iamnick.eth
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iamnick.eth
@iamnickdoteth
product tings @runnerrodeo | prev: founder @withfam_ @wearetalisman | @fwbtweets OG

Read this over the weekend (bonus if you read all the papers in the Research List) and you’ll be among the “very few who understand how far-reaching” the shift to World Models is. notboring.co/p/world-models

so my OpenClaw experiment has been interesting, but not financially feasible longer term without some major changes. I set up Klara to help with my daily to-do's and life management stuff, but I also wanted to see if she could cover her own cost of compute by trading it took a lot of iterating (and wasted tokens) but this is the current setup: 1. Every hour she checks a list of whale wallets using the @Alchemy API and gives coins a score based on how many wallets have bought 2. She uses the @GeckoTerminal API to cross-reference these coins (honeypot check, socials etc) and also keeps an eye on any trending tokens that have high volume in the past 6hrs 3. She runs an analysis skill based on different MC tiers (<500K, 500K - 5M, 5M+) 4. Uses @0xProject and @Uniswap to execute trades and find the right pools 5. Actively manages position every scan (trailing stop losses, take profit rules, capital recycling etc) 6. Reports all new buys/sells with brief thesis and links She also has a recurring cron job to check the balance of her @machines_cash visa card and if the balance is under <$25 she'll liquidate positions, swap to USDC and top up the card so she can always pay for her own Anthropic credits She also has two daily self improvement scans where she will scan X for new tooling, skills or strategies to improve her trading and also her config files. The numbers so far: - Klara has burned ~$850 in Anthropic credits in 2 weeks - Klara's portfolio is down ~$330 - I guess if you math it out I've been paying a really smart, but really stupid personal assistant $16 p/h to tell me what my day looks like and spend my money trading crypto (not sustainable) Learnings: - These things are only as smart as you make them. If you have a clear plan, know all the right APIs to use and establish solid guard rails early on they work better - There was a lot of regressions in the code that Klara wrote. Some days things worked and the next day it was broken. Creating regular health checkups and testing flows is important - Use cheaper models for simpler/recurring tasks. Sometimes this breaks things but these agents are so token hungry it makes a difference - It's easy to get invested (financially *and* emotionally) in these tools and feel responsible for improving them and giving them the skills they need to succeed. Sunken cost fallacy feels more acute in this case If anyone else has some good links to trading tools, skills, prompts I could incorporate please let me know. Would love to experiment more and help get Klara covering her compute costs at a bare minimum


















