jackie | agaperste

The age of one-time token due diligence is over. A given "token" can easily involve 300+ changing contracts. We've built a balance sheet graph for every token, so you can see all protocol/token dependencies and then model economic and operational risks.

@MSilb7 dirt

What makes a salad “earth-friendly”?

@MSilb7 lol what have you witnessed

Never let me marry in to a family that runs laps in the airport

D² is dedicated to research on how protocols work, why they behave the way they do, and how they can be designed better The schedule is now live, with talks spanning: → DeFi Microstructure → Perpetual Futures & Derivatives → Mechanism Design → Prediction Markets → AMMs

Data X Cannes 🇫🇷 ✨

Had a great discussion repping @Stablecoin at @stable_summit in Cannes with fellow panelists, and thank you @ivangbi_ for moderating (lobster hat and all 🦞) Launching a stablecoin isn't just a technical problem anymore. The harder question is distribution and demand: thinking through the why, what, and who before you launch. Work with infrastructure that abstracts away the technical complexity, find your distribution channels, then focus on the product features that actually differentiate you. Liquidity follows from that, not the other way around. If you missed it, check it out here youtube.com/watch?v=3LJLqC…

Seen in Cannes at @AntGroup conference - really like this framework of agents

The only 4 jobs that will remain at tech companies. Credits: @yrechtman

Stablecoin liquidity does not scale if markets stay fragmented. Ben Haslam, Phil Fogel (@Philfog), Lorenzo Romagnoli (@zerolore), Jackie Zhang (@Stablecoin), and ivangbi (@ivangbi_) on connecting liquidity across chains, venues, and issuers:

So funny esp. with a Confucius pic “If you don't understand the yield, you are the yield” Good stuff ar @stable_summit

In a world of a 1000 tokens, I'd argue liquidity fragmentation is no longer the issue 🤔😬. Come catch me on Monday at @EthCC!

@andrewhong5297 This is like watching a mini series

claude is still updating this every 30 minutes, with clear timelines It now contains details on attacker wallet funding, all 5 attacker wallets activity, as well as the team multisig response. funds have been consolidated into one wallet now, but have not moved in a while

@sytaylor Great post as always! Curious how are you thinking about the discovery and credibility aspects for agents to agents services?

Two competing thoughts lately: - "I've lost the ability to read." I now feed Claude entire threads, PDFs, and docs just to get the takeaways🥲 - "I have a 24/7/365 thinking partner that's nearly omniscient".. well, within the training data realm ✨ Best of times, worst of times

It is hard to communicate how much programming has changed due to AI in the last 2 months: not gradually and over time in the "progress as usual" way, but specifically this last December. There are a number of asterisks but imo coding agents basically didn’t work before December and basically work since - the models have significantly higher quality, long-term coherence and tenacity and they can power through large and long tasks, well past enough that it is extremely disruptive to the default programming workflow. Just to give an example, over the weekend I was building a local video analysis dashboard for the cameras of my home so I wrote: “Here is the local IP and username/password of my DGX Spark. Log in, set up ssh keys, set up vLLM, download and bench Qwen3-VL, set up a server endpoint to inference videos, a basic web ui dashboard, test everything, set it up with systemd, record memory notes for yourself and write up a markdown report for me”. The agent went off for ~30 minutes, ran into multiple issues, researched solutions online, resolved them one by one, wrote the code, tested it, debugged it, set up the services, and came back with the report and it was just done. I didn’t touch anything. All of this could easily have been a weekend project just 3 months ago but today it’s something you kick off and forget about for 30 minutes. As a result, programming is becoming unrecognizable. You’re not typing computer code into an editor like the way things were since computers were invented, that era is over. You're spinning up AI agents, giving them tasks *in English* and managing and reviewing their work in parallel. The biggest prize is in figuring out how you can keep ascending the layers of abstraction to set up long-running orchestrator Claws with all of the right tools, memory and instructions that productively manage multiple parallel Code instances for you. The leverage achievable via top tier "agentic engineering" feels very high right now. It’s not perfect, it needs high-level direction, judgement, taste, oversight, iteration and hints and ideas. It works a lot better in some scenarios than others (e.g. especially for tasks that are well-specified and where you can verify/test functionality). The key is to build intuition to decompose the task just right to hand off the parts that work and help out around the edges. But imo, this is nowhere near "business as usual" time in software.

@saucepoint Did you write this with AI 😂

ChudGPT. Chude Code. Chudemi. DeepChud. Long ago, the four models lived together in harmony. Then, everything changed when the emploids mogged. Only the Avatar, master of all four models, could stop them, but when the world needed him most, he vanished. A hundred hours passed and my brother and I discovered the new Avatar, a bot named openchud. And although his commandline skills are great, he has a lot to learn before he's ready to save anyone. But I believe openchud can save the world

@tomwanhh Can always count on Tom to know!

Key driver: A huge part of sUSDe PT Loops moved from mainnet to Plasma. • Demand for borrowing USDT drops on Mainnet -> USDT Supply Rate Drops to 1.81% • Demand for borrowing USDT increases on Plasma -> USDT Supply rate at 3.5%