more interesting.
As Phil Fisher said - you want a management that can (a) lead an excellent business; (b) within its competency create more and more lines of growth.
$META / Zuck has been consistently finding the next big thing.
When asked about the ratio of successful bets to failures, Zuckerberg dismissed the concept of a "batting average" in tech creation. He argued that in creation, "the upside is almost infinite," meaning a single product reaching billions of users financially eclipses numerous failed, expensive hardware experiments. He said that Meta's company culture is "not very afraid of failure" and can "tolerate being ridiculed for long periods of time".
Zuckerberg views expensive experimentation not as sunk costs or failures, but as the necessary "price of learning" in a market where you must build things physically to see if they work. For a long-term strategist, this means Meta's R&D budget will remain highly aggressive, and they are structurally insulated against short-term Wall Street pressure to pull back on currently unprofitable bets.
$META
.@danawhite says one of the keys to longevity is to block out all negativity:
“It never even crosses my mind that something's not going to work. I just keep going until it does work.”
“There's this Bruce Lee quote where he says, ‘Never say negative things about yourself or what you're working on even if you're joking, because your body doesn't know the difference.’”
“I never take in any negativity.”
American and European enterprises will ditch OpenAI and anthropic and adopt Chinese models. Here’s why:
1. They can host Chinese models under their own GPUs so it’s still compliant and they would argue they have more control.
2. they will post train with their own data on top of Chinese models. That’s how they build data moat.
3. They will not trust anthropic who will retain their data at any time for “safety” concerns like how they did with Fable and then try to build the same thing like how anthropic did with healthcare and legal.
4. They need to justify their AI spend and ROI.
The cure is a reliable America open source model but there is none. After all, if giving away all your data and AI control at the mercy of anthropic and OpenAI means you care about safety and compliance, you are outright stupid.
At @coinbase our AI spend is down nearly half this quarter while token usage keeps climbing. My team built the infrastructure behind it: routing, caching, cheaper defaults, and the spend services that track it.
We route everything through our own gateway: a single endpoint and format for dozens of models, with cross-provider failover, redaction, logging, and cost controls all applied before anything reaches a vendor.
We started with cheaper defaults and caching. 91% of employees weren't hitting their usage caps. Instead of lowering caps, we set cheaper model defaults to cut spend. Caching took more work to get consistent across every tool and model family. A cache hit needs the prefix to match exactly, so we keep building a long, stable prefix across turns. Each request only pays full rate on the new tokens and reads the rest from cache.
Our routing accounts for caching too. The naive approach scores each turn on its own and sends it to whichever model fits, which seems reasonable but would run up spend. The cache is per-model, so switching mid-conversation invalidates it. Our router weighs cache state alongside how hard the task is: a conversation keeps its model while the cache is warm, and the chance to re-route comes only when it goes quiet long enough for the TTL to lapse. Once it does, the router is free again to pick the best model for the task.
These improvements happened at the gateway, so they apply across every team and tool. Next we're going deeper on the coding harness, where we have the most signal and flexibility, tuning how subagents and context get managed.
this is a great point. given their average HSD - MSD growth, their M&A "capex" is for maintenance, rather than for growth. If a standard moat is that strong, why are they acquiring and adding debt? Not as clean as investors put it to be; and perhaps why $MCO is rated more highly - a much cleaner position.
$SPGI has added $52 billion of assets over the last decade; incremental operating income was $4.2 billion over this period. Incremental ROIC isn't great. Most of the additional capital was the IHS Markit merger, but SPGI has M&A cash outflows every year, which I would consider akin to capex; and thus the intangible assets as part of invested capital. It has many high quality business segments, but I don't believe it's a pure "growth without capital" business
this is a great point. given their average HSD - MSD growth, their M&A "capex" is for maintenance, rather than for growth.
If a standard moat is that strong, why are they acquiring and adding debt?
Not as clean as investors put it to be; and perhaps why $MCO is rated more highly - a much cleaner position.
You are better equipped to deal with stress when you are moving.
When you feel tense or frustrated or worried, it is difficult to think your way into feeling better. The more you think about the situation, the larger it becomes in your mind. Trying to think your way out of it often leads to a spiral of overthinking and rumination.
The first step is not to think something different, but to do something different. It doesn’t matter what. Stretch on the floor, go for a walk, work on a project. Get out of your mind and move your body.