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Sunday, October 25, 2026

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@kevin__mak 3 clicks

Kevin Mak on X

$CMPS Great article this weekend in Politico about psychedelics. There's overwhelming alignment across the government to moving these treatments forward. Given this, I really can't see COMP360 getting ensnared in the approval process, or worse, through reimbursement/REMS bureaucracy once commercialized. At current prices, I believe the market is treating CMPS as a "risky proposition" because historically, that was very true. I think that regime has changed dramatically in the last 12 months. Spend some time talking to an LLM about COMP360 vs Spravato (>$2B/year in sales). Which would you rather take? But even more importantly, Spravato has <5% market share of Treatment Resistant Depression, the other ~95% of patients are generally seeking options. Disclosure: Creek Drive and its affiliated funds holds a long position in CMPS. Views expressed are current opinions for information only, subject to change and are not investment advice or a recommendation to buy or sell any security. Investing involves the risk of loss and past performance is not indicative of future performance. See the disclosures link in my bio for more important information. --- The VA has led the push in Washington to advance access to psychedelic therapy. It’s involved in 20 psychedelic clinical trials and was one of the first major health care systems to roll out Spravato, an FDA-approved treatment for depression using esketamine, a chemical component found in ketamine. Ketamine — an anesthetic frequently referred to as a psychedelic due to its psychoactive effects — is currently the only psychedelic-like drug approved for medical use. Trump administration officials say they hope more will be approved soon. “We want to see the drug approved if it’s safe and effective, and the reason why is because there’s a mental health crisis,” Matt Zorn, deputy general counsel at the Health and Human Services Department, told POLITICO.
@aleabitoreddit 6 clicks

Serenity on X

Just another $40B going into the "AI Infra" Bubble... Elon stated this $SPCX financing would primarily fund $NVDA GPU procurement H1 2027. Which indirectly increases demand for memory, networking, etc needed. In some other notes, VPEC today in UDN: "InP substrates is seriously in short supply" in regards to suppliers like $AXTI. - Morgan Stanley believes that InP substrates, EML and CW lasers will be the primary bottlenecks - VPEC emphasized that whoever can secure more raw material supply in the future will have greater pricing power and influence in the market. Very true about supply procurement... both upstream materials like epiwafers/substrates to ultimately compute. We're in a volatile period where all your largest companies in the world are fighting over control of the future of AI infrastructure. Any slowdown seems unlikely.
@calvinblissett 6 clicks

Calvin Blissett on X

$MP. You guys know me I am CHEAP, negative enterprise value, double digit dividend yields cheap. The theme behind $MP looks very secular, I saw Ross Perot call what they have in California the “Saudi’s Arabia” of magnets. Analysts price targets are virtually all 100% above today’s price. The selloff is not justified based on the underlying commodity price (aka fundamentals) is my takeaway from some reading. I also spoke with someone who worked at BofA this summer and per him “on a call with a senator the senator was essentially just repeating buy $MP and the moderator said shut up and stop”. May someone with a bigger brain then me give their thoughts
@calvinblissett 1 click

Calvin Blissett on X

$MP. You guys know me I am CHEAP, negative enterprise value, double digit dividend yields cheap. The theme behind $MP looks very secular, I saw Ross Perot call what they have in California the “Saudi’s Arabia” of magnets. Analysts price targets are virtually all 100% above today’s price. The selloff is not justified based on the underlying commodity price (aka fundamentals) is my takeaway from some reading. May someone with a bigger brain then me give their thoughts
@RPavuluri 8 clicks

Rohan Pavuluri on X

Always amazed when I learn about a new public company for the first time. Especially one that did YC and is based in SF/NYC. @BillionToOneInc is a $5B+ public company ($BLLN) that I never heard of before today. Despite it being YC S17 and the fact that I did YC myself a couple batches afterwards, I had no clue it existed. As far as I can tell, it's @ycombinator's biggest bio success story too. Checked the X account and it has 1,302 followers. Have never seen on a podcast, a wsj article, on the timeline, etc. but yet a monster bio company making very real revenue! Goes to show that there are likely multiple companies founded in last 10 years (not just the sleepy under the radar midwest ones from decades ago) still based in hot areas (BillionToOne is in Menlo Park) that still don't show up on the "timeline" and are even public (BillionToOne IPOed last year) that fly very under the radar...looks like the buzz makes no difference to its success!
@convequity 1 click

Convequity on X

Guess what is a more severe bottleneck than HBM? Grid transformers, switchgear and EPC, and electrical steel, both severity 94, are more severe than HBM at 93. Those numbers come from our AI Infrastructure Bottleneck Map, an AI infrastructure supply chain map. Severity runs from 0 to 100 and measures how hard a node constrains new AI capacity in 2026 to 2028. It measures scarcity, not the size of the market. On each company we score return potential and risk, each from 1 to 10 over the same 2026 to 2028 window. Return potential is the upside still left in the company. Risk is company risk, and 10 is the riskiest. The goal is to identify the companies with high remaining return potential and relatively lower risk. Not investment advice. The five most severe nodes, and what each one is: Grid transformers, switchgear and EPC, severity 94 Medium- and high-voltage equipment, grid interconnect, and the construction services that install them. The backlog runs multiple years, and the constraint is forming through 2028. • $HTHIF Hitachi, Ltd. Return potential 6.2. Risk 1. This is the lowest risk on the list, the return potential is still high, and the grid business sits inside Hitachi rather than in a separate listing. • $POWL Powell Industries. Return potential 7.5. Risk 3.2. This is the highest return potential on the list, the risk is still moderate, and Powell sells the medium- and high-voltage equipment on this node. • $600089.SS TBEA Co., Ltd. Return potential 6.5. Risk 6.1. Return potential is high and risk is high, and TBEA builds high-voltage transformers in China. Electrical steel, severity 94 The core steel inside transformers. Supply is tight, and this constraint is also forming through 2028. • $5401.T Nippon Steel. Return potential 6.4. Risk 3.2. High return potential with relatively lower risk, from a major mill for the electrical steel that goes into transformer cores. • $005490.KS POSCO Holdings. Return potential 6. Risk 3.8. This is the holding company rather than a separate steel listing, POSCO is a major electrical-steel mill, and the return potential is lower than Nippon Steel's with higher risk. • $CLF Cleveland-Cliffs. Return potential 6.5. Risk 4.2. Return potential is high, the risk is higher than Nippon Steel's, and Cleveland-Cliffs is the only US producer of grain-oriented electrical steel, the steel in transformer cores. HBM, severity 93 High-bandwidth memory stacks, which constrain accelerator performance. Supply is extremely tight and the vendors are few. • $005930.KS Samsung Electronics. Return potential 6.5. Risk 3.5. High return potential with relatively lower risk, from one of the three companies that make HBM. • $000660.KS SK hynix. Return potential 6.5. Risk 4. SK hynix is the second of the three HBM makers, with the same return potential as Samsung and higher risk. • $MU Micron Technology. Return potential 6.5. Risk 5. Micron is the third HBM maker, with the same return potential and the highest risk of the three. Gas turbines and on-site generation, severity 88 The turbines that make prime and backup power on site, and the hot-section parts those turbines need. This is the next power constraint forming in the 2026 to 2028 window, and this node has two listed names, not three. • $HWM Howmet Aerospace. Return potential 6. Risk 2.3. High return potential with relatively lower risk, and Howmet makes the castings that large turbines wait on. • $603308.SS Anhui Yingliu Electromechanical. Return potential 7.2. Risk 7.8. Return potential is high and risk is high, and Anhui Yingliu makes castings for industrial gas turbines in China. Leading-edge foundry capacity, severity 86 Manufacturing capacity at 7 nanometers and tighter. The map calls this the main AI hardware bottleneck. • $TSM TSMC. Return potential 6.2. Risk 3.8. The scarce capacity on this node is the capacity TSMC already runs. • $INTC Intel Corporation. Return potential 7.4. Risk 6.8. Return potential is high and risk is high, and the foundry work sits inside Intel with no separate foundry listing. • $0981.HK SMIC. Return potential 6.2. Risk 6.8. SMIC, Semiconductor Manufacturing International Corporation on the Hong Kong line, is the third listed foundry on this node, with a higher risk than TSMC.

Investor Letters

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MYR Group q3’26 Earnings Preview

MYR Group’s Q3 2026 preview cites data-center and power transmission demand, with long-term service agreements supporting margin growth and…

MYRG $4B
Monte Independent Investment Research 5 clicks

Mosaic, Part One: The Story

Mosaic’s history traces the 2004 Cargill-IMC merger and the phosphate and potash mines that shaped NYSE: MOS.

MOS $5.5B
Latticework by MOI Global 33 clicks

Mosaic, Part Two: The Deep Dive

Mosaic, NYSE: MOS, is the subject of a second audio program for professional investors analyzing fertilizer producers.

MOS $5.5B
Latticework by MOI Global 4 clicks
GNCGF · long

Greencore Group PLC

Greencore is the UK’s leading fresh prepared food producer, pitched as undervalued with potential to nearly double within 12–24 months.

GNCGF $3B
Value Investors Club 1 click

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