the main issue with Bitcoin imo is that for last few years the marginal bid was etf flows and Saylor, both were price-insensitive and both are kind of gone now.
etfs are in record outflows and $STRC is below par so saylor’s issuance engine is on vacation while he’s selling btc to fund the dividend so the bid that held price up regardless of valuation just disappeared.
so when you remove a price-insensitive buyers that probably lost bit of apetite in Bitcoin ETFs after being sent three tax brackets lower on 10/10, price kinda has to has to fall until price-sensitive demand shows up.
therefore for the actual bottom I would preferably like to see either another very traumatizing event (large OI flush, RV > IV as shared on screenshot, deep negative funding and so on) or new demand showing up at prices which are too attractive to skip.
from the look at things, it feels like these violent delights will have violent ends.
Perps being banned in the US was one of the largest tail risks. That risk is gone.
HL’s model is stablecoin-margined perps. This model has now been blessed.
Yes it benefits Kalshi and Coinbase directly in the short term, but perps as a product category is going to get a whole lot bigger as a result.
Rising tide lifts all boats.
We welcome today’s CFTC actions: approval of the first U.S.-listed perpetual derivatives contract, an accompanying Commission policy statement on the listing of perpetual derivatives, related interpretive guidance and no-action relief from the Market Participants Division, and a Staff Advisory on 24/7 Trading, Clearing, and Settlement, as a long-overdue acknowledgment that perpetual derivatives are a legitimate and essential tool for price discovery and risk management.
For too long, regulatory ambiguity drove these markets offshore, depriving American traders and institutions of access to regulated venues and undermining U.S. competitiveness in the global derivatives markets.
Today’s actions chart a new path forward. We look forward to engaging closely with the Commission to ensure that the framework it develops is workable not only for centralized intermediaries, but for the onchain protocols where the most significant perpetuals activity actually occurs.
i've been running Codex for ~8-24h per open math/physics research problem. few thoughts:
parallel agents don't seem to scale that cleanly for a lot of problems. many of these are just extremely sequential. you don't really get to "spawn 50 agents and solve it from nowhere." it's more like: tiny move, check, reframe, tiny move, dead end, try again. hours/days of serial cognition, which honestly rhymes with how these fields move over decades.
this updates me a bit against the sci-fi picture of "superhuman math/physics intelligence" as some alien oracle that instantly sees the proof / theory.
the actual superhuman-ness is more mundane and maybe more important: the agent has absorbed a huge prior, can read long papers basically instantly, can think/write at >50 tok/s, and you can clone it across dozens of problems. speed + knowledge volume + multiplicability. that's the superpower.
also: frontier physics seems much more tractable for these agents than decade-old open math problems. for some physics directions, ~8h is enough to get something paper-shaped and nontrivial.
big caveat tho: research taste is still missing. the agent is a pretty good problem-solver, but not yet a top-tier problem-picker. it can push hard once the direction is chosen, but you probably still want a human with taste choosing the problem / framing / bet.
current model: agents are becoming very strong research labor, but the bottleneck shifts upward into taste, problem selection, and knowing which hill is worth climbing.
quick thoughts pre mkt
Korea had a scare in the early morning when a policymaker floated the idea of redistribution of "gains" from the memory shortage beneficiaries like samsung and SK Hynix. IMO - This is why there is a valuation gap between KR, JP and US equities. Stock and equity holders do not share the same protections that they are afforded in the US.
Aside from that, these comments are probably a first indication that while the AI roll out is indeed REAL. Governments may have to step in to equitise between the "haves" and "haves not". What that means is equity price down.
Overall, i think positioning in memory and semis are very stretched. This doesnt necessarily mean they will go lower, only that if they do go lower, there will be a big unwind. Possible ideas - sell 1x3 put spreads?
@MadsPosting@ElishaDLong Convinced this how it’s done. Thinking about things just puts a time block in between idea and execution.
May as well just jump straight to execution
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/goal also lands in Codex CLI 0.128.0.
Our take on the Ralph loop: keep a goal alive across turns. Don't stop until it's achieved.
Built by my co-worker and OpenAI mentor Eric Traut, aka the Pyright guy. One of the GOATs I get to work with daily.
We rebuilt Kiyotaka for v4.0. Still 100% free to use for all chart enjoyers.
This is the biggest product release we’ve shipped yet:
a complete redesign, major UI/UX upgrades, new search, new chart types, better tooling, faster performance, new color themes, and a much improved execution interface. With more coming next week.
But v4 is bigger than a feature drop. Kiyotaka now feels faster, clearer, and much more intentional to use.
This marks a major turning point in how Kiyotaka works and where it’s going next.
One API across crypto, prediction markets, and order flow.
Now open and free.
Monitor odds, funding, toxic flow, and order book pressure from one place.
🇺🇸 JUST IN: SEC says certain crypto interfaces, including DeFi front-ends, wallet extensions, and apps, may operate without broker-dealer registration under conditions:
• No custody of user funds (self-custodial only)
• No investment advice or recommendations
• No order routing or execution
• Fixed, neutral fee structures only
• No discretion over transactions or market activity
There's a physicist at Stanford named Safi Bahcall who modeled this exact principle and the math is wild.
He calls it "phase transitions in human networks." When you're stationary, your probability of a lucky event is limited to your existing surface area: the people you already know, the places you already go, the ideas you've already been exposed to. Your opportunity window is fixed.
When you move, your collision rate with new nodes in a network increases nonlinearly. Double your movement (new conversations, new cities, new projects) and your probability of a serendipitous encounter doesn't double. It roughly quadruples. Because each new node connects you to their entire network, not just to them.
Richard Wiseman ran a 10-year study at the University of Hertfordshire tracking self-described "lucky" and "unlucky" people. The single biggest differentiator wasn't IQ, education, or family money. Lucky people scored significantly higher on one trait: openness to experience. They talked to strangers more, varied their routines more, and said yes to invitations at nearly twice the rate.
The "unlucky" group followed the same routes, ate at the same restaurants, and talked to the same 5 people. Their networks were closed loops. No new inputs, no new collisions.
Luck isn't random. Luck is surface area. And surface area is a function of movement.
The lobster emoji is doing more work than most people realize. Lobsters grow by shedding their shell when it gets too tight. The growth requires a period of total vulnerability. No protection, no armor, soft body exposed to the ocean.
That's the cost of movement nobody posts about. You have to be uncomfortable first. The new shell only hardens after you've already moved.
@om_patel5 The interface is cool, but the deeper shift is this:
The best agent systems reduce supervision overhead.
If you still have to constantly watch the dashboard, you have not really created leverage yet.