This is the official account of https://t.co/UsuqNFKaBt. We are rebuilding our twitter again and this is the new home for all future updates.
Our old handle (@Shyft_to ) was compromised 3 months ago.⚠️ Please unfollow & report it.
Spread the word. Let’s rebuild stronger. 💙
We've been in discussions with https://t.co/nbc8LzDcrP to bring their priority fee intelligence to Shyft's platform. We have users already asking for exactly this and the slot-level approach is meaningfully better than standard RPC methods. Excited for the priority fee innovation that's coming out.
shoutout to @Shyft_to for being an amazing RPC partner to build on @solana.
millisecond-obsessed Solana infrastructure with multi-region Yellowstone gRPC streaming, shred-accelerated RabbitStream, and staked RPCs built for production.
this is why we are working together during @colosseum, and integrating our priority fee module as a start.
OPOS
Only Possible on Solana
Only Possible on Shyft
@GlowieDev Internally we filter by instruction discriminator, which also means that we dont parse any IDLs.
Its easier and intuitive to parse instruction name thats why we went with it. But yes if we see that descrimators would be better then we can have that as well.
Stop rebuilding the parsing layer.
Focus on your trading logic.
GitHub: https://t.co/rbAnBTBWye
Ladybug is early, evolving, and built from listening to real user pain of hundereds of devs. Feedback, issues, and PRs welcome.
P.S: Rust sdk coming right up.
Every Solana trading strategy starts with the same mistake - rebuilding the Yellowstone gRPC parsing layer from scratch.
That’s weeks of work before writing a single line of strategy logic.
Ladybug SDK fixes that 🐞
Focus on strategy, not parsing🧵👇
My data journey has been... a trip.
Fell in love with data analytics 'cos I love numbers. Started like everyone else: Tableau & Power BI. "Behold, my beautiful pie chart! Such insights!"
Ventured into SQL, then Python. Then discovered ML on Kaggle and it was love at first sight. Binge-watched all the courses, thinking I was a data god. "My model can predict... if my model will finish running."
But I still felt a darkness. Something was missing.
Then I heard "on-chain analysis."
At first, I thought this meant having 15 tabs of Etherscan, DexScreener, and CoinGecko open while refreshing 100x/day. "Ah yes, the price went up. My analysis is complete. I am an on-chain analyst." 😂
LOL.
I wasn't doing analysis. I was doing on-chain browsing.
The real lightbulb moment hit when a mentor suggested I actually learn it. I found @andrewhong5297's roadmap and his @dune's live videos with @ournetwork__ . My mind was blown. "Wait, you mean I have to write queries? Not just watch the mempool?"
Then immediately I was done with the blogs in the roadmap and started being conversant with dune, @Dan_the_Mage led me to @analyticsage, and my queries finally started to make sense because there was a community to grow.
I've now leveled up from 'Dashboard Builder' (that wins Hackathons) to 'Actual Product Engineer' thanks to @apostleoffin Python cohort 1 lectures. We learnt to script frontend/backend like pros.
Looking back, the proof is in the code. The scripts that generate signals for ismartybot are now just straight-up novels:
Discovery Alert: 3.3k lines
Alpha Alert: 2.2k lines
My git commit messages are basically just "pls work https://t.co/Y35Y5WpcvB_final.v2". Yes, definitely I would modularize the project soon.
This thing is wired up to a ton of endpoints. We're hitting APIs from @dune, @heliuslabs, @GoPlusSecurity, @Rugcheckxyz, @MoralisWeb3, @shyft_hq, @dexscreener, @CoinGecko, and various Solana RPCs just to make the magic happen. All hosted on @render free instance which is now no longer running the project properly since the introduction of machine learning prediction.
So when people DM me, "How is ismartybot hitting >50% win rate daily in THIS market??", my answer is simple:
It's not TA, vibes, or hopium. It's just a metric ton of Python.
Want to learn the real sauce my boss @defi__josh and I use? Stop browsing and start building. Register for the next python cohort.
https://t.co/gcGqGHx4kR
Here's some working examples in rust and TS. We benchmark new @Pumpfun mints
RabbitStream vs Yellowstone gRPC with the same client.
https://t.co/WR9a0JF0pp
Docs:
https://t.co/uO2JJwBhT3