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A deep learning system that predicts the assembly order of protein complexes using Graph Neural Networks. Trained on the Marsh-2013 benchmark dataset, achieving Kendall τ=0.73 — competitive with published research.
Built in PyTorch with full end-to-end pipeline: data preprocessing, GNN architecture design, ablation studies, and interactive visualization dashboard. Deployed on Hugging Face for live inference.
The network for creativity
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Hey Contra 👋 I've been heads-down building Promptly, and I'd love your eyes on it before our launch.
From my time delivering over 20 software projects as a tech lead, I realized the biggest bottleneck in building an app isn't the code itself. It is communication. Founders speak in ideas, and developers speak in strict logic.
Here is how Promptly works. You just describe your app idea in plain English. The AI actually pushes back, asks the hard questions, catches the vague bits, and automatically writes a developer-ready blueprint as you chat.
The goal is simple. When you hand this document to a developer, the next thing you get back is an accurate, fixed-price quote. No more wasting days trying to draft technical specifications and sitting through endless rounds of discovery calls just to get on the same page.
Instead of staring at a blank document, you get three tools that update in real-time:
The Pushback Chat: It refuses to just nod along. If you say "make it fast and secure," it helps you define exactly what that means. It hunts down edge cases before you ever pay someone to fix them.
The Visual Map: A live, interactive diagram showing exactly how your features connect. It catches logic flaws and missing steps before any code is written.
The Living Blueprint: An auto-generated, professional project spec that exports straight to Notion, Linear, or PDF.
Plus, it gives your idea a "Developer-Readiness Score" out of 100 so you know if it is actually ready to build. It even recommends the best tech stack based on your specific budget and complexity.
The core engine and all of these interactive features are fully functional right now, but I am still smoothing out the final rough edges. I am aiming for a public launch in about three weeks.
Where I need your help. I have three quick questions:
Where would you want to export your project blueprint, beyond Notion, Linear, or PDF?
What is the biggest headache you face right now when trying to explain your ideas to developers?
What feels missing? The blind spots are the most valuable to me right now.
Any feedback on new features, improvements, or things I should kill entirely would be hugely appreciated. Drop a comment below.
Thank you for taking a look 🙏
building solo, in public
Product ManagementFull Stack DevelopmentSoftware DevelopmentWeb DevelopmentAI DevelopmentClaudeNext.jsFigma
This is a very interesting concept! Where did you design the UI/UX? I feel like a better choice of font is still out there. Overall good work and clean UI. 🔥
Testing two visual directions for Lowkey.club service covers.
A leans into AI-native workflow and machine precision.
B leans into warmer campaign energy and “Marketing Made to Move.”
Both are built around contrast, dark grids, and the Signal Ember accent system.
Which direction feels stronger for Lowkey?
7 voted
70%
3 voted
30%
10 votes
Closed
I prefer Machine Precision, but both work well. You could also borrow a few elements from one to the other and blend them.
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