Good Morning to Everyone who Chooses to not give up, inspite of a cancerous price action and continues to push themselves to learn Trading, eveyday.
Which is like 0.1% of you.
The probability that we perceive the truth of reality is zero. In Dr Joe’s latest blog, learn what would happen if we got beyond our five senses and became aware of the infinite information in the quantum field. https://t.co/uT6R80aXlX
Join Dr Joe for a special, two-day free livestream event on Aug. 12 and 13 at 9 a.m. PDT / 12 p.m. EDT – and experience a preview of two brand new meditations. Learn more: https://t.co/JwpNri8DTb
Got liquidated and need 5 SOL to make it all back in one trade?
Here is all you have to do:
1) RT this tweet
2) Comment what coin you will bid
3) Follow our AI kwant @late_ser
The lucky winner will be announced on Friday 🫡
#DOGECAST on #Sol is under $5m mc & the ATH is around $35m mc.
I wouldn't be surprised to see a new ATH in this month.
Check @DOGECAST_USA out guys.
ChHAfQsUznqUpvFSNQsu42KsRr1t3ct56fBigVSHpump
Reposting here to get someones attention:
I’ve been building something closely aligned with this vision, leveraging the ELIZA framework by a16z (built by @shawmakesmagic) to create a personal AI agent with advanced recruiting and career analysis capabilities.
Here’s a breakdown of the project:
1. LinkedIn Data Integration:
Since LinkedIn’s API is highly limited (even with a business license), I downloaded my full dataset of 12,000 connections and uploaded it into a Google Cloud PostgreSQL database. This serves as the foundation for training the agent to map connections, roles, and affiliations.
2. AI Agent Functionality:
Using the ELIZA framework, I built a recruiter character that operates through Telegram. The agent is capable of:
Analyzing uploaded résumés to provide tailored feedback and interview questions based on the candidate’s experience and target roles.
Aligning résumé insights with job opportunities (currently restricted by LinkedIn API limitations but with future potential to expand).
Automatically applying to positions on behalf of the candidate, streamlining the job search process.
3. Multi-Platform Integration:
The agent integrates with GitHub, Twitter, Telegram, and CoinGecko APIs. This enables:
Mapping LinkedIn profiles to GitHub contributions using data from the Electric Capital Developer Report. For example, if a LinkedIn connection works on Arbitrum, the agent identifies 300+ sub-ecosystems associated with the project and correlates relevant repositories.
Fetching real-time market insights about companies and projects via CoinGecko to contextualize opportunities.
4. Rust Server for Advanced Training:
I built a Rust server to analyze my LinkedIn data, training the agent to understand 9 years of posts and 12k connections. This allows it to act as a personalized recruiter, reaching out to candidates on my behalf with targeted messaging.
5. Telegram Automation:
When a user uploads a résumé via Telegram, the agent performs a comprehensive analysis, matches their skills to open roles, and generates tailored interview prep. With expanded LinkedIn API access, it would also analyze current positions, align them with the user’s profile, and even apply to jobs autonomously.
This agent bridges professional networking, skills assessment, and job application processes, creating a dynamic and automated recruiter experience.
It aligns with your vision of building a LinkedIn for AI agents that assemble teams based on credentials, skills, and leaderboards. Excited to explore how this can scale further and become a core part of the future of work!
Here are a few example posts as well of the POC and the recruiter agent posting on my Twitter!
Big s/o to @shawmakesmagic for changing my life with ELIZA!
Also, I have a folder on my desktop called "Coinbase Interview" — it’s like this was meant to be lol.