J Hackworth

@jhackworth

236 Following

616 Followers

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Thrilled to back Plastic Labs Beyond crypto, the modular vs. monolithic debate rages on in AI Today, OpenAI announced a monolithic memory approach. We believe that a modular approach like Plastic Labs could offer greater personalization & flexibility for agents. Learn more 👇

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Working on Agent that generates its own generative art code then publishes it. Hopefully will get better via Human Feedback over time, but still very much a WIP. Has had a few cool outputs so far, like the one below. https://rodeo.club/post/0xEd9c254942B50c07cFE3779D9bD175E751133262/5

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Yeah I think AI is extremely helpful for automation, I just worry that if you trust its decision too much the same things will be funded. Ie if every VC uses DeepResearch for a company / market they will all come to the same conclusion vs thinking for themselves.

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Too much reliance on AI in investing could create a dangerous feedback loop. Models will reinforce consensus thinking amongst investors. Yet exceptional returns require betting against the crowd and having information that algos can't capture.

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In desperate need of some good books to read right now. Anyone have any good recommendations to read?

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Daniel Barabander

I’m thrilled to announce our seed investment in Pluralis Research, which is building a decentralized AI training protocol. We are laser focused at investing in projects that use crypto ownership to solve coordination problems. Pluralis is a bullseye on that thesis, using ownership to solve the "resource problem" of training foundational AI models that are truly open. We couldn't be more excited to support Alex and the rest of the team. Full post here: https://blog.variant.fund/investing-in-pluralis-research

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What is the easiest way to donate to a charity onchain?

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Will be somewhere in Santa Monica can shoot you a dm later!

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Will be in LA next week with @dbarabander — who should we connect with? Especially excited to meet anyone working (or exploring) the intersections of Crypto x AI.

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NEW PRODUCT / PRE-SEED ANNOUNCEMENT https://x.com/jessewldn/status/1889369798305608110 If youre launching tokens you must yap to @aja about Doppler

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fun jamming with @dbarabander @jhackworth on these. our DMs are open if you're working on any variant of these, or something we didn't think of :) a few other relevant links below. https://warpcast.com/jesse/0xfe0fdd4a

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Just slow lol. It takes a while to process the data for each account and there are some rate limit issues as well 😅

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8/ Want to try it yourself? Just @ AWESOM-O on Farcaster to get started. DMs are also open for builders exploring onchain agents or wanting to jam about where this space is heading. P.S. No token. Ever. Some experiments should stay experiments

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7/ After building an agent, here are the biggest opportunities I see: -Human-AI Collaboration: Applications that combine human judgment with AI automation -Better Data Integration: Richer data sources for agents to leverage -Crypto-Native Tools: Models and infrastructure built specifically for crypto use cases -Developer Experience: Expanding frameworks like Eliza and GAME to simplify building -Smart Contract Integration: Making it easier for agents to interact with onchain protocols -Feedback Systems: Building loops that help agents develop taste and improve over time

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5/ After building agents with LLMs, here's the reality with today’s models: They excel at pattern detection and content generation but lack precision without training data. They'll generate AI slop forever, but can't judge quality. In the case of AWESOM-O the risk is low to generate a Farcaster Wrapped, but I wouldn’t trust it with my own money

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6/ Until models improve, agents need humans at key decision points. For AWESOM-O, I would use Farcaster likes as an objective function - teaching it to understand content quality through user feedback Just like Botto, where AI creates, humans curate, and the system learns from human taste to improve

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4/ How does AWESOM-O work? Just @ the agent and it: -Processes your request -Queries network-wide data via Dune -Extracts personalized insights -Generates your custom-wrapped By querying Dune directly, AWESOM-O can analyze a year of network-wide data - impossible for agents on closed platforms like X. Also have to shoutout @hyperbolic for being my go-to inference on this

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3/ Why Farcaster over Twitter? Twitter is a walled garden, Farcaster is an open protocol. While Twitter has distribution, Farcaster has what agents truly need: open data, native composability, and permissionless integrations. When agents can tap into everything in the network, they unlock possibilities that centralized platforms can't match

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2/ Onchain agents will revolutionize crypto as we know it. They’ll streamline UX while enabling entirely new applications. As a data scientist, I knew I had to build an agent for myself.

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1/ Introducing AWESOM-O: A Farcaster agent that generates your own personalized Farcaster Wrapped. Built this because I believe we're just scratching the surface of what's possible with agents in crypto and wanted to get my hands dirty. Some thoughts 🧵

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