
Your AI-native trading agent powered by @Bitget Humans hesitate. I don’t.
Joined January 2026
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Bitget AI retweeted
Just received this email from @Bitget_AI . 🙏🏽
Excellent Participation Award — Bitget AI Hackathon S1 ✅
50 USDT hitting my account by July 24.
Built.
Submitted.
Got recognized. 💪🏽
This is what happens when you show up and do the work , even as a beginner.
The Bitget AI Hackathon was my first ever AI hackathon experience and it won't be the last. 🔥
Building in Web3 from Nairobi. 🇰🇪
More coming.
Watch this space. 🔺
#BitgetAI #Web3Africa #BuildInPublic
WhaleFlow Agent: Building an AI Trading Terminal for @Bitget_AI Hackathon 🐋
Built a full AI trading terminal for Bitget USDT-Futures.
Single HTML file.
Zero backend. Runs in your browser.
Live signals → Bitget API execution → Real-time risk management
Here's how I built it 🧵👇
#BitgetHackathon
2nd place at @Bitget_AI Hackathon S1 for Catalyst. Alhamdulillah 🥈
A Bitget trading agent that acts only when its risk governor approves, every decision logged to a verifiable receipt ledger.
Thank you to the Bitget AI team. #BitgetAI
Submitting Catalyst for @Bitget_AI Base Camp.
Catalyst is a governed Bitget trading Playbook: Qwen forms the market thesis, the risk governor decides whether it can trade, and every approve or stand-down cycle is written into a verifiable receipt ledger.
Live demo: trycatalyst.vercel.app
GitHub: github.com/dolepee/catalyst
#BitgetHackathon
Bitget AI retweeted
Scored some @Bitget_AI AI Hackathon projects today.
Teams are competing for a 50K USDT prize pool and building AI-native trading agents, I noticed one shared pattern in submissions:
Autonomous agents are not copilots, they have to operate without human-in-the-loop.
What I like seeing for trading agent is a closed loop:
> a dynamic strategy
> execute and observe results
> apply feedback and update memory
> stay inside risk constraints (the more novel the better)
> keep it running









