Trissy

@litcapital @real_y22 mode

Golden age of American Dynamism

@punter_punts real

@amabinvesting eternal bad karma

using your mom as exit liquidity would be a diabolical outcome

@crypticd22 🤜🏼

@Cryptotrissy Great write up 🤛🏼

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.

@onchainrobber no code no ceiling no worries

After $GSD (still holding), I’ve positioned into my next bag for AI Szn 2.0. $NOCODE Lore - as the name suggests, it literally has no code, yet somehow racks up 65k+ stars on GitHub and is one of the biggest Git memes itself. No Code → No FUD → No Roadmap → No Rug. Can’t get any better 🚀

@spyzer i am a mere vessel for my bags

@Cryptotrissy Thank you I may or may not have stolen some words from your channel

Overview of current projects I'm watching (AI szn 2.0) I dont know about you guys but this kinda reminds me of layup last AI szn late 2024. Strong rebounds after first leg up. High quality viral devs entering our space which are on the edge of the biggest change since the internet. I'm not saying it will end up going the same way again, I'm saying you should pay attention. Current 'leaders'; >>utility -- $RALPH ; Ralph is a looping agent that repeatedly reruns a model with fresh context until a defined success condition is met, excelling at deterministic, testable tasks like debugging and TDD. The north star is Loom: a swarm-style framework that scales this brute-force persistence into coordinated, self-correcting autonomous agents. Crazy viral on X & github/in AI community. -- $GSD ; GSD uses a structured validation loop where verifier, planner, and debugger agents repeat until a task is correct, keeping each step in a fresh context to avoid token bloat. Instead of brute-force autonomy, it works like a senior engineer—shaping requirements, asking the right questions, and continuously checking that the system is built as intended. Level of adoption (github download/star chart) is literally parabolic. -- $X1XHLOL ; dev (16 y/o gigabrain with most github stars on a single repo- 110k) describes a fully homomorphic encryption marketplace (FHE) in his whitepaper. An open-source AI security scanner that actively tests for: > prompt injection, social engineering, role confusion ,multi-turn escalation, encoding tricks, .. Lucas (dev) just open-sourced the core engine while keeping the hosted product (dashboard, reports, infra) as SaaS. a16z 'Big Ideas 2026 predictions' called out AI agent security as THE critical infrastructure problem for this year. token has actual utility: subscription payments, early access, discounts. Defining new category / moving before incumbents. -- $GRASP ; GRASP began as a mental framework for assessing AI risk, similar to how Ralph started as a concept rather than a product, but it’s now evolving into something concrete centered on reducing token usage, improving agent reliability (especially for looping agents), and applying GRASP principles--- ((G: Governance (ownership + override) R: Reach (permissions + blast radius) A: Agency (autonomy + looping power) S: Safeguards (evals, monitoring, rollback) P: Potential Damage (worst-case impact)) ---to appeal to conservative businesses. The creator brings strong DevOps, infrastructure, and AI experience, plans to fund development and marketing through the the token, and will share more details on tech/future plans/.. on Jan 23. Dev is also irl friends with Ralph dev. -- $CMEM ; 14.7k stars on github, offering persistent memory for Claude across devices and workflows. It’s now one of the most popular Claude plugins with ~15k GitHub stars, top trending rankings, and strong adoption among professional developers. "A Claude Code plugin that automatically captures everything Claude does during your coding sessions, compresses it with AI (using Claude’s agent-sdk), and injects relevant context back into future sessions." Context and memory are v important. -- $GRU ; Web3 native dev with solid track record, a system that lets you spawn and control Claude agents on your own machine directly from Telegram/Discord, giving you the ability to monitor their work and approve or reject actions before they run. The platform supports both supervised and fully autonomous modes, secure encrypted secret storage, multi-agent coordination, and extensibility through MCP servers. It also includes priority scheduling, shared context between agents, and full conversation and audit trails so autonomous work remains controllable and traceable. Mert loves the idea ; vibecoding from mobile. >>memes -- $CLAUDE (make no mistakes) ; commonly used phrase among AI devs -- $NOCODE ; there is no code -- $LOCALHOST ; if a retard codes something and tries to share it online not knowing localhost only points to people their own machine -- $CURSED ; gen Z programming language. Ralph built it >>?? -- $SOL ; Claude keeping tomato alive. Very complex/interesting experiment. Sorry if I missed some coins (share them below), sorry if I didn't include the most bullish info on your coin. Just trying to make people aware of what's happening. Follow for more, I'll try my best to keep sharing alpha & my thoughts on what's happening. Let's print 🫡

@onchainrobber we gettin shi done

@Cryptotrissy $GSD is coded!

@prelemur nah people who actually research shill gsd

@0xuberM gsd men

@crypticd22 what if

There we go First sign of recovery onchain and the coins with the strongest bids are the ai coins. This meta is gonna see a round 2, as we’re seeing with Ralph and I expect ceilings to be raised this time as the winners are clear and we see greater concentration of liquidity. $Gsd is the one with big potential here. The timing of its launch during the end of the first wave of this meta means lots of people weren’t looking creating a market inefficiency, and additionally it also doesn’t have bag holders who bought higher, unlike all the other strong plays in the narrative right now. One of the best r/r plays at this moment

@amabinvesting ni hao fine shyt

quick euphoria followed by deep depression dopamine receptors fed and fried everytime the playbook is the same, btc/majors bounce of local lows, onchain picks up a new meta and turbo bids it, late entrants come in and buy the top, btc/majors correct, everyone capitualte their bags, meta leaders bottom/consolidate, btc/majors bounce off a higher low, meta leaders bounce even harder whenever a new meta goes through a boom and bust this quickly, its usually an indicator of there being some underlying value present when prices go up noone cares about ownership, token integration or equity when prices go down everyone comes out with the pitchforks and starts poking holes at the meta ai16z spent 2 weeks consolidating between 10-40m after its intial run to 190m before its parabolic run virtuals spent 4 months consolidating between 20-80m after its intial run to 160m before its parabolic run history rarely repeats itself, but it often rhymes, stick around, stay intune with onchain and perhaps you are able to run it back when, not if, btc/majors turn around to the upside, my bet is on crypto x ai of the last couple weeks or something new in the same domain bouncing the hardest osamabinstudying history and patiently bidding bottoming formations

@crypticd22 like clock work

@Cryptotrissy Gas capitulation got everyone looking away at the wrong time

Gsd now caught up to gas in GitHub stars and nearing Ralph, with a dev that’s 100% committed to the token The Ralph recovery shows there’s still appetite for this narrative. I expect the higher quality plays to follow Ralph

@leftcurvemaxing great post

on day two of using $GSD in my workflow and realized i feel 10x more productive, so i felt compelled to sit down and write out specifically why I think it's a game changer typically when you sit down to build something, you want to come to the table with a PRD (product requirements document) unless youre yoloing something, this tells claude code a specific outline of goals and requirements for what you want to build when using a looping plugin such as the ralph loop, you tell it "accomplish abc things" or "read PRD and test + build each section" and it will do it however, these are not "smart" checks in the system what GSD does that's so brilliant is before it spawns a bunch of agents to research or work on a piece for you is it asks specific questions about your prd, your goals, how xyz pieces should function etc, and it then builds out its own document on top of that not to mention the standard "does this actually work as intended" checks that come built into the tool, all while not wasting a ton of credits. the agents work efficiently without much waste due to how optimized GSD is what I will say is it's not as hands off as other tools, but as far as building something that isn't broken slop, the check ins after each piece is built is part of what makes GSD so good. you're sacrificing a little bit of speed (though not by much) for things that are much better, less prone to breaking, more thorough and actually useful the end result is your code has way fewer mistakes, much more detailed requirements, features you may not have considered that are actually useful, and fluff that's removed because you realize one part might not actually a good idea and you want to pivot. if you DO decide to pivot then GSD walks you through everything and catches what may need updated in earlier/other pieces for you the other brilliant part of GSD is you can have it rip a new project on its own. you don't have to have a PRD already written. you can sit down and have it start a new project and build out a PRD with you based on a conversation the "english is the new programming language" bit feels pretty real when you sit down with a tool like GSD and you can go from 0 to 1 in an afternoon. will emphasize again that this is different than the workflow of other tools that rip into the writing portion without fully gathering context/goals, and you end up wasting time shoehorning in features that should have been there from the start, or trying to fix things that shouldn't have been broken from the start if youve been hesitant about building something, GSD will make it much less intimidating and you should give it a shot hats off @official_taches, GSD is my new favorite way to work

@sonder_crypto no ceiling

Uber, the largest taxi company, owns no vehicles. Airbnb, the largest accommodation provider, owns no real estate. $NOCODE, the most starred repo on GitHub has no code. Something interesting is happening.

@duckingnator seems like they're quite busy vibe animating

What happens when psyopanime releases a full length 10 minute plus episode that goes viral all over Twitter with Elon already following the page? Are you ready for that scenario? I get my news from psyopanime. Sent from my LG Smart Fridge OLED 144HZ.

@ChillTRD likewise

I get my news from PsyopAnime.

@PsyopAnime diff