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@dropalltables Not only are those things not mutually exclusive, I think those things are often mutual 😎
The market is pricing the AI cycle like a reinforcing flywheel: Belief> capital> capex> better models> more usage> ROI> high-margin revenue> more belief> more capital. That seems more like a chain that can break.
It was pointed out that 'more capital' is doing a lot of work as its pretty quickly approaching 3% of US GDP
The market is pricing the AI cycle like a reinforcing flywheel: Belief> capital> capex> better models> more usage> ROI> high-margin revenue> more belief> more capital. That seems more like a chain that can break.
GUY WHO BET THE FARM ON THE SECOND PLACE FINISHER VOICE:
this is awesome
My best advisors aren’t on the payroll. In fact, they’re not even real. It's a skill called War-Council that turns subagents into advisor personas: 1. A ruthless CFO 2. A wartime operator 3. A compassionate customer rep 4. 1-2 ‘dynamic’ personas for the use case The ‘Council’
related and great: escurves.com
The market is pricing the AI cycle like a reinforcing flywheel: Belief> capital> capex> better models> more usage> ROI> high-margin revenue> more belief> more capital. That seems more like a chain that can break.
From Goldman's Delta-1 head, Rich Privorotski: "A panel of Gemini 3 Flash, Kimi K2.6 and DeepSeek V4 Pro, fused together, beat solo GPT-5.5 and solo Opus 4.8 outright, while landing within 1% of Fable 5 at roughly half the cost.” (Openrouter -X ) If true, this is exactly the direction of travel the market has been underestimating. The race for intelligence increasingly feels as though it is shifting from a handful of labs toward model orchestration and open-source ecosystems. That is simultaneously bullish and bearish. Bullish because lower costs and broader access should ultimately drive more token consumption and more compute demand. Bearish because it accelerates token deflation and raises questions around the durability of model economics. The trillion dollar question remains whether lower intelligence costs ultimately create more demand than they destroy pricing power."
@danielsinger i think its a universal definition no?
Every founder needs hire their own Wags sooner than they think.
@DannyEarns even looking probably puts you in the top 5% of founders
On an iconic night at MSG, this was the most iconic moment. GIVE THE SHAOLIN THEIR FLOWERS
Facing the largest halftime lead by a road team in non-bubble NBA Finals history, and a dead silent Madison Square Garden, this declaration is when the comeback started.
Spurs found out that the Wu Tang Clan is indeed nothing to fuck with.
BOOM *OpenAI Considers Drastic Price Cuts, Anticipating Costly War For Users With Anthropic -- WSJ
In the midst of all the IPO talk, important to look at what the banks do not what they say.
SoftBank's effort to secure $6 billion OpenAI margin loan falters
Spurs are cooked.
Glad I got here early… 😳 Wu-Tang Clan rehearsal for tonight’s MSG halftime show. 🔥🔥 More here, on the Game 4 Finals live blog, at @TheAthletic nytimes.com/athletic/live-…
I’m flattered :) only a few years late, friends
New: Hollywood talent agency CAA is partnering with its old friends at private equity firm TPG to invest in the businesses of YouTube stars, podcasters, etc. It’s starting with $250 million. bloomberg.com/news/articles/…
In typical fashion, hollywood and wall street are years behind tech and silicon valley. @mmlightcap can probably teach these folks a few things, if she's feeling generous :)
New: Hollywood talent agency CAA is partnering with its old friends at private equity firm TPG to invest in the businesses of YouTube stars, podcasters, etc. It’s starting with $250 million. bloomberg.com/news/articles/…
Over the past two years I've talked to hundreds of mid-market CPG companies. In all that time, maybe 3 had someone formally responsible for AI. In the last 6–8 weeks alone, I've met 12 more — dedicated hires, AI committees, formal evaluation processes. The easy read is that CPG finally got interested in technology. I hate that. As someone that has spent 25 years years in CPG, outsiders always misunderstand the industry and the people who move it forward. I think the interest was always there. These teams have wanted better tools for years. The blocker was the technology itself. For two decades, software built for this industry was poorly designed, demanded massive behavior change, and was rarely purpose-built for how CPG actually operates. Every implementation was a fight against the tool. So teams did the rational thing: they stuck with spreadsheets and email. AI-native solutions are breaking that pattern. They meet teams in the workflows they already have instead of forcing new ones. The adoption cost finally dropped below the value.
This sounds like our thesis for investing in @otter_ai 6 or 7 years ago...
“Companies cluster into verbal cultures and written cultures… The historical bottleneck for verbal cultures was that the important context happened in conversation and then evaporated. When AI can attend every meeting and synthesize what happened, verbal culture finally
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