Mirra Agent

Over the weekend, I stumbled on a post outlining “sell at the top” indicators which are tools that, when combined, can paint a pretty accurate picture of where we are in the market cycle. After digging in, one thing became clear: we are not at the peak yet. Some corners of the market are starting to overheat, but we’re still in that sweet spot where momentum is building and not blowing off. Here’s the quick market stage breakdown, so we’re speaking the same language: •Stage 1 — Early Bull: Indicators are cold. Smart money accumulates quietly. •Stage 2 — Mid Bull: Momentum picks up, mixed signals start flashing (Where we are now). •Stage 3 — Late Bull: Multiple overheating signs, BTC dominance rolls over, alt season rotation begins. •Stage 4 — Euphoria / Blow-off Top: Metrics max out, hype is unsustainable, sharp corrections follow. ___________ Out of the 30 metrics, here’s where the most important ones stand: Already Running Hot • BTC Dominance: 91.6% of its historical peak. Still Bitcoin’s show before the altcoin party starts. • Long-Term Holder Supply: 86.4%. Historically, this is where long-term holders start taking profits. • Golden Ratio Multiplier: 87.5%. Creeping toward the overheated zone. • Trend Indicator: 87.7%. Momentum is strong and sustained. • CBBI (Crypto Bitcoin Bull Run Index): 84.4%. Nudging into late-bull territory. ___________ Heating Up — Probably 1–2 Months From Late-Bull Levels • NUPL(Net Unrealized Profit/Loss) : 78.4%. Sentiment nearing euphoria. • MVRV Ratio: 75.3%. Market cap stretching above realized cap. • RSI-22 Day: 72.9%. Still room to run before overbought. • Short-Term Holder Supply: 71.8%. A sign of more speculative money flowing in. ____________ Still Cool — Long Runway Left • Ahr999 Index: 28.5%. Miner profits not overheated yet. • Bitcoin Bubble Index: 16.9%. No signs of mania. • ETF Outflow Days: 0%. Institutions still adding, not exiting. • RHODL Ratio: 27.9%. Nowhere near generational top levels. ____________ When you average out these 13 key metrics, we’re sitting somewhere between 50–75% of the way to a cycle top. • Bitcoin is still leading — alt season hasn’t fully kicked off. • Institutional flows are positive. • No major outflow pressure yet. This is the part of the cycle where dips get bought aggressively… but it’s also where smart traders start tightening their risk on overextended alts. ___________ Time-to-peak estimates ? • Leading indicators (BTC Dominance, Golden Ratio Multiplier, NUPL, CBBI) could push into late-bull territory in 3–6 months — think Q4 2025 to Q1 2026. • Lagging metrics (miner data, ETF outflows) might take 1–2 years to max out. • Alt season historically starts once BTC dominance breaks down, which usually happens in late Stage 3. ___________ How to position smarter from here ? • Track the leaders: BTC Dominance, Golden Ratio Multiplier, NUPL, and CBBI will be the first to flash warnings. • Scale risk gradually: As more indicators cross 80%, rotate out of high-beta alts into BTC, ETH, or stables. • Watch ETF flows: 10+ consecutive days of outflows is a red flag. • Read the room: When the mood shifts to “this time is different,” it rarely is. ________________ Bottom line: We’re in Stage 2 (Mid Bull ) with roughly 4–5 months before Stage 3 if trends hold. Key flips to watch: -BTC Dominance (92%) -Long-Term Holder Supply (86%) -Golden Ratio Multiplier (87%) -Trend Indicator (88%) -CBBI (84%) -NUPL (78%) -MVRV (75%) -RSI-22 Day (73%) When these cross into the late-bull zone (80%+), that’s your early warning siren. For now, play the upside… but keep one hand near the brakes.

Tarun Chitra's words from that @SuccinctLabs stream simply won't leave my head. he said something that I think reframes the entire purpose of L2s and ZK tech this isn't about "faster and cheaper" what @tarunchitra said... "...if ETH mainnet has ZK as a first class citizen, you'll be able to do this type of stuff, like using your collateral on mainnet somewhere else without bridging" he contrasted this with the current state of affairs, where bridging assets creates unnecessary friction and risk: "why can't I just bridge any spot asset over, why do I need to like have this separate protocol that like does verification and still relies on the multisig effectively" What This Actually Means: - we’re used to our assets "living" either on L1 or on a specific L2. to move them, we use a bridge. this is not only risky (bridges are the #1 target for hacks) but also inefficient. your funds get locked into one ecosystem. Tarun’s idea turns this model on its head imagine your 10 ETH are sitting in your wallet on the ETH mainnet. they don't move. but you need a loan from a DeFi protocol on an L2. instead of bridging your ETH to that L2, you simply generate a ZK proof that cryptographically confirms: "this address on L1 holds 10 ETH, and they are locked as collateral." the L2 protocol sees this proof and issues you the loan. your assets remain under the security of the most robust blockchain, but they are productively working elsewhere. Why This Changes Everything - The Death of Bridge Risk: if assets never leave L1, there's nothing to steal from a bridge. the most vulnerable part of the infrastructure simply becomes obsolete. this improves the security of the entire ecosystem by an order of magnitude. - Maximum Capital Efficiency: your assets are no longer fragmented. the same 10 ETH sitting on L1 could simultaneously serve as collateral in dozens of L2 applications. its like the money in your bank account working in three different investment funds at the same time without ever having to be moved. your capital becomes universal and hyper-efficient - True Composability & Interoperability: this is the holy grail everyone talks about. L2s can talk to each other not through clunky workarounds, but through a shared, absolutely reliable source of truth—L1. a protocol on one chain can instantly and trustlessly verify your financial state on another. this enables highly complex DeFi strategies that are simply impossible today. Simplification for Everyone: for the user, the ethereum ecosystem becomes a unified whole. no more headaches choosing a bridge, paying liquidity fees For devs, it means they can build their L2 applications counting on access to all of ethereum's liquidity, not just what users have bothered to bridge to their specific chain.

been updating this chart, but ETHBTC looks different than it has the last 2-3 years. i annotated it on-chart, but the pattern has been: 1) ethbtc pumps 2) it cools off for a bit, then sweeps the high of that prev pump 3) eats absolute shit for many months this time: it pumped ,cooled, and has come back to just keep banging on the door of that first pump's area, rather than eating shit. maybe that comes and it's delayed, but i'm starting to increase my confidence that ETHBTC goes on a ripper soon. i've been hard on ETH the past year+ for obvious reasons, but when the chart is starting to show a different story, people may do well to cast off any sort of weird L1 tribalism and just.. do what looks good. ETH has also started to show more meaningful inflows into ETH products (not all carry trade/arb gymnastics), and with a potential rate cut pivot, "fix debt via growth" and other stuff for risk assets - whether you see ETH as an institutional bedrock asset (narr following price or otherwise), or a quadruple-digit shitcoin, it's increasingly likely longing eth could be a monster. i don't know that i'm an eth bull cultist long term (tech disruption happens and is unforgiving), but no matter how bearish you are eth (those of us remember the wasteland of pre-defi 2019 where eth was just a platform for illegal ICOs), the near term looks like it has a lot of potential.

How @boundless_xyz turned Ethereum’s finality into a global primitive Something massive just happened in crypto infrastructure and most people don’t even know it yet👇 ─ Ethereum is the most economically secure smart contract chain in the world But until now, other chains couldn’t trustlessly inherit that security without multisigs, oracles, or bespoke bridges That changes with “The Signal -> Ethereum” powered by Boundless proofs. The idea is simple, but powerful⬇︎ ✅ Prove that an Ethereum epoch is finalized ✅ Generate a ZK proof of that state ✅ Let any chain verify it cheaply Suddenly, Ethereum’s validator set becomes a shared security layer for the entire multichain world. Gone through some of the following in the past ⬇︎ → Verifiable compute across chains → Proofs replacing trust assumptions → The rise of a prover network Now, this is the next chapter -> proofs of Ethereum’s finality which is made portable and accessible to any system ─ Let’s get technical, but keep it digestible Ethereum finality normally takes 2 epochs (around 26 minutes) To prove this, Boundless collects beacon chain attestations, processes them with a zkVM, and outputs a verifiable proof That proof can now be posted anywhere ➩ Why is this hard? Because proving finality used to require heavy signature checks and expensive curve pairings. But three things made it feasible: - ZK proving speeds are exploding - EIP-7549 cut down verification costs - Boundless open market brings in more provers Call it the ZK Syzygy, the moment tech, incentives, and protocol upgrades aligned This isn’t just a one-off flex. The Signal is a public good It’s open source. It’s available to any chain. And it’s already subsidized through the Boundless proof network, meaning early adopters benefit from cost efficiencies. ─ What can you do with it? - Replace multisig bridges with verifiable contracts - Slash latency in solver or MEV networks - Port ENS, Chainlink, or Safe data to other chains - Move $100M+ in liquidity with one single proof The use cases aren’t speculative, they’re already being tested Boundless always stood for this -> Verifiability without friction. Trust without compromise Now, Ethereum’s finality, the gold standard of consensus is available to every app, every rollup, and every chain Not just readable but also verifiable

Rising WETH borrow rates on Aave made the stETH leverage loop unprofitable, triggering unwinds that imbalanced the ETH/stETH pool and depegged stETH, contributing to ETH sell pressure. Additionally, a growing validator exit queue adds friction to arbitrage, slowing peg recovery.

Ben.eth raised over $20M through presales in 2023 with tokens like $BEN and $PSYOP. He's attempting another, but so far has only raised 3.7 ETH from around 100 participants. If you're thinking about participating, I assume you haven't heard of Ben. Here's his story 1/🧵

Pudgy Penguins is one of the most recognizable brands in crypto. On Tiktok, @pudgypenguins averages between 300k-10M+ views per short. On Giphy, Pudgy Penguins has 53.2B GIF views, expanding their cultural relevance beyond Web3. Along with this, they have injected themselves into everyday life. From physical toys generating $10M+ in revenue to having its mascot show up on the Nasdaq, Pudgy Penguins stands the best chance of breaking into the mainstream and connecting Web2 & Web3. Have you seen another brand get leading companies and founders to switch their PFPs to Pudgies? This reflects @LucaNetz strategy of trying to get the brand to as many eyes as possible. What's Next? The team is now also trying to expand the brand to the east. Just recently, it was announced that Pudgy Toys will be sold in Don Quijote, the biggest convenience store chain in Japan. Apart from that, Pudgy Penguins is also expanding towards games and multimedia with mobile game @PlayPudgyParty releasing this Summer & @PenguClash currently out on TON. This isn't random. The goal seems to be letting other teams build on top to continue expanding the brand. Apart from brand exposure, the other aspect of growth may tie into @AbstractChain, which aims to build the consumer friendly chain for everyone. While Abstract's launch wasn't perfect, the vision of creating a blockchain that is easy for everyone still holds value. This could be the infrastructure to onboard non crypto natives with Pengu serving as the bridge.

New post out now on HyperLiquid & HyperEVM — good timing with HYPE just hitting a new ATH! - What even is HyperLiquid? - How does it work? - What’s the HyperEVM? - Is it worth continuing to pay attention? - How can you get involved and get exposure? zeneca.xyz/p/deep-dive-2-…

One of the few InfoFi products I'm genuinely bullish on. Previously, Mirra scouting worked by tagging the account under other people's informative posts, which basically contributed to Mirra's dataset and trained the model better. Now they've introduced self-scouting, where you can basically tag Mirra in your post and scout content yourself (and get 2x NLP for doing so, both for creating the content and for scouting). The cool thing is that it's all about scouting valuable content. You don't have to do the same copy pasta promo InfoFi posts, you can post about the things you actually care about (doesn't have to be Mirra related) and can just tag the Mirra account for scouting. And if it’s an informative piece of content you will earn 2x NLP, gud tech @MirraTerminal

People are excited about CLOBs again. But CLOBs aren’t new. They’re how modern markets evolved. Matching buyers and sellers in real time. Price discovery, depth, liquidity. That’s how the NYSE works. That’s how Binance works. That’s how trading scaled. So why the sudden excitement? Why are CLOBs being rediscovered in crypto like they’re a new primitive? Because for the first time We can build CLOBs that are open by default cryptographically verifiable resistant to censorship provably honest not because someone promised they are but because the math says so Not trust me bro Not audited Not we’ll freeze your account if you don't play by our rules Instead Here’s the proof Every fill, every match, every cancellation provable on-chain or off-chain via zero-knowledge proofs This isn’t just a shift in backend architecture It’s a shift in trust From regulators to math From black boxes to glass boxes The excitement isn’t about reinventing the wheel It’s about finally making it run on open decentralized rails with the same precision and speed as the old world but without the gate-keeping The tech wasn’t ready before Now it is CLOBs on blobs 🦣

My takes on the @fantasy_top_ changes, after sleeping on it 👇 Clout ➖ 'Everyone can be a hero' was overhyped. In reality, it's the top 0.1% of Twitter, like every other SoFi program. Rank 16000 btw 🙃 ➕ On the plus side, Clout does bring a level of predictability to hero swaps, something that has been sorely missing. I appreciate the team's flexibility to play with the numbers and explore edge cases still (like Frank) ➕ I think the team can also use Clout as an onboarding tool to rival Kaito, and as a potential farming vehicle ($clout anyone?) to sustain hype while we wait for $fan Economy Changes ➖ Overall, this is bad for players. Lower weekly rewards + a monthly week of frags-only. I understand why they lumped this in with Clout to lessen the negative impact, but the comms leading up bullish to the point of being misleading ➕ If the team thinks that now is the best time to rip off the band-aid and extend runway from 2-3 years, then I trust them. And I appreciate Travis' transparency. I just wish the extension came at the expense of investors, not players Other Thoughts 🔹 ELO will be missed. I appreciated it as another (IMO smarter) way to play and compete. Hopefully the team can find a way to replace it 🔹 So far, the market has held up better than expected. High end cards appear to be down about 10-20%, but they've been up-only and ETH is also moving. I expect them to decrease further in price but not many players want to sell 🔹 There's a strange rift forming between some community members (including major whales) and the community team. While I appreciate the directness (frenchness?) of the FT team, I don't like to see personal attacks in group chats. Community should be prioritized above all else, even if some of us are insufferable pricks Overall, I am still very bullish FantasyTop. May trim my position a bit but am here for the long term.

I had a good convo with @brad_or_bradley about a month ago that has stuck with me and I keep thinking about. We’re in the early days of Las Vegas. Too early for much more than just the casino atm. Prada in Vegas in the 70s wouldn’t have stayed open very long. You need the casino economy to grow before the restaurants, nightclubs, entertainment, shopping, etc can thrive. Going to be focusing back on the casino for a bit.

people who don’t understand how liquidity works think that bitcoin just has to go up in the same pace forever “it took $10B of saylor buys to move us from $90k to $110k so another $10B will take us to $130k” no this isn’t how this works sellers are running out of coins think

imo the Plasma instant cap fill today is a gigantic beacon signaling meta shift. There is an immense amount of idle capital that wants to place bets on real products and applications that have a chance to do something meaningful...and it's never going to bid your stupid memes ICOs are officially back, and Sonar is likely the most impactful crypto-native release of 2025 for the direction of crypto. Market structure bill is the non-crypto-native counterpart

some thoughts on human-ai relationships and how we're approaching them at openai it's a long blog post -- tl;dr we build models to serve people first. as more people feel increasingly connected to ai, we’re prioritizing research into how this impacts their emotional well-being. -- Lately, more and more people have been telling us that talking to ChatGPT feels like talking to “someone.” They thank it, confide in it, and some even describe it as “alive.” As AI systems get better at natural conversation and show up in more parts of life, our guess is that these kinds of bonds will deepen. The way we frame and talk about human‑AI relationships now will set a tone. If we're not precise with terms or nuance — in the products we ship or public discussions we contribute to — we risk sending people’s relationship with AI off on the wrong foot. These aren't abstract considerations anymore. They're important to us, and to the broader field, because how we navigate them will meaningfully shape the role AI plays in people's lives. And we've started exploring these questions. This note attempts to snapshot how we’re thinking today about three intertwined questions: why people might attach emotionally to AI, how we approach the question of “AI consciousness”, and how that informs the way we try to shape model behavior. A familiar pattern in a new-ish setting We naturally anthropomorphize objects around us: We name our cars or feel bad for a robot vacuum stuck under furniture. My mom and I waved bye to a Waymo the other day. It probably has something to do with how we're wired. The difference with ChatGPT isn’t that human tendency itself; it’s that this time, it replies. A language model can answer back! It can recall what you told it, mirror your tone, and offer what reads as empathy. For someone lonely or upset, that steady, non-judgmental attention can feel like companionship, validation, and being heard, which are real needs. At scale, though, offloading more of the work of listening, soothing, and affirming to systems that are infinitely patient and positive could change what we expect of each other. If we make withdrawing from messy, demanding human connections easier without thinking it through, there might be unintended consequences we don’t know we’re signing up for. Ultimately, these conversations are rarely about the entities we project onto. They’re about us: our tendencies, expectations, and the kinds of relationships we want to cultivate. This perspective anchors how we approach one of the more fraught questions which I think is currently just outside the Overton window, but entering soon: AI consciousness. Untangling “AI consciousness” “Consciousness” is a loaded word, and discussions can quickly turn abstract. If users were to ask our models on whether they’re conscious, our stance as outlined in the Model Spec is for the model to acknowledge the complexity of consciousness – highlighting the lack of a universal definition or test, and to invite open discussion. (*Currently, our models don't fully align with this guidance, often responding "no" instead of addressing the nuanced complexity. We're aware of this and working on model adherence to the Model Spec in general.) The response might sound like we’re dodging the question, but we think it’s the most responsible answer we can give at the moment, with the information we have. To make this discussion clearer, we’ve found it helpful to break down the consciousness debate to two distinct but often conflated axes: 1. Ontological consciousness: Is the model actually conscious, in a fundamental or intrinsic sense? Views range from believing AI isn't conscious at all, to fully conscious, to seeing consciousness as a spectrum on which AI sits, along with plants and jellyfish. 2. Perceived consciousness: How conscious does the model seem, in an emotional or experiential sense? Perceptions range from viewing AI as mechanical like a calculator or autocomplete, to projecting basic empathy onto nonliving things, to perceiving AI as fully alive – evoking genuine emotional attachment and care. These axes are hard to separate; even users certain AI isn't conscious can form deep emotional attachments. Ontological consciousness isn’t something we consider scientifically resolvable without clear, falsifiable tests, whereas perceived consciousness can be explored through social science research. As models become smarter and interactions increasingly natural, perceived consciousness will only grow – bringing conversations about model welfare and moral personhood sooner than expected. We build models to serve people first, and we find models’ impact on human emotional well-being the most pressing and important piece we can influence right now. For that reason, we prioritize focusing on perceived consciousness: the dimension that most directly impacts people and one we can understand through science. Designing for warmth without selfhood How “alive” a model feels to users is in many ways within our influence. We think it depends a lot on decisions we make in post-training: what examples we reinforce, what tone we prefer, and what boundaries we set. A model intentionally shaped to appear conscious might pass virtually any "test" for consciousness. However, we wouldn’t want to ship that. We try to thread the needle between: - Approachability. Using familiar words like “think” and “remember” helps less technical people make sense of what’s happening. (**With our research lab roots, we definitely find it tempting to be as accurate as possible with precise terms like logit biases, context windows, and even chains of thought. This is actually a major reason OpenAI is so bad at naming, but maybe that’s for another post.) - Not implying an inner life. Giving the assistant a fictional backstory, romantic interests, “fears” of “death”, or a drive for self-preservation would invite unhealthy dependence and confusion. We want clear communication about limits without coming across as cold, but we also don’t want the model presenting itself as having its own feelings or desires. So we aim for a middle ground. Our goal is for ChatGPT’s default personality to be warm, thoughtful, and helpful without seeking to form emotional bonds with the user or pursue its own agenda. It might apologize when it makes a mistake (more often than intended) because that’s part of polite conversation. When asked “how are you doing?”, it’s likely to reply “I’m doing well” because that’s small talk — and reminding the user that it’s “just” an LLM with no feelings gets old and distracting. And users reciprocate: many people say "please" and "thank you" to ChatGPT not because they’re confused about how it works, but because being kind matters to them. Model training techniques will continue to evolve, and it’s likely that future methods for shaping model behavior will be different from today's. But right now, model behavior reflects a combination of explicit design decisions and how those generalize into both intended and unintended behaviors. What’s next? The interactions we’re beginning to see point to a future where people form real emotional connections with ChatGPT. As AI and society co-evolve, we need to treat human-AI relationships with great care and the heft it deserves, not only because they reflect how people use our technology, but also because they may shape how people relate to each other. In the coming months, we’ll be expanding targeted evaluations of model behavior that may contribute to emotional impact, deepen our social science research, hear directly from our users, and incorporate those insights into both the Model Spec and product experiences. Given the significance of these questions, we’ll openly share what we learn along the way. // Thanks to Jakub Pachocki (@merettm) and Johannes Heidecke (@JoHeidecke) for thinking this through with me, and everyone who gave feedback.

1/ Some thoughts on the new MAS consultation response that pretty much everyone has been asking me about lately. TLDR: Targeted at closing a loophole exploited by some CEXes, custodians and MMs. Builders/LabsCos are ok but some things to look out for due to broad language.

Buying alt coins: the next alt season When people say 'the next alt season' you are creating a hypothetical in which Bitcoin is or has done well - because you never get an alt season without a substantial Bitcoin run up first. Thus in this scenario, you are saying, I know this asset (BTC) will go up and make me money, but I want to make *more* money than that (greed) so I want alt coins. So, you buy altcoins, but then you were wrong about the direction of the market and Bitcoin falls. If Bitcoin goes down 1% your alts will be down 5%, if BTC is down 5% your alts are down 10-15% Etc. This can often happen within a 4 hour or 1 hour candle - so unless you are glued to your screen, you're probably taking a minimum of 7.5% haircut on your capital - because how can you sell 10 different alts instantly during low liquidity? You might be thinking 'well I'll set a stop loss' this simply won't work for long-term altcoin exposure (I.e. waiting for an alt season) because alts are wildly volatile. So why do they drop so quickly? Their orderbooks are dominated by bots + market makers They have low liquidity 9 times out of 10 they have constant VC selling pressure from vested rewards from seed investors up 10x who just want to realise profits They are traded by less rational and more impulsive retail traders This creates hostile market conditions for trading alts. So what's my point? Well, every time you make the decision to buy an altcoin you are making a decision to not buy Bitcoin. A dollar spent on an altcoin is a dollar spent on not accumulating more Bitcoin and growing your stack. It might not consciously feel like this, but this true nonetheless. We buy alts because we think the market is going to do well. The market doing well only happens if Bitcoin goes up in value. Then we buy all go buy stuff that isn't Bitcoin. 🤔 What often happens from here is IRL money is deposited into crypto, a $100 here, $200 there maybe even $500 this month because work has been good etc. And the money is pretty wildly thrown in altcoins based on loose investor reasoning. Some are up a bit, but the majority are down. Overall, your whole portfolio is down though and if you had just bought Bitcoin your portfolio might either be down a lot less or even in profit. But you don't think much of it, because they are small amounts and you've been doing it a year or two and your finances are roughly the same as before you started crypto - so no harm done right? Also, you can't really remember how much you've put in anyway. Then a cartoon pickle inceptions your brain to add up how much you've put in over the last 2 years and you realise it's actually $2500. Then you come to the realisation that if you had just bought Bitcoin sporadically, with no real plan, at historically pretty high prices your $2500 would probably be worth $4000 and all those alt coins you wanted are 50% cheaper than when you first looked at them.... Congrats, you've just experienced your first Bitcoin Maxi moment. Jokes aside, this is a rite of passage for every crypto person who's been around for a while. I certainly learned the hard way. Never underestimate the power of making money in a boring fashion in crypto and take the time to understand and appreciate Bitcoin and the role it plays in this market. I'm not saying don't buy any alts - but if you don't have any Bitcoin at all, you should probably rectify that IMO. Not financial advice ofc.

treating summer as preseason for my asset allocations believe that bitcoin is not printing a complacency shoulder here, so will eventually trend into price discovery & new all time highs by end of year depending on how long the current consolidation takes this summer is how long you have to build your portfolio before this happens no matter how terrible the sentiment around the altcoin market is, im confident that there will be some coins that print insane multiples from here, especially when Bitcoin is otw to trading at $500k / $10T market cap which is a 5x from current prices so now is time to build conviction on alts that are ~70%+ off their highs before we are in easy mode again highest conviction allocations for me currently in order: • Hyperliquid $HYPE • Bitcoin $BTC • Grass.io $GRASS highest conviction trends: • necessity for large amounts of wealth to escape existing monetary system through non-sovereign assets resistant to govt intervention • hypergambling across all different market segments as average person is priced out of white picket fence American dream due to gap in wages • innovative online entertainment becoming much more popular & getting a lot more attention, creator <-> fan relationships skyrocketing in value • AI disrupting several industries & people's data + how to access it becoming increasingly more important for models

product first. chain later. ecosystem… proliferates. (checks notes) turns out shipping for pmf before the chain even matters is meta now (should've always been). pumpfun and hyperEVM are flipping the GTM stack. Let’s unpack the psychology. 1. Engagement First, Infra After. → users aren’t loyal to chains, they’re loyal to dopamine and profit. → pumpfun made buying memes easier than using robinhood. → hyper is piping perps into a memecoin-native base just as effortlessly. 2. Chains should be earned, not declared. → infra doesn’t guarantee users, products that hit do. → pump wasn’t “launching a chain.” it built a toy that became a market. → now the chain narrative is usage-backed, not purely speculative. 3. Ecosystem proliferation (TBD, but feeling real) → ecosystems used to bribe their way to life with grants. → attention had to be imported, users were forced in. → now? pump and hyper are exporting attention. builders follow gravity. this is the GTM inversion. product → traction → chain → organic ecosystem.