SocialFi isn’t slowing down and $PAID is an example of that. However, this is a trend that won’t move us forward. When we exhaust narratives, the last thing we should be doing is placing money on the laps of people who’ve gone through no friction or reputational risk to earn it. Of course the common man is going to take 100k and walk away when all he’s had to do is open this app and press one button. As a feature and construct, Xmoney is great. It’s reinvigorating the thesis that many of us traders have seen coming from a mile away with Fomo, Pump and trading attention as a whole. Couple this with their optionality to buy crypto and stocks, soon it will be a WeChat contender. Every style of speculation will continue to be monetized, which is now being laid on top of the source root. X represents the townhall of society and ideologies, we’re fast approaching monetizing attention in final form. What’s more important than placing free money on influential accounts laps, is using this capital as a way to reward power users. X was the first company to demonstrate profitability and growth by giving their revenue to the top power users. Since the inception of bonding curves, fees and revenue have mostly cycled back to deployers and the launchpad itself. Very little, if any has gone directly to the people who’ve caused that revenue. There’s essentially been no rewards cycled back into traders hands other than airdrops, even they’re very far and few in between. We’ve only just started to see a shift with Fomo and Pump app’s callouts. For the first time platforms are realizing they can’t siphon capital from users and claim “buyback and burns” are reinvesting into the community. Not saying I’m against buyback and burns, although when looking at it from a purists perspective, it’s essentially a liquidity drain. I’m sure infra like Paid will continue showing up in different colours. From past memory, I think most of us are past the Bags app meta and it’s time to build tooling which rewards the power users, not refuelling the “please bro” personas to shill bundled micro caps.

The current state for onchain feels like one of those positions where it’s better to wait for a clear reversal than buying the dips. Reasons being: - War escalations causing higher oil prices - Inflation starting to spiral with 30y yields coming back up to $5. Bessent is going to be forced into commentary as he positioned himself as “the house”, now traders are pricing him into action - Innovation exemption - forcing licensed exchanges/dealers of tokenized stocks to have permissioned blockchains/infra and adhering to new policy about assets - Mid terms in 1.5 months, I don’t factor this when considering LTF price, but it’s important to keep in mind when reflecting upon how the republicans are responding to all these factors. If they’re growing unfavourable day by day with decisions, it’s going to cause negative sentiment towards assets as expectations will be that they lose, democrats take the other side to their wrong doings and fiscal policy While I tend to be in the camp of trying to time bottoms based off sentiment and available negative information (known variables and forecastable downside risk), I think it’s better to be patient with onchain here. Since the main drivers of this retrace the past week or so has been catalyst driven, it’s better to assume prices bottoming out will be positive counter catalysts (Bessent addressing the liquidity support buyback operation, derisking war and controlling oil prices, innovation exemption giving more clarity to “dealer exemptions”). One thing to note is we are in a bullish environment. BTC broke the forbidden 82k bear market level. Ideally we get a bullish retest here at 82k and more clarity regarding the innovation exemption and how stockfi coins can continue to operate. In the mean time Stonk looks to have silently increased their buybacks to 75% from 50% in the past day based off their latest revenue update. Nate also wrote a banger thread describing the liquidity flywheel, arbitraging between assets on Long and how it compounds the liquidity acquisition moat. Keeping check on the leading eco’s and how they’re fundamentally evolving will be the best indicator of who has strength when we either get counter positive catalysts or fundamental development so strong, onchain traders outweigh the development over negative backdrop. My gut says we’re close to onchain bottoming but at the same time these current fears driving price down put an overcast on the eco, which are more likely to force us to trade sideways until resolved. Unless we get some sharp wicks to the downside, for psychological reasons I think it’s better to have key distinctions of what type of catalysts or fundamentals would present a buy signal for your desired bags.

There’s a clear reason why coins on Stonk Fun aren’t moving. Slippage is way too high. The 3% tax for reflections doesn’t bother me too much, but there’s an additional 2.5% tax for covering network and operating costs. Pair this with Solana’s low liquidity. Most coins sub 20 mil have around 1:10 LP:Mcap ratio. Meaning 50% of the LP is underlying asset/Sol and 50% native token. Accumulating 0.5% is roughly 15% slippage, 1% is roughly 25%. I get that its the name of the game with the buyback and burns for Stonk + reflections, but if they wanted more runners surely they’d dedicated at least 0.25-0.5% of the fees to facilitating deeper pools? The innovation exemption slowed down stocks pairings due to more regulatory requirements required. Which is why Stonk has performed better since majority of coins are crypto pairings, which are more reflexive/volatile. So the slippage premium comes from your estimation on how well the underlying crypto asset will perform. Comparing to Long xyz, default community mode pools have 0.5% fees. Split into 0.1% for creator, 0.2% into buyback/burn, 0.2-0.4% for LP depth. Really wouldn’t take much to improve Stonks LP’s with a tiny tweak. They’re playing into Sol’s trading environment, however for coins to break through low 8 figs, you need traders willing to blast 6 figs of size with confidence. That’s just not possible with this current structure as larger traders aren’t willing to lose 20%+ on finding entries. We’ve seen how strong sentiment was from AI whales dumping multiple millions in single clips and being instantly bought up while having little effect on the chart. I’m not trying to attack the platform and have been actively trading/holding coins, all they would need is some slight mechanic changes. I can see why it's hard at this stage to restructure their fees as they've been immensely successful already. It's always easier to give an external opinion than to be the one building. Even if Stonk doesn’t want to play the liquidity acquisition game like Long, I think they would highly benefit from deeper pools. There's still a massive moat to bring tokenized stocks to Sol.

After many months of research and consideration, $CODEC is once again my highest conviction trade. My bullishness for robotics never left, however the environment clearly wasn’t favourable and products were still too immature to have a real impact on development. So why the sudden change of mind? What’s so interesting that’s brought me back? Firstly, this wasn’t an overnight decision. Around 3 months ago I was coming back from a trading hiatus, since my read on the market wasn’t great, a protocol I have to better my edge is reading as much non crypto related material as possible. This is my favourite tool in the arsenal to respark my curiosity, which is one of, if not the most valuable trait when becoming interested in your craft again. By reading about non crypto related sectors, it helps open my mind on potential possibilities through breaking a close minded state. You realise how much opportunity, innovation and capital flows through society as a whole. As you can probably guess, one of these topics was related to robotics. In my telegram channel, I spoke about the introduction of World Action Models (WAM) and Egoscale + Scaling Laws. Very quickly I realized how much the space had progressed over just a 6-9 month period. A complete step change had been made across nearly every vertical, many of the theses I had a year ago have arrived and are showing rapid improvement. Since then, it’s been the core narrative sitting in the back of my mind that I haven’t been able to shake. I’ll try to keep the key points short as each of them deserves their own article, which I’ll hopefully write in the near future. 1. World Action Models (WAM) - a new architecture which builds on VLA’s/VLM’s by adding prediction. Instead of only choosing an action, they try to predict how the scene will change after that action. Data collection through teleoperation is largely inefficient, humanized sensors are massively growing and companies adjacent to them. Nvidia defines them as models that predict future world states and actions. DreamZero see’s WAMs as a way to learn physical dynamics and generalize to unseen motions where standard VLAs can struggle. Robotics is moving from task specific policies toward general purpose physical intelligence. 2. EgoScale and Scaling Laws - trained a VLA on 20k hours of action labeled egocentric human video, found a log linear scaling law between human data scale and validation loss, showed that validation loss strongly tracks downstream robot performance and reported a 54% average robot success improvement over no pretraining on a 22 DoF dexterous hand. This has been proof that dexterity can improve with better and more data. 3. In context learning - In context learning lets models learn new tasks from examples instead of by changing weights. This is not the same as permanently learning a skill. The robot changes its behavior while the demonstration is in context, but its model weights are not updated. So in the next session, that skill is gone. Generalist AI’s GEN 1.5 shows that a robot can take a short demo video as a “prompt” and immediately perform the task. In trials on simple tasks, it learned from just one demonstration with no extra training. This proof of concept suggests robot skills can be transferred by demonstration much as GPT learns from text prompts, although this is only for short horizon context, not long tasks. Prompted skills aren’t as good as fine tuned ones. Nevertheless it’s a massive progression. 4. Simulations - They’ll never capture everything that happens in the real world, but what they do give us is access to information that is difficult to get from videos alone such as the exact position of objects, contact points, forces, and robot movements. That makes simulation a useful complement to real world data. Codec (SimArena) can help by providing realistic, calibrated simulations and task setups that match the robot being used. This gives the model more examples to learn from and helps it make better predictions 5. Systems - As tooling, benchmarking, authoring layer, system ID etc become more advanced, robotics slowly becomes a compute problem. Different physical robots and even two nominally identical copies do not behave identically. Simulation tooling can’t accurately correlate between foundation models. System ID is the missing layer and where simulation tooling like Codec will be able to abstract calibrations, giving more confidence for deploying in reality. So what specific tasks am I focused on? - Publicising robotics research and being in the weeds for every new innovation that’s coming out on a daily basis - Positioning Codec’s marketing so it fully captures how the architecture is aligned with industry standards and future bottlenecks - Help @unmoyai put his big brain thoughts onto this app as there’s very few people with his technical knowledge + experience - Simplify and point readers of my page in the right direction, the entire sector has multiplied. There’s so many new sub fields and interesting experiments happening that are often complex and hard to keep track of - Bullposting I’ll address the elephant in the room and explain why I left unannounced previously, which I want to apologise for. With start ups and especially in crypto, small decisions make a massive difference. Everything is about attention to detail and rapid execution. I was extremely hands on with product positioning, marketing, business analysis etc alongside my own bullposting and trading, which was a position I was comfortable to be in, since I’ve scaled multiple companies before. Due to being so hands on, I was very passionate and strong minded on certain decisions, I treated the product like it was my own and even wrote a 30 page product and business analysis on every vertical. At some stage myself and the team had weak communication while trying to move at a high growth start up pace. This eventually led to myself being frustrated as there was too many chefs in the kitchen and conflict from multiple marketing heads. So with this conflict, I silently stepped away as I had too much respect for the @codecopenflow team, @0xdetweiler and everyone else involved behind the scenes who put so much effort in. Looking back, did I handle the situation well? Probably not, but when I become passionate on my work I treat it like life or death. With my departure I gave a list of items which needed to be improved from my perspective regarding processes, operations, positioning and overall structure. I can confidently say these have greatly improved and with my inputs I should be able to help put the icing on the cake. Due to past experiences, I know there will be some people uncertain of my commitment. To help with my transparency towards being dedicated for the long term, you’ll be able to watch my Fomo account. I wished I could have made this post when the price was ranging at 2-3 mil. However this wasn’t a decision I took lightly and I wasn’t risking my reputation, I’ve spent over 2 months going back and forth with the team making sure I understand every vertical to a tea. This wasn’t a decision I was going to make without seeing a clear long term roadmap that matches how I see the robotics industry evolving. As the terminator once said: “I’m back” Codec coded.

Long XYZ vs Stonk Fun I hold bags in both ecosystems and kept this comparison mostly unbiased. Before getting into the technical details, it’s important to consider the backdrop and motion of each platform. Long is the breeding ground of pairing memetic tokens with tokenized stocks, on the largest chain powered by Americas largest degenerate stock trading app. It sits as the flagship launchpad to demonstrate whats possible when you removed walled access from U.S assets (Pons is bundled slop imo). At any moment, Vlad can add 100 mil in mcap to any asset he chooses based off tweets. When looking at revenue numbers for Robinhood, the chain has done 8% vs whole app/company ($33.6M / $430M). Chain vs trading (options + stocks + crypto + event contracts): $33.6M / $256M ≈ 13%. Stonk is the Solana esque reflections platform that has genuine underlying stocks to support its ecosystem, unlike Long thus far. Unfortunately they don’t have a key figure who can easily command 100 mil in mcap from a tweet. What they do have is reflexivity from volume due to higher fees and reflections that can pump metrics to give them better annualized return stats etc. Toly did manage to support the pa and help push it from 130 mil to range highs, obviously his motion can’t compare to Vlad though. Also interesting to see little support Pump have received from the Sol foundation, while they’re fully backing Stonk. Volume is funnelling through Raydium instead of pumpswap for Stonks assets. Quick comparison, 30d revenue Pump is about 3.2–3.7× Stonk. 30d volume Pump is about 1.2–1.7×. Last 7 days Stonk is slightly ahead of Pump’s launchpad revenue ($7.1M vs $6.1M). Asset Structure Most Long pools use Robinhood’s stock tokens as the base asset (NVDA, AAPL, TSLA, etc). Some pools use the $AI meme token or special LongX wrappers). Each Robinhood Stock Token is simply an ERC 20 debt security issued by Robinhood Assets (Jersey) Ltd. It’s backed 1:1 by a share held in custody, with price and dividends reflected onchain via an adjustable multiplier. These tokens give only economic exposure, no actual shares, no votes, no true ownership. The AMM pool literally holds the tokenized wrapper, not a NYSE share. However, Vlad’s recent tweets mentioned in-kind redemption and voting rights are on the way. Stonk creators choose the quote token freely. Common options are xStocks (Backed/Kraken tokens) or PreStocks, among others native crypto pairings. xStocks are SPL tokens on Solana that are each 1:1 collateralized by a real U.S share held by a regulated custodian. Like Robinhood’s tokens, xStocks give only price exposure, holders get no equity votes or dividends on chain. PreStocks are tokens issued by Special Purpose Vehicles holding pre IPO company shares (e.g. OpenAI, Anthropic). Buying a PreStock token buys a proportional share of that SPV, not a seat on the company’s cap table. The AMM pool holds these wrapped tokens (or any chosen crypto/stablecoin), never the underlying share certificates. Launchpad mechanism The main difference is where each launchpad is trying to create compounding liquidity. Long’s launch process is tightly integrated with Robinhood stock pairing. Every new token is directly paired to a stock from day one, for example the $AI token launched into an NVDA pair. Long uses a “dutch auction” style anti sniping mechanism, tokens begin at a high initial price and slide down until fully sold, giving all buyers the same entry price instead of rewarding the fastest snipers. Ticker symbols are reserved 24 hours in advance to prevent front running. Long concentrates new liquidity into its network of stock backed pools. StonkFun is closer to generalized permissionless pairing infrastructure. Tokens can launch against xStocks, pre IPO stocks, currencies, leverage tokens, SOL or custom mints using Raydium LaunchLab, with a conventional constant bonding curve which migrates into a CPMM. The biggest distinction for the thesis is that Long appears to be concentrating liquidity into a connected stock ecosystem, whereas StonkFun is explicitly optimizing for “pair anything with anything.” Fees Long: Fee splits are fixed at launch. By the latest structure (July 27), trades incur roughly 15% total fees (down from ~30%). That breaks down to ~0.1% to the creator, ~0.2% into buybacks/burns, and ~0.2–0.4% left in the LP for depth. The protocol keeps only ~5% of those fees; the other 95% go to the token issuer. (Older V1 pairs had ~1% fee on each side.) In $AI pairs, the 1% effective fee splits as 0.5% to the creator and 0.5% into $AI buybacks. There is no holder reflection tax by default in Long pools (some community mode pools add a tiny auto burn, but it’s not the norm). Stonk: Default launch pools use a 1% trading fee, split 0.50% to the token creator and 0.50% to StonkFun as platform revenue. Creators may optionally pay a 2% fee tier (roughly 1.5% to creator, 0.5% to platform). In its “reward launch” mode, StonkFun adds a permanent transfer tax: holders receive either 1% or 3% of each trade back in the quote asset (an onchain tax), which is funded by the creator’s fee. Essentially, trades incur 1% on the pool plus 1%/3% that flows directly to token holders. These mechanics are built into the launch form and go onchain (e.g. 1% pools split 0.5/0.5 by default). Revenue Long: There is no public fee dashboard for Long. Dune data shows ~$1.27B of trading volume through Long’s stock leg pools (as of mid Sep). At Long’s current fee splits, that implies on the order of $6–8M total fees to date (roughly $1.3M to creators, ~$1.3M into buybacks, ~$3.8M to LP depth under Nate’s V2 mix). Vlad and Nate have only publicly noted that about $3M of $AI has been burned/locked so far. Since Long has no native launchpad token collecting fees, none of this revenue comes back to holders via the protocol. Playing the long game for liquidity acquisition, especially with Vlad pushing in kind redemptions and voting. I can see why people aren’t a fan of them not having a native launchpad token that cycles revenue back to buyback and burns. StonkFun: roughly $10.5M in fees over the last 30 days, with cumulative gross revenue around $11.2M since launch. ~60% of all fees are used to buy and burn STONK and about $5.5M has gone to buyback so far. Easily viewable and forecastable to the naked eye. Roadmap Long is tightening a niche, its innovation is the stock paired format itself. The big idea is that certain pools (like $AI/NVDA) could become so deep that new tokens piggyback on that liquidity, rather than each token needing its own giant LP. Long’s “moat” is the network of tokenized equity pools, success means every launch plugs into that web of stocks. Future roadmap hints (like leveraged wrappers, in-kind redemptions, and voting) all point toward reinforcing that positioning. StonkFun’s moat is breadth and permissionlessness. It’s building a full featured launchpad stack: fixed bonding curves into CPMM pools, arbitrary pairings, standardized creator economics and systematic buybacks (flywheel). The recent Raydium LaunchLab integration dramatically expanded its launch throughput (as shown by spikes in RAY’s volume). StonkFun optimizes how tokens launch (vs what they launch against). Long is trying to optimize the liquidity graph around the primitive. StonkFun is optimizing the launchpad primitive.

My thoughts and favourite Long xyz trades These ideas are taken purely from a narrative and forward looking perspective for each token. $MEME (50 mil) Currently sitting in a weird equilibrium of memetics and catalyst coin. Most traders were positioned for a debrief by Vlad explaining how he views the current environment of tokenized stocks paired with memes. His response was fairly shallow and essentially said “we stand behind stock tokens”. While traders want a more lengthy debrief on the situation, I think Vlad’s done this on purpose to keep some mystery to the marketing so he maintains a sustainable attention roadmap for the eco. Adam (AMC CEO) is still pushing the feud, while he seems on the less intellectual side, my guess is his marketing team is pushing him to continue the back and forth to generate more mindshare for AMC as they’re a dying brick and mortar company. It’s not the first time they’ve been in the lime light and my guess is he’ll continue to ride the attention train for as long as Vlad will let him. They know the power that reddit type personas hold when cult like communities form around its asset. While I’m not trying to be a conspiracist on this trade idea, the most logical conclusion I can see is Adam continually poking the bear to increase mindshare. Vlad’s already followed and directly engaged more than any other asset, I do think he wants to make an example out of this, however he’s shown he lets the market decide winners and he gives it the stamp of approval. In no case has it been profitable to try and front run hints other than Cashcats initial leg down for the listing. Personally a stale trade which will resolve in the coming week as Vlad is forced into some type of debate against Adam. I can see the bull case for how it could become the flagship token for reviving brick and mortar stocks, at this stage it feels too much of a coin flip. $BONER (33 mil) My favourite token on the list and what I see as the purest expression of the Long thesis besides AI. Memetic wise its fitting for your average young male crypto stereotype. Why I see this as the purest trade is it’s the first case that’s combined genuine memetic appetite while fitting the criteria for being an attention play on its underlying stock. Out of all the current coins it feels the most organic and I haven’t heard anyone say they dislike Boner (pause). My main concerns is that its 1) a bit too much of a resemblance to fartcoin even though it does have some pretty unique variables and 2) it’s a little bit vulgar compared to the other main runners we’ve seen. Something that’s important to consider with memetics is how included can everyone be? Can you show a kid and they’ll smile? Can you show your gf and she thinks it’s funny? Simple variables which I think are quite important when determining big runners. Something I wonder is if having a stock like HIMs worth 6B, is that a positive or a negative? Say the coin is able to trade to 500 mil, is that price then capped because its reaching too close to the stocks valuation? Would traders then assume its time to move onto something else because why would a meme get close to the valuation of the stock, or is it the opposite where they believe in flipping the stock/short squeezing it. If you took away the HIMs CEO follow i don’t think price would be very different to where it is now, which is a more bullish case as traders are treating it as an attention/catalyst trade, once it starts climbing due to its own memetics i think its pa becomes reflexive. Any interactions are a bonus. I personally have a small bag from these levels, although I am of the belief that patience will be rewarded over the coming days/week and we’ll get attractive entries as we conclude a flush out across onchain. I’d be interested to size this trade at 15-25 mil if we get it. $MOO (18 mil) This one caught me off guard never made a ton of sense in the early days. The mindshare and the cult like community that’s formed around it is hard to ignore. Moo pools are paired with tokenized memory stocks, the most recent catalyst in stocks with the AI trade. The grand vision is growing these pools like SKHYNIX, MU, SNDK (DRAM) etc to be the acquisition layer via the MOO token. Equity traders will eventually come onchain and buying Moo is a by product of the demand through the routing. Essentially creating a non liquidatable leverage long position on the idea of memory traders being onboarded to RH chain. What started out as a degen narrative eventually plans to evolve as the coordination layer for memory assets. I get the narrative and think it’s quite cool. It’s very dependant on your view of where you see the memory market going over the coming months with OpenAI and Anthropic IPO. I’m not deep in the memory weeds so my opinion feels shallow, first reaction is that memory is priced in and there’s not a ton of asymmetry other than being a foundational component to AI, the same way NVDA is the GPU LLM stock. If Long continues to succeed I don’t see why this token wouldn’t act as beta considering mindshare. Although it’s not my type of trade since I don’t have a read on the memory market. $STRATEGY / $SAYLORMOON (5 mil/1 mil) I do think one of these coins has a good chance of performing, depending on how active the team is and their marketing. Quite reliant on BTC strength and/or Saylor gaining attention. We’ve seen many variations of these coins with Sol pairings but none successful or under the Long/RH umbrella. Left curve rational is RH chain is for crypto, degens on their app are getting access to crypto, BTC is the face of crypto, MSTR is the face of BTC, eventually one of the BTC/MSTR pairs runs with strong enough narrative. You’re banking on fees collecting ultra sound immutable BTC dollars to funnel the vault with the hardest asset on earth. If I had to compare it to something it would be brc20 NFTs, they sound really good in theory but how much genuine demand will there be? Biggest catalyst is if we break 82k on BTC, then I’d be much more interested as a leverage play when the bull market resumes. Saylormoon was the initial BTC pairing, however it feels a little niche and memetics aren’t the best imo. Strategy have a pretty cult community behind them and also a nice marketing flywheel with optics. $iNu / $ICOIN (3 mil/2 mil) When I first saw icoin I liked it but didn’t overthink it too much. Then I saw some posts which gave me higher conviction. Apple is the highest regarded brand in the world. Most of us have more screen time on our phones higher than any other activity we participate in, including sleeping. iPhones dominate the world, the user satisfaction and branding they’ve been able to maintain is stronger than any other product. Which makes the thesis for icoin/iNu interesting since you’re banking on the idea that icoin/iNu is the cleanest representation of a coin possible. Issues I see with the coins is there’s no real catalyst other than pure memetics. Apple CEO isn’t going to interact, Apple stock isn’t going to have a crazy enough run to generate high mindshare. Since the main thesis evolves around clean branding of Apple’s products, I prefer icoin over iNu since iNu feels like it’s trying to be both a AI derivative and leverage the apple branding. If a token is going to purely leverage branding with no catalysts, I’m interested in the most pure variation of that. Maybe I’m wrong and it’s not my highest conviction idea, although that’s how I view these coins in their current state. Feel free to shill your thesis for these coins or ones I’ve missed in the comments. I’m genuinely interested in narratives I might be missing and actively looking for the best representations of Long’s eco.

Long xyz is the ai16z of this meta. Their goal: “make billion dollar runners” - @Natan_benish The same way that ai16z was home turf for the best developer tooling to build AI agents, Long xyz is home turf to the best liquidity sources for tokenized assets. Tokenized stocks liquidity flywheel = AI agents plugin/integration flywheel Eliza gave developers a shared runtime where actions, providers, evaluators, memory, social clients and onchain tooling could all be plugged into the same agent. Every new integration made the framework more useful for the next developer, which made the next agent easier to build. What makes Long’s launchpad different is the pre bond (dutch auction) launch mechanic. A mechanism from the NFT days where price moves down during the auction to reduce how much of an advantage snipers get at launch. Although with the recent changes, what happens after launch is the more interesting part. Fees from volume can be routed into a vault accumulating the underlying RWA, while fees can also systematically grow LP and mechanically reduce supply. Volume isn’t purely extractive, every trade can incrementally strengthen the market structure of the token itself. Which is a very different design philosophy from most launchpads since success creates fees for the platform but doesn’t necessarily create a stronger token. For a launchpad to succeed beyond more than its narrative, it needs genuinely interesting tokens which can stand on their own narrative/memetics/utility. This is why you’ll see a thousand copy cats once the originator takes off and starts a new meta. Launchpad vamps can be convincing and shiny object syndrome makes it difficult to distinguish whether an emerging eco is genuinely coming for the throne or just another short lived rotation. The easiest way to distinguish a meta from a rotation is breadth. One token running can be reflexivity. Multiple unrelated tokens sustaining volume, holders and liquidity is when you start getting evidence that the underlying rails themselves have PMF. This was also part of what separated ai16z. Eliza wasn’t dependent on a single agent use case, the same runtime could power agents that interact, query external data, retain memory, execute onchain etc. Earlier in the week Nate hinted at enhancing the depth of all assets across the platform: nitter.net/Natan_benish/status/20… Assuming there’s some type of stocks -> AI -> NVDA routing, you’re effectively creating a liquidity graph where child markets can share a common intermediary instead of every pair needing to support completely isolated depth. This matters as liquidity fragmentation is one of the biggest problems once you move from trench sized positions into actual size. Early on you care about asymmetric entry and incentives. Later on you care whether you can put 6-7 figs through a route without nuking yourself on price impact. This is also why Nate’s point around $AI and eventually the wider eco becoming highly liquid matters more than just having another token run. Liquidity itself becomes the product. You get a positive double edged sword as new pairs are incentivised with anti snipe dutch auction mechanics that provide greater bootstrapping, while fee derived rewards are more meaningful to early holders. As tokens reach maturity with larger mcaps, traders aren’t necessarily looking for reflections but deeper liquidity as they believe the narrative is worth sizing into. So the incentive curve changes with the life cycle of the token. Appealing to a multitude of trading strategies is important as when comparing to Pump’s bonding curve, it highly benefits deployers and those playing in the sub 1 mil range which is why we see a lot of 1-5 mil toppers as fees drop off significantly. Both Long and Robinhood are aligned with these incentive mechanisms as more successful runners creates deeper liquidity for future Long tokens. While Robinhood’s chain has overall higher TVL, opening the gates for more complicated DeFi, Agent, dividend etc strategies due to excess idle capital. Speculation is effectively being used as the liquidity acquisition layer for tokenized equities. Memecoins bring attention + volume -> volume creates fees -> fees reinforce liquidity -> better liquidity allows larger traders to participate -> larger markets make the underlying rails more attractive for the next launch -> accumulated tokenized equities produce new trading strategies ai16z commoditized agent creation while letting the agents manufacture their own distribution. Long is trying to commoditize token creation while letting the tokens manufacture their own liquidity.

The writing is on the wall for what the dominant meta will be in the upcoming bull. So much so that even with the slightest signs of corrections, launchpads like $STONK and underlying tokens are flying on opposing chains. This is by far the closest euphoria we’ve seen in comparison to AI szn. While it feels late, I think we’re still late early considering Vlad only just followed $AMC and the HIM’s CEO followed $BONER. We’ve only had one Robinhood listing for $PONS thus far which was done quite late into the pump. We’re yet to see many strong endorsements from Vlad and traders are pricing the eco significantly high due to how he’s handled the attention roadmap. Sol’s biggest issue is it doesn’t have a native exchange which can be used as a catalyst. Remove the possibility of being listed on the Robinhood app and I can guarantee these coins would be multiples lower. We’ve been cynical for a liquidity catalyst that brings external capital like we do every bear market. Now we’ve finally found one and it’s such a strong moat that volume across social trading platforms had its highest week since Trump coin. I was expecting more input from Vlad to carry the momentum but traders have been so starved of a quality leader that they’re willing to place all their eggs in one basket with the meme x tokenized stock barbell. Coins like $AMC and $BONER are going to be flagships for how dying or new gen companies can be saved with memetics if the CEO co operates or drives some form of attention to them. The easiest way to understand this is reverse engineer yourself as a CEO of a brick and mortar company. Revenues declining, sales are decline, customer acquisition is low, marketing is declining, AI is stealing marketshare. You see Vlad doing numbers with the Robinhood chain that took his exchange years to reach in a matter of weeks. Stocks like AMC and HIMs are in the limelight because they decided to spend 5 seconds interacting with a memecoin, with the potential to bring a new cultural movement for their products. How many contacts in tradfi like the HIM’s CEO do you think Vlad has access to? Do you think he’d be able to convince other public CEO’s to support memecoins adjacent to their stock if he can show previous results that its improved mindshare, volume and price? Public CEO’s engaging with memes is by far the most asymmetric chance of external capital entering our space. Hyperliquid has been the best performing asset as it’s been able to leverage decentralized trading for tradfi which is where we know all the capital is sitting. This is a direct correlation to the liquidity we’ve been trying to siphon from stocks to onchain with the help of the biggest stock trading degeneracy app in the world. You can’t make a more perfect storm. The Hims marketcap is $6B. Amc is $2B. For reference that’s #20 and #45 respectively when comparing against the highest crypto mcaps. Crypto participants deeply underestimate how much capital and social influence they control over markets. We’ve tried this idea before with ICM but we didn’t have the tail winds of a leader like RH or tokenized stocks being embedded into our infra. 2021 was NFTs (culture, artists, small funds) 2023 was memecoins (TikTok, rich natives, zoomers) 2024 was AI szn (power users of frontier models, low level devs, mostly native capital) 2026 is memefied stocks (public CEO’s of the largest companies in the world being KOLs and bringing external capital + attention) We’ve never seen such a perfected attention roadmap by a new upcoming chain, no leaks in any vertical of the business. Everytime we get some form of fud or uncertainty he steps in at the perfect time to stop coins/volume from going stale. There’s no interns mis firing on tweets, no core team members being hacked, no desperation or direct marketing, Vlad is simply S tier. If you’re in Solana’s position, this is quite scary to watch.

How does Robinhood rival Solana? As RWA trading on RH breaks $100m in daily volume, this is the first time since Launchcoin that there’s been a new eco which offers a fresh alternative. A new mechanism - pairing tokens with RWAs/stocks as their underlying value accrual mechanism. No one has had the network effect to take capital from Sol due to their imbedded routes with the speculative hot ball of money that moves from narrative to narrative. The arrival of Robinhood chain is what’s enabled an unlock, onchain experiments now have a parent figure that can supercharge productive capital with the highest growth and attention assets (tokenized stocks x memetic pairings). Launchcoin failed due to Pasternak showing no appreciation for genuine teams building or congruent narratives, if the team isn’t willing to foster a high growth eco and interact with passion, it’ll show rather fast. So far we’ve gone through wave one which was the sudden outburst of cashcat, it’s 85% drawdown, listing and return to ATHs. Currently we’re coming towards the end of the second wave where everyone has almost fully priced in the next listing being a utility coin like I discussed in my last post. Something I haven’t seen discussed is the isolated moat of the RH app. All the other chains have essentially converged on a trading ecosystem which has been integrated with Fomo, Pump, GmGn, Axiom etc. The RH app will be a unique venue that no other coins or projects have access to other than native coins. I don’t think enabling the catalyst of the app would be the best use of it just yet. Once this wave two dies off/if we get a utility listing in the coming week or so, I think it would be better ROI from their end to spend the next month facilitating a more hands on environment. The way they’ve kept interactions subtle and hints from Vlad on podcasts etc has been S tier in terms of playing into a slow drip attention roadmap. However the next stage would require substantial more effort and contribution from the core team to maintain this level of momentum and enticed users. As we know, rotations are rampant and Sol has been performing equally as well with Ansem returning close to ATHs and Pump going on a heater. The fact we have both eco’s rivalling each other so closely is perfect for traders, as we can play rotations and have more say in how the environment evolves, since if one team isn’t willing to listen we can easily jump to a more favourable playground. RH can steal Sol’s lunch as Sol was always seen as the onchain nasdaq. Sol’s adversaries main platform is the retail driven nasdaq and doing several times the numbers with U.S KYC’d users compared to Base. It is hard seeing attention move away from Sol due to the trading infra and level of volume that still maintains on new pairs, despite it being such an efficient game, RH can fight on different levels though. @0xTojo described a phenomenon which I highly agree with and voiced before. RWA’s themselves aren’t sexy or overly interesting if you’re trying to capitalise on attention economics with how fast internet culture moves. The combination of pairing memes (culture) with serious assets (stocks) merits a type of relationship where cultural assets can now have direct economic impact with productive ones. Something we’ve yet to truly see. This feels semi comparable and less exciting to the agent trade, where agents were being funded to go across the web and find ways to become more productive with capital in their own wallets. Since these assets now turn productive, there’s addition capital which can be used to monetize experiments or incentivise human/agent contribution based on speculative outlooks (memes performing well in beta to Sol pairing etc). At the same time I’m the first to point out this is ponzinomics at the end of the day, in the early innings, money flows in, experiments go down the risk curve and we end in shambles like usual. However that’s why we show up to play these games as coins like $AI made genny wealth for many (I fumbled it unfortunately). “DeFi summer came and went, programmable finance remained. The AI agent trade came and went, but software being able to hold a wallet and act economically remained interesting. Memecoin mania will eventually come and go, but culture becoming instantly liquid isn’t going away. RWA’s might stop being a narrative one day, but the world’s assets being internet native will remain.” - Tojo Robinhood still has the luxury of agentic trading, options, prediction markets and dividends which are fully untapped and no team has gained substantial traction thus far. Plenty of bullets still in the chamber.

Right thesis, wrong timing. $CASHCAT has crossed some very important catalysts for the Robinhood eco to prove it has staying power. Primarily, it survived a -85% drawdown while getting a listing from the team in a reasonably short time span. I previously spoke about the game theory of listing the coin and dealing with the issue of fnf’s dump millions onto new retail, which removes the biggest catalyst. Or wait to list the coin, onchain volume dies off, onchain no longer has faith in the team and when they eventually come back around they’ll be Base 2.0. Essentially played out as expected where they lightly teased the token without giving too much clues for the listing. Given how aggressive the rotations were from eco to eco pre BTC pumping, my guess is they had to list it sooner than they wanted to as DEX volumed dropped 60-70% from the highs, which is important for them to maintain investor and builder interest. Going forward, we can take hints at face value as mentions of Cashcat were consistently dropped and also added onto their balance sheet. Which merits well for other eco plays, especially utility tokens as they’ve been mostly untapped thus far and make a lot of sense with how RH’s stock offerings are platformed. So far the leading utility plays are: $PONS - launchpad + trading frontend built on Uniswap V3/V4 $AI - first mover of Long xyz launchpad which ties stocks as the native token pairing $STONKBROKER - ecosystem utility play that loops rewards back to NFT holders as the core contributors $INDEX - stock dividend memecoin/ponzi Pons feels unlikely for listing as its a generic launchpad and Uniswap frontend DEX, the reason for listing would probably be to incentive platforms to generate volume = revenue for their chain. Stonkbroker feels like it has too many moving parts and failure points, also most of the benefits go to NFT holders, I’d imagine tokens would bring more economic value and attraction for new users. Index is interesting from a novelty perspective as it’s been mentioned by Vlad multiple times and something that never crossed his mind as possible, important to note as they were vocal about Cashcat before listing. The token takes a 3% trading fee which is automatically airdropped to holders which seems fairly easily to integrate on their app. The issue here is the low volume and minimal fees they’ve generated for holders. AI and Long xyz was the more complex asset for listing as you previously had to claim through the website, but that’s now changed where 50% of fees to to burning AI and the other 50% go to the community pool. What’s interesting is the recent Long xyz partnership with Lighter to bring leveraged tokenized assets onchain, Lighter was invested and advised by Vlad. While they were first movers, it’s fairly reliant on stocks performing well akin to Index to maintain mindshare. However the narrative of stocks or alternative assets being the primary pairing feels like the perfect narrative for RH’s tokenized stocks movement. Having a utility play listed on the exchange seems far more likely compared to another meme, as they wouldn’t want to vamp Cashcat and bringing volume to tokenized stock mechanisms or novel experiments bodes far better than being another meme chain, Sol already has that pie. It’s clear they’re willing to list assets at the right time, minus a few points from the team for how front ran Cashcat was. You’d imagine second time round they get it right as it was a very unprofessional look on their part. RH genuinely feels like the only other eco to Sol which can sit at #2 and potentially rival Sol for the throne if we do bottom on BTC here, which is looking more and more likely. If so then I’m expecting Cashcat to march far higher, RH to list one/multiple utility plays as they’ve seen the effect of doing so with Cashcat, especially going into a trending market and building out the necessary infra for traders and devs to be one of the more vibrant eco’s this bull.

Robinhood is what Base was meant to be. This alone is what’s keeping me so bullish on the $CASHCAT trade. The bear market has forced everyone into excessive risk management and losing the ability to fire on narratives which could be break out trades. Which is why $ANSEM has performed so well as consensus turned to people believing there would be no more mid 9+ fig runners in memes. Now that it’s happened once, the genie is out of the bottle. A couple hints from CZ alone nearly sent a coin to 9 figs. Even still, with the amount of failures in L1's and new chains attempting to vamp attention and liquidity, it’s potentially even worse than the death of memecoin narrative. We’re seeing DEX volume within striking distance of Sol within it’s first week while having minimal comms from the team or Vlad. Again, not trying to blindside you with my bullishness. These are just the main factors where I see a discrepancy between perception and reality for traders. If the RH team go silent and stop endorsing etc then obviously Cashcat will have a short life span. Based on the support and hints so far I think it’s fair to say they’re probabilistically not going to let this die. The CFO has Cashcat in his bio… Does it get a listing? What are the best circumstances for them to list where both onchain wins and their users buying into the coin at the listing price? Initially when I bought, I thought listing was relatively priced in, but after further consideration it seems more of a 50/50 consensus between traders and also varying timelines. You’ve essentially got the chicken and the egg problem. List the coin now, fnf’s dump millions onto new retail, removes the biggest catalyst. Or wait to list the coin, onchain volume dies off, onchain no longer has faith in the team and when they eventually come back around they’ll be Base 2.0. If I was in there position, I’d continue to lightly endorse which keeps the chart stable or gradually increases price to help metrics and steal mindshare from Sol. After 1-2 weeks, list the coin, you now have a tribal community who will be loyal to your chain. The game theory then becomes speculation on what coins will be listed next keeping the hot ball of money from exiting. Continue showing support for Cashcat to ensure the runner doesn’t die while provoking other memes but not to a point of saturation. Develop RWA’s, Agentic trading or whatever underlying fundamental narrative they see pushing their business over the next 5 years. You now have beefed out onchain metrics, revenue, mindshare and ability to pivot with a user base willing to listen to you. This is all theoretical and what I would assume to be common sense as someone who’s been in this space for several years. It’s interesting to see their focus on Agentic trading and what angles they might push with that. Everyone throws around the idea of RWA’s like it’s some obvious untapped gold mine that we just don’t have access to yet, but is it? You could argue NFT’s were a premise to RWA’s and collectibles. Turns out no body wanted their Rolex or diamonds reincarnated as a txn hash. I do think crypto is the end game for finance over the next few decades, however from a business moat, Agentic trading will drive far more volume to their platform, causing revenue to sky rocket. Instead of depending on human labour to take trades, you’ll have users in the future with dozens of models (agents) set with pre defined conditions to take trades. Thus driving significantly more volume via automation. Maybe their end goal is to build such a diverse blockchain that facilitates transparent data on anything from onchain stocks to private inference marketplaces that Agentic trading can thrive from all the possible backtesting and inputs? That’s the most logical conclusion I can create for now.

Rumblings of AI szn 2.0 are starting to emerge. Two coins with the highest potential: $RALPH A looping agent that repeatedly runs the model until a task is successfully completed. It feeds Claude’s full output, including errors and test results back into a fresh prompt each iteration. Using a brute force loop continues until a defined success condition is met. Unlike complex orchestrators, Ralph is intentionally simple, it uses bash scripts or wrappers to relaunch Claude with updated context each time. This avoids prompt degradation and token overflow by resetting the context window per loop. It excels at automating error prone tasks like debugging, test driven development and recursive code refinement, especially when the goal is clear and human oversight is minimal. Ralph’s like a quant that loops through iterations until it reaches a specific outcome. It excels at tasks where the goal is deterministic and testable, such as building trading strategies, fixing bugs or refining outputs until a pass condition is met. The strength lies in persistence, not planning. Meaning it’s better suited to more experienced developers as you’ll need to have your requirements doc very well thought out. The roadmap is building loom which is essentially a swarm style framework that just multiples it's loops. @GeoffreyHuntley started building pieces of this future stack (custom source control, sandboxed execution environments, telemetry feedback loops etc) to enable AI weaver agents to not only write code in loops but also coordinate, deploy and self correct on a larger scale. This would be the end goal and northern star for agents to reach as it combines persistence with orchestration. This represents the north star for autonomous agents: combining Ralph’s brute force persistence with multi agent orchestration, unlocking full cycle AI development with minimal human oversight. $GSD What makes GSD (Get Shit Done) special is its structured validation loop, no plan is executed until a verifier agent confirms it's complete and sound. If a task fails to meet the goal, GSD automatically invokes debugger and planner agents to diagnose and fix the issue, repeating this loop until it passes. This persistence mirrors the Ralph Wiggum “loop until success” model, but with a more disciplined architecture. Unlike Ralph, which relies on long prompt chains that can run into context window limits, GSD isolates each task into a fresh Claude context, reducing token bloat and avoiding prompt degradation. While Gas Town uses complex multi agent orchestration, based off a Kubernetes approach, GSD finds a middle ground, coordinating small, validated agent loops that build toward large outcomes without overwhelming infrastructure. It prioritizes clean context reuse, structured planning and token efficient execution while maintaining user control at each phase. Which is why I like GSD and @official_taches so much. As it works with you in the planning stage to carefully set your requirements and ends up providing a much more accurate result. I really like Ralph as a concept and it opens peoples minds to the possibility of agents which can run fully autonomously. However, if I’m being specific with my code base and requirements doc, GSD acts more like a senior engineer. Asking all the right questions, making sure there’s logic and cohesion in the code and what databases you’re connected to etc. Throughout the build, it’ll come back to check in, ensuring the current outputs are correct and the system is being built as intended. If I’m a developer or trying to build something with unique customization, this is a massive positive for me. Both tools are great and are a breath of fresh air. This is the most interesting development we’ve had in a long time. Many are missing the forest for the trees and I’d be paying much more attention if you’re tapped out. The fact we've got multiple viral dev frameworks to convert over to crypto is really good signs that innovation will be rewarded and the meta continued with the right aptitude towards building. Covered both of these tokens at 2 mil mcap in my telegram. However I think they go much higher and we’re on the cusp of a large move.

Why does Robotics need a token? The short (traders) answer: speculation. Take ai16z for example. Never even had token utility and it became the most used product because of the depth and plugins of its Eliza toolkit. I believe token utility isn't as important as building infra which is actually usable by outside devs. Eliza was the most used github repo at one point and had devs from all industries coming to test it. This should be the goal for anyone building in both AI and robotics. Speculation drove mania -> volatility due to the belief of future utility and demonstrated how impactful it is as a fundamental. Profitable traders understand the asymmetric value of this. We know token utility is beneficial, especially in the right circumstances though. Virtuals took a more crypto native flywheel approach to the launchpad framework, attaching all forms of commerce and distribution to their token. Virtuals and ai16z topped at $3 bil and $2.6 bil mcaps respectively. One housed the strongest flywheel we’ve seen since DeFi szn and the other a global framework which proved far more successful regarding developer usage and majority of teams building on Virtuals tooling eventually had to move over because they were being restricted so much. It is interesting watching $VIRTUAL lead the way for robotics atm, taking a standardized approach to incentivising data provisioning + funding new start ups. They introduced Unicorn, which is their new launchpad model. Replacing Virtuals older points system with direct token stakes and rewards. They’ve gone back to a more traditional launchpad route where each new Unicorn startup (a robotics project on Virtuals) starts at a low valuation and acts more like a bonding curve. The founding team’s funding is vested and only unlocked as the project grows, forcing builders to deliver results. They also launched SeeSaw, crowdsourcing rich spatial datasets (humans recording first person videos of tasks so robots can learn from real world experiences. Packaged as a fun mobile app that crowdsources human interaction videos to train AI and robot agents. This “middle way” focuses on cloud data infrastructure and funding. There’s no question that high quality real world data is crucial for embodied AI. Especially in the foundational phase, robotics benefits from large volumes of varied environmental input. Data like this is the fuel early models need to learn and generalize. Virtual's approach helps bootstrap this layer effectively and has its place in setting the floor for capabilities. But over time, this value plateaus. As more data protocols emerge, the volume of available real world data increases, while the number of end users who can meaningfully absorb and use this data doesn’t scale linearly. Which means the returns become more concentrated, mostly benefiting teams building large foundational models. These models will still matter and be profitable, but the edge starts to shift elsewhere. What starts to matter more is giving users the ability to collect and use their own custom data. Custom data pipelines are where I see more value accruing, tools that allow a store owner, a warehouse team, or a household to quickly gather and fine tune robots to their specific environments. That kind of data won’t be bundled in any dataset marketplace. As we’ve seen with LLM’s, most users don’t care about the training rituals behind GPT. They care about how to feed it their own docs. The long term opportunity is in making that collection and integration loop simple. While Virtuals is going for data (fuel for AI models) and a marketplace to fund and share in robot ventures, I believe the biggest impact will come from those who remove the most abstractions from complexities of robotics development. Hardware, software and data need a unified toolkit which gives individual devs a chance to experiment without needing to build a custom framework, which is what sparked AI szn this time last year. Data is important and real world data is significantly more important for robotics than AI, especially in the early innings to set the foundations. But I don’t believe this is where the biggest value layer occurs in the long term. What we need is better abstraction of tooling, giving developers faster iteration loops going from A -> B. Data is only one of the inputs in a very large hardware and software stack. Robotics is far too deep of a sector to throw a crypto incentive layer over and needs to be looked at from a holistic view. Data -> Perception -> Planning & Reasoning -> Control & Actuation -> Feedback Integration. Due to this depth, there won’t be any single crypto company which will build a monolithic stack covering each of these areas (full stack humanoid for example), if they were they would have raised 8/9 figs in web2 and wouldn’t bother with crypto. The most impactful token utility will come from supporting tooling that gives devs incentives to grow out an open source library of new plugins/attachments with flexibility. Something which rewards devs for contributing mapping software for specific motors, sensors, cameras etc, alongside leading foundational models that then plugs in to any robot. On top of this, whoever builds the most successful task marketplace will be akin to unlocking custom games on Roblox or Fortnite. Humanoids are still like toddlers, they need to be taught (tasks) which improve their feedback to environmental scenarios, slowly turning them into functioning adults. This won’t be possible without global coordination as there isn’t large amounts of quality real world data yet, and more importantly, tooling which can help abstract this entire iteration flow. Which is why I’m so bullish on $CODEC as it’s essentially creating a new robotics middleware from scratch, whereas Virtuals leverages existing AI models and focuses on aggregating resources around them. Codec’s architecture might enable faster iteration on actual robot tasks (since it provides a framework to quickly deploy and share new behaviors), whereas Virtuals architecture aims to accelerate the inputs and support for those tasks (data + funding). The core idea is to replace fragile, hard coded automation scripts with adaptive AI “Operators” which are very aligned with leading VLA architecture from companies like Deepmind etc. Finding a way to attach token utility (incentives for mapping and abstraction of iteration loops) is where we’ll see the biggest impact. The majority of robotic foundation models are already going open source and this isn’t a decentralized crypto pipe dream psyop we try to spin on other narratives. Hardest and most important part is acquiring real users/devs, then you add the flywheel on top to supercharge the ecosystem. Imagine if ai16z had Virtuals flywheel.

The fact we’ve speed ran the axiom trading style into the ground is +EV for the space. To bring life back onchain, we need runners and success stories. The only way you get this is by traders dumping at typical resistance levels and the coins never give another pullback, going vertical in a straight line. You only win if you’re a believer. Opposingly, everyone’s trading style has been based on wallet tracking and volume the past 12-18 months, other than AI szn and ICM (utility). I spend a lot of time pondering where onchain might be heading but feel I’ve never really gave it deep concise thought. While I’ve given many macro ideologies of how ICM might evolve, they felt more broad in concept. Tbh I think you could consider onchain and alts to have been in a bear market since Trump coin. OTHERS chart confirms this for the first 7 months going from January to July with a -50% drawdown, while we did have decent performance from July to November, it still doesn’t really feel like we’ve had any form of consistent narratives due to rotations. Even in the 22/23 bear market, we’d still get multi week narratives which were typically a safe buy and hold for several days. The axiom trading style has speed ran this into the ground as deployers squeezed every bit of juice out from multi walleting new launches. There’s clearly demand for fundamental assets, look at the stock market. What’s killing onchain and crypto traders is the fact we’ve entered some of the strongest liquidity injections seen since covid stimulus. But our “digital hedges” have basically been flat or down when looking at the BTC/SPX chart for the past 160 days and OTHERS/SPX for 270 days. Crypto has always been the most positively skewed sector to new liquidity injections, which is a strong reason we haven’t seen any traders be consistently right over the past year as we’ve never really traded in this type of environment. So what do we need for onchain and alts to revive? @goodalexander had a really interesting “conspiracy” on his recent @notthreadguy stream which I ascribe to. Tldr: inflations spinning out of control, only way to stop government debt is buying treasuries to offset the constant printing. Who are some of the biggest treasury holders? Stablecoins. Stablecoins need to be backed 1:1 in collateral with treasuries. So by increasing stablecoin adoption you can potentially offset inflation through holding treasuries as collateral. How do you increase stablecoin adoption? Onchain stocks. If you go deeper into the bills they’ve been submitting, they’re heavily inclined to set up legal frameworks for stocks to live and trade onchain. As more stocks come onchain, their value needs to be pegged to traditional markets, meaning that more liquidity (stablecoins) needs to become available, thus doing more treasury buybacks. Right now there’s something like 28 billion a quarter in stablecoin growth and we need to be doing 83 billion per quarter (almost 4x) to hit the deficit target to reduce inflation. People holding their assets in stocks offchain doesn’t give any value to the government when trying to offset debt. Rather than increase taxes, they want to turn capital markets into a casino (speculation on crypto rails = more stablecoin demand = funding the debt deficit). That’s the macro picture. I’m not saying this will be right and goodalexander has been wrong before, although I think it’s a very well thought out thesis where there’s a lot of evidence pointing to this being the direction it plays out in. So say we get this grand idea of onchain stocks increasing heavily from stablecoin adoption, then we can almost see crypto acting as a pre market to stock “IPO’s” and companies joining S&P 500 etc. This is where the ICM thesis comes in for real businesses/products coming onchain. There’s going to be extreme incentivization for businesses to start onchain and I believe we’ll eventually not only see stocks coming onchain but crypto projects turning to stocks (being available for boomers to buy). This will be the ultimate speculative bridge which looks to be the Trump’s multi year game plan based on legalisation bills. Memecoins will always exist in some format (you could argue polymarket predictions are a form of memecoin), although the stock market has existed for hundreds of years. If you’re betting on speculative future outcomes, it’s quite safe to bet on the idea of stocks and businesses coming onchain instead of betting on attention (memecoins and derivatives) to revive our industry. Which all loops back to my original idea of why it’s good axiom style trading gets washed out. If we’re to see a return to utility and fundamentals coming onchain, wallet tracking will have its perks although it’s not going to be where the bulk of the money is made. Everyone knows there chances of beating new deployers is second to none. Well formulated theses and multi week/month time horizons on industry shifts (conviction) will once again return to the throne as the highest +EV trading style. It’s already proven itself with stocks. Now we’re expecting speculation to shift from tradfi and stocks to crypto as the ultimate rail to offset inflation. If true, then you value trades like Hyperliquids HIP3 very highly.

Robotics szn is here. These largest raises in web2 and software which has the most likely carry over for crypto speculation. @Figure_robot - $1 billion Figure is building full stack humanoids, powered by their control software platform called Helix. Their focus is towards scaling production and doubling down on the Helix AI platform and simulation infrastructure that gives the robot its brain. @AppliedInt - $600 million Applied Intuition provides a software platform for developing, testing and deploying autonomous systems. Investor interest is from its autonomous vehicle and robotics simulation technology. Applied’s tools help engineers simulate and validate self driving cars, trucks and other “moving machines” and the company has expanded into defense applications as well. Also with a goal on to scale any defense use case requiring at scale simulation and validation of robot/autonomous fleet behavior. @SkildAI - $500 million Skild is developing a “Skild Brain” which is a general purpose AI model designed to control a wide range of robots with a single system. The platform has been shown working across humanoid robots, quadrupeds (robot dogs) and robotic arms on tasks such as dishwashing to climbing stairs. Their focus is on providing a unified AI “brain” for any robotic form factor. @physical_int - $400 million Phyiscal Intelligence (π0) is building a universal “robotic brain”, foundational software that can run on any robot, removing the need to write task specific code. It’s AI platform has been demonstrated on household tasks like folding laundry, bagging groceries and retrieving toast from a toaster. Personally this is the one I find most interesting on the list and where I see the most mindshare accruing to general purpose service robots. @shieldaitech - $240 million Shield AI is a defense technology company focusing on AI software for robotic aircraft and drones. It’s “Hivemind” software enables military drones and even fighter jets to fly autonomously in high threat combat environments. They develop some hardware while their core IP is the autonomy software, where they’re scaling defense OEMs and primarily have government customers. Takeaways: All these high profile robotics startups share a software focused “brain” architecture and a broad value proposition. Rather than building single purpose machines, they focus on universal AI control platforms, essentially foundation models or operating systems for robots. A common technical approach is heavy use of simulation, large scale AI training and continuous learning loops. These platforms train their models on simulated scenarios and human demonstration videos, then fine tune on real world robot data, creating a “shared brain” that improves as more units are deployed. Which is aiming to solve the data scarcity in robotics by aggregating experience from every robot into the central model. Figure’s Helix and others invest in massive simulation infrastructure and GPU compute to accelerate learning and testing in virtual environments. By decoupling intelligent control from specific hardware, these companies can target multiple verticals with one platform, much like what my favorite crypto robotics project is doing. New capabilities learned in one context can quickly transfer to robots in another industry, accelerating deployment of features across different industries without starting from scratch. Everyone’s racing towards general purpose robots. The hardware and mechanics itself are advanced to the point where the software or “AI brain” is the main component missing from turning these metal toddlers into fully efficient adults that enter the workforce. The real value is in how we reach that point. Where the opportunity for vertical integration across specific robotics applications will generate the most leverage imo.

What I’ve been working on this past month with the $CODEC team: - Researching the entire Robotics sector and technical architecture from a birds eye perspective with @unmoyai (latest developments, best practices etc) - Understanding where and how Codec’s product positions in every single one of them (addressing the pain points) - What specific use cases and narratives this unlocks - The biggest value layer for the tooling and where major capital is flowing - Comparing web2 tooling and what led to the success of AI szn (Virtuals & ai16z) - what are the core components to spark developer activity? - Tokenomic flywheels and utility The team has done a great job with technical articles, although I still believe they’re only brushing the surface of explaining how important their tooling really is. My aim is to help build frameworks and processes to capture the narratives more succinctly while highlighting the true features the SDK unlocks. As it stands, there’s still nothing even in web2 which offers the same type of abstraction that Codec is working towards. Open source contribution is the way forward and leading foundation models like Nvidia’s Issac Gr00t are already building with this in mind as data and task training is still so early on. You can’t use AI text strings to train robots, there’s no “internet of robotics”. Each of these humanoids and robots you’re seeing are built with full stack monolithic architecture, there’s no carry over for task training or ways to add new components (extra sensor or camera to the back of the head) without having to rewrite the entire codebase. Instead of building data pipelines and simulations for singular monolithic architecture, they’re taking a modular approach where instead of building tasks for whole systems, It breaks each part of the robot down into core components (motors, sensors, actuators, eyes etc). Meaning it can easily plug into any type of robot/humanoid no matter its system and instruct it to carry out requirements based on individual parts. Similar to what we saw with Eliza and Virtuals, devs didn’t need to code their entire framework and had GPT models with all the plug-ins (twitter, news feed, dexscreener API’s etc) at their finger tips. All they needed was personal context for their Agents inputs, then it was purely a matter of fine tuning. The goal for Codec is very similar, a developer hub where devs don’t need to worry about building their own “game engine”, the SDK toolkit is what Unreal Engine/Unity is to game development. Myself and @0xdetweiler have been doing a lot of hidden work in the background to help achieve this. This work has taken a significant amount of my time away from trading and why you haven’t seen me writing as frequently on Twitter or Telegram. For those who’ve read my content, you know how big I am on not sacrificing trading time as all it takes is one good trade to change your trajectory. The potential, narrative and market share Codec is going for is so large it convinced me to sacrifice my time as the pay off could be the next ai16z. The tech alone isn’t enough, the reason I’m writing this is due to how important it is to build in public and have constant communication about direction and core positioning (what my 30 page masterdoc consists of). Today we saw the tip of the ice berg for Humanoids with the 1X release, this is only going to accelerate with more teams releasing their robots onto the market over the next couple months. Robotics will have the largest encapsulation, growth and mindshare of any narrative we’ve ever seen. Don’t bet against the future.

Have you seen how viral this has gone? The types of emotions its sparked from people? Everyone’s gone from “humanoids are a thing 5 years into the future” to “oh fuck they’re here”. Encapsulation for novelty and growth is the biggest defining components when producing narratives and you simply can’t get anything more encapsulation than human sized robots running around society, taking a piece of the $42 Trillion dollar global GDP for the labour market. This is just the start, there’s only going to be dozens more coming onto the market and doing so very soon. These companies know whoever wins the Robotics race will quite likely be one of, if not the largest company in the world 1-2 decades from now. Robotics won’t slow down, won’t go away and is going to steam roll our entire economy. You all know how I’m playing the trade.

The most exciting ICM/utility coin is very undervalued at these levels. Our industry's biggest ever ICO, largest revenue generating app and highest user count is about to show you the tip of the iceberg for its new direction. There’s one specific utility coin on their platform which has refused to die. One that's accumulated 6 months of survival where the core holders only get more bullish by the day. This is the first time since 3 mil mcap I’ve added to my position. - Amazon replacing over half a million workers with robots, pushing to automate 75% of it’s workforce - $VIRTUAL pivoting their entire platform to Robotics - x402 is unlocking how Agents will be able to interact with commerce; Operators are the next stage which will be able to freely roam the internet and carry out economic tasks, this sets the foundation to robotic/humanoid assistants as well (VLA's) This technology is going to be the single biggest economic shift we’ve ever had. AI hasn’t been able to progress because it’s stuck inside a window. It’s dealt with text strings its entire life, how is it meant to progress into human capability when it doesn’t have a physical body to experience our same depth of reality? Maybe the unlock to AGI isn’t better GPT models but a body for AI brains to develop "consciousness" in. AI didn’t make sense until devs had public tooling to build their own GPT models with personal context (Virtuals & ai16z/Eliza). Robotics doesn’t make sense as there’s no plug and play optionality for individual devs. Large teams have walled access to the best data, brains and hardware specs. What happens when someone creates the Eliza of Robotics? $CODEC coded.