Help & Supportcareers@gravityer.com
Systemizing Vibe Coding through AI Harnessing Engineering. Creator of DocMason & LlamaPReview. Turning complex knowledge into reliable context for AI.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
codex-deepseek-bridge
June 20, 2026 – Present
Use DeepSeek models inside OpenAI Codex through a tiny local Responses-compatible bridge.
View ProjectDocMason
March 21, 2026 – Present
DocMason is a repo-native agent that turns your complex office files into a local LLM knowledge base and your second brain. The repo is the app. Codex is the runtime.
View Projectllamapreview-context-research
November 21, 2025 – Present
Research artifacts exploring Search-based vs. Agentic RAG strategies for AI Code Review. A deep dive into solving the "Context Instability" problem in LLM-based software engineering, analyzing trade-offs in recall, latency, and cost.
View Projectjetxu-llm.github.io
October 10, 2025 – Present
Personal blog focused on LLM, RAG systems, and AI Code Review
View Projectblog-comments
October 10, 2025 – October 10, 2025
Comment storage for my blog powered by Giscus
View Projectrepo-graph-rag
March 2, 2025 – Present
Code Mesh builds deterministic, evidence-backed repository knowledge graphs for Graph RAG, code understanding, and reproducible code intelligence.
View ProjectLlamaPReview-site
August 27, 2024 – Present
Official website for LlamaPReview Github APP: AI-powered GitHub Code review assistant. Showcases features, usage, and benefits of our GitHub App.
View Projectllama-github
May 16, 2024 – Present
Llama-github is an open-source Python library that empowers LLM Chatbots, AI Agents, and Auto-dev Solutions to conduct Agentic RAG from actively selected GitHub public projects. It Augments through LLMs and Generates context for any coding question, in order to streamline the development of sophisticated AI-driven applications.
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily skewed towards AI/ML, RAG systems, and backend/dev-tooling development, primarily using Python. While there are some frontend technologies listed (HTML, CSS, JavaScript), the focus is not on modern frontend frameworks or complex UI/UX development. This indicates a potential mismatch with a dedicated 'Frontend Developer' role, which typically requires deep expertise in frameworks like React, Angular, or Vue, and strong UI/UX sensibilities. The candidate's interests seem more aligned with AI engineering or full-stack roles with a strong backend/AI component.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions suggest an ability to articulate technical concepts, but there are no direct assessments of communication, teamwork, or problem-solving in a collaborative environment.