Wasif Ullah @wasifullahdev

@AliGrids Right

@aditiitwt Hello world

@nizamdesign B

@EmmanuelBuilds React

2025 taught me: - Fine-tuning models > building from scratch (most of the time) - Clean code & good documentation save more time than clever hacks - Shipping fast + iterating beats waiting. #SoftwareEngineering #AI #LessonsLearned #Tech2025

@Peerlist Docker compose up

@stevebauman @stevebauman Solid advice! Optimizing DB queries and queuing are a great start. Adding caching for static data and load balancing for scale could round it out. Thanks for sparking the discussion!

@samirande_ 3hr for each paper max

If you could only use ONE tool for your next project (besides your IDE), what’s your pick? I’m curious what devs can’t live without! Share yours and why. #Coding #Tech #Developer

Every dev has THAT one bug that haunts their dreams. What's the weirdest coding glitch you've ever faced? Spill the tea I'll share mine too! #DevLife #Programming #Tech

What's the ONE tech trend you think will dominate 2026? I'm betting on smarter dev tools to cut coding time in half. Drop your prediction below let's see who's right! #Tech #Coding #Innovation

MERN devs, what's the ONE tool or trick that saves you hours on your full-stack projects? I'm neck-deep in a React-Node app and curious about your go-to hacks! Share below. #MERN #WebDev #Coding

Computer vision folks, what's the toughest dataset you've wrestled with? I'm building a real-time vision app and want to hear your war stories bonus points for wild edge cases! #ComputerVision #AI #Tech

Blending MERN apps with computer vision is my jam. What's the next big thing you want to see in web apps powered by AI vision? Dream big, let's brainstorm! #MERN #ComputerVision #DevLife

@simonw Not exactly an LLM fine-tune, but I recently tackled something similar on the vision side teaching a model to interpret hand-drawn flowcharts and convert them into structured data. RF-DETR + PaddleOCR + a lot of geometric heuristics. medium.com/@wasifullahdev…

Full article linked in the first tweet This project took 2 months of debugging real-world chaos. If you're interested in production computer vision, the Medium article has all the technical details, challenges, and solutions. Questions? Happy to discuss.

just published a detailed breakdown of how I built an AI system that converts hand-drawn diagrams into structured, machine-readable JSON. if you work with images automation or need to digitize visual workflows this might interest you medium.com/@wasifullahdev…

What I'd do differently next time: - Start with even more diverse training data upfront - Build visualization tools earlier for debugging - Use ensemble methods for arrowhead detection - Consider GNNs for spatial association (though KD-Tree worked well)

If you're building solutions that need to: → Parse visual diagrams at scale → Extract structured data from unstructured images → Handle real-world image quality challenges → Maintain high reliability in production Read this Article.

The Real Insight: When you hit the limits of pure deep learning in messy domains, geometric algorithms become your competitive advantage. A well-designed algorithm grounded in math + smart fallback logic beats raw model power for production robustness.

Performance Metrics: ✓ 96.71% precision on arrow connection detection ✓ 96.71% recall across complex, crowded layouts ✓ Works reliably on real-world diagrams ✓ Handles mixed drawing styles in the same image ✓ Processes diagrams at scale without degradation