Bullpen.News From Edwin Dorsey
Get Daily Recap Feedback

Wednesday, October 7, 2026

Back to today

From X

@convequity 3 clicks

Convequity on X

$NET's AI hosting is limited by the physics of its edge footprint and by the role of its products. Carrier-hotel sites built for fast network traffic are a different proposition from purpose-built AI datacenters. Cloudflare’s own engineering disclosures acknowledge power constraints, and management distinguishes its strategy from the hyperscalers’ GPU spending race. Our assessment starts with a two-H100-per-server edge configuration. H100 PCIe and NVL-class cards operate around 350–400 watts per GPU, versus up to 700 watts for H100 SXM. Hyperscalers commonly pack eight SXM GPUs into a machine and connect those machines into dense clusters. The distinction is power, cooling, memory bandwidth and GPU interconnects — not simply whether a model can run. The existing edge footprint cannot acquire hyperscaler-class cooling and power density through server upgrades. Dense, liquid-cooled Blackwell and Vera Rubin systems require a different infrastructure commitment. We see little chance that NET’s existing edge footprint becomes a competitive home for those dense clusters. For sustained, large-model inference, our assessment is that sparse edge GPUs cost more per token than dense AI clusters. Geographic proximity saves network transit time, but it does not guarantee a faster first token or a cheaper response. Greater compute capacity, faster interconnects and efficient batching can outweigh the edge’s network advantage. We expect heavy training, frontier-scale hosting and the most demanding next-generation inference to remain concentrated with hyperscalers. Workers AI’s progress with larger open models is real. Hosting those models does not establish an economic advantage over dense clusters. AI Gateway also lets customers route requests to external providers, matching the model and infrastructure to the task. Cloudflare can still win substantially. More agents mean more requests to secure, more Workers executions, more orchestration and more demand for fine-grained access controls. Those workloads build on infrastructure and capabilities Cloudflare already has. On the SaaS Survival Scorecard, we score $NET at 2.5 for Model-Layer Leverage. That reflects its substantial work building an agent harness across inference, orchestration and execution, while stopping short of model post-training and reinforcement learning.
@StableBread

Fajasy on X

My investing thesis in a nutshell (w/examples): 1) Buy with a strong margin of safety or stock price near/below cash and/or book value. 2) Buy in industries and/or markets where the money is flowing. Makes it a lot easier. 3) Buy the best early and/or the most overlooked in that particular industry. 4) Pay up for unfair advantages, excellent mgmt teams, and companies with huge latent pricing power. 5) Sell when the thesis breaks. Or a much better risk/reward setup hits your desk. Otherwise continue to add/hold. Don't track stock prices. Track the main business KPIs like any competent mgmt team would. Example #1: Bought $NBIS 4x mid $20's (best overall). Then bought $BRUN common and warrants pre-merger (most overlooked). Example #2: Bought $FTEK $1.39. Cash floor new excellent operator CEO. Strong upside potential w/data centers. Example #3: Bought $BABA $70's. Strong margin of safety, market leader, unfair advantages. Sold $170 for better risk/reward. Example #4: Bought $ELMT @$19 and @$14. Unfair advantage. Strategic. Cheap. Critical in strong growth industries. Example #5: Bought $TOST @$24. Beaten down due to macro headwinds and new/early $DASH competition. But almost everything in business stronger and expanding to new verticals. Lastly, if you're unsure or don't fully understand the business. Just say no. In fact, say no to most stocks. Most probably your best idea is already in your portfolio. Don't lockup your money in a 3/5 setup, you're trying to make outsized returns! And sub to my newsletter (link in bio) if you want my deep dives. 😉

Investor Letters

All letters

Research Roundup Vol. LV

OpenAI’s enterprise privacy push and Synopsys’s Factory 2 royalty model anchor a technology roundup, alongside oil above $100 and Bitcoin’s…

SNPS $97B
Monte Independent Investment Research

New Position (ONON): Game is On

On Holding (ONON) is gaining sportswear share, expanding store space and launching soccer with Kylian Mbappé as investors debate U.S.

ONON $11B
Aurelion Research 3 clicks

Deep Dive: Intuit ($INTU)

Intuit’s $21.4 billion software franchise faces AI-driven pricing pressure in tax and accounting, even as QuickBooks and TurboTax retain…

INTU $79B
Rebound Capital 4 clicks
VEEV · long

Veeva Systems INC

Veeva Systems is a vertical software company valued as if its best growth years are behind it.

VEEV $46B
Value Investors Club

Canterra Minerals: Research Note

Canterra Minerals increased Lundberg indicated tonnage 55% to 26.1Mt, with 226.2Kt of contained copper equivalent, supporting a Buchans…

EQX $13B
Atrium Research - Equity Research

Kenorland Minerals: Research Flash

Franco-Nevada bought 10.0 million Kenorland shares, a 12.4% stake, for C$22.2 million in a secondary transaction that issued no new shares.

FNV $46B
Atrium Research - Equity Research 1 click

Publications we follow

Every publication on this site, hand-picked.

109 publications

Newsletters 92

YouTube 4

Blogs 12

Seeking Alpha 45 of 216

Nominate a publication

X accounts we follow

Every account on this site, hand-picked.

74 accounts
Nominate an account

Investor letters we follow

189 firms

Sectors

Ordered by how often our editor reaches for them.