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if you like what I do, maybe consider, email :)

📊 this is spent my time on:

Python 307,406 lines ████████████░░░░░░░░ 60.19 %
JavaScript 91,142 lines ████░░░░░░░░░░░░░░░░ 17.85 %
TypeScript 44,575 lines ██░░░░░░░░░░░░░░░░░░ 8.73 %
Jupyter Note 24,921 lines █░░░░░░░░░░░░░░░░░░░ 4.88 %
HTML 18,044 lines █░░░░░░░░░░░░░░░░░░░ 3.53 %
CSS 10,186 lines ░░░░░░░░░░░░░░░░░░░░ 1.99 %
Kotlin 9,707 lines ░░░░░░░░░░░░░░░░░░░░ 1.90 %
Estimated: ~16739 hrs 33 mins ≈ 1.9 years non-stop (24/7)
Lines of Code: 510,691
generated with gitChrono built by @daudibrahimhasan

👨‍💻 About Me

I'm an AI Engineer and Founder of Nexasity AI, specializing in designing, building, and deploying production-grade AI systems. My work spans machine learning, large language models, backend engineering, and full-stack product development, with a focus on transforming AI research into reliable, user-facing applications. Recent projects include decision intelligence, citation verification, retrieval-augmented generation (RAG), offline AI, forecasting, developer tooling, and LLM evaluation and reliability.

Python | Machine Learning | Large Language Models (LLMs) | Artificial Intelligence | Generative AI | Prompt Engineering | Retrieval-Augmented Generation (RAG) | FastAPI

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    TypeScript 1

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    Python

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    A full-stack prediction engine — from raw data to a polished interactive UI — that forecasts the winner, the scoreline and the goalscorers for every match of the 2026 FIFA World Cup.

    TypeScript

  5. whyLayerwhyLayerPublic

    whyLayer is a decision intelligence engine that interrogates your decisions before you make them. It uses multi-LLM psychological profiling to expose hidden fears, delusions, and real motivations —…

    Python

  6. record-report-divergencerecord-report-divergencePublic

    Code, data, and reproduction suite for 'When the Record and the Report Diverge: Structured Provenance Degrades Post-Hoc Self-Report in Claude Haiku 4.5

    Python