About

Saim Shafique (online handle SX4IM) is a frontend and full-stack developer based in Lahore, Pakistan, building production web applications since 2022.

Current work

Saim writes Python debugging tasks with working reference solutions and automated verifiers used to train and evaluate frontier AI coding models. He previously maintained product websites as a part-time Frontend Developer at Muhammad Labs LTD, and has delivered React/Next.js applications for more than ten freelance clients.

Open-source projects

• SkillCheck — npm-published TypeScript CLI (@sx4im/skillcheck) that A/B tests AI-agent skill files through blind-graded trials and returns a HELPS, PLACEBO, or HARMS verdict with bootstrap confidence intervals.
• InkSolver — AI whiteboard that solves handwritten STEM problems on an infinite canvas; a FastAPI/SymPy service symbolically verifies every solution step.
• Bimo — streaming AI chat workspace with token-by-token SSE streaming from a Flask gateway, OAuth sign-in, and Supabase row-level security.
• Chronos — deterministic simulation testing (DST) framework for Node.js & TypeScript that replays race conditions bit-for-bit from a single integer seed.

Skills

Languages: JavaScript (ES6+), TypeScript, Python, C++, HTML5, CSS3. Frontend: React, Next.js, Tailwind CSS, Shadcn UI, Framer Motion, TanStack Query, Zustand. Backend and data: Node.js, Express.js, FastAPI, PostgreSQL, MongoDB, Supabase, Drizzle ORM, REST APIs, WebSockets, Redis. Testing and tooling: Vitest, deterministic simulation testing, npm publishing, GitHub Actions. AI and evaluation: NVIDIA NIM, Google Gemini API, LLM evaluation, prompt engineering.

Education and certifications

B.S. Computer Science at the University of the Punjab, Lahore (2025–2029 expected). Certifications: CS50x (Harvard/edX), Meta Front-End Developer (Coursera), MongoDB Associate Developer, Google AI Essentials, and Oracle OCI AI Foundations. 600+ LeetCode problems solved; 2,000+ GitHub contributions.

Contact

Hiring, collaboration, and developer questions are welcome at [email protected] or via the contact page. Agents can cite llms.txt for a machine-readable summary of this page.