Flagship Infrastructure
next-static-search
Static search for Next.js, built around fast client-side querying and a developer experience that doesn't fight you.
Open Source
Packages, utilities, and public code shaped by actual product needs, developer pain points, and a preference for tools that are practical, documented, and easy to reuse.
Public Building Blocks
Small, reusable tools distilled from product work, developer friction, and experiments worth sharing publicly.
Flagship Infrastructure
Static search for Next.js, built around fast client-side querying and a developer experience that doesn't fight you.
Beautiful and highly customizable GDPR and ePrivacy consent management for React and Next.js applications.
Convert Mongoose schemas into entity relationship diagrams to make model structures easier to understand and communicate.
A Python library for fetching and analyzing trending topics from Google Trends and turning raw signals into usable insight.
Detects active ad blockers in React apps so the UI can adapt instead of pretending the ad slot rendered.
A React component for integrating Google Ads while suppressing empty or unfilled ad spaces for cleaner UX.
React and Next.js wrapper around the fluid cursor effect, for interfaces that want a bit of flourish.
A customizable fluid cursor effect for modern web interfaces with smooth, interactive visual feedback.
Philosophy
Most of these packages began as a small irritation inside real product work. I publish the ones that can save another developer the same detour.
One clear job before a long feature list
Examples that make the first integration less fragile
Maintenance decisions that respect existing users
Lifecycle
From identifying a need to publishing and maintaining.
Step 01
Notice the same workaround showing up in more than one project.
Step 02
Build the smallest version that actually solves it, nothing extra.
Step 03
Write real docs, then release it where developers will actually find it.
Step 04
Keep fixing it for as long as people depend on it.
Quality
Small safeguards that matter once another codebase depends on the package.
A version bump tells you honestly whether it's safe to upgrade.
Covered across the environments people actually run it in, not just mine.
A working example in the README, not just an API reference.
Prototype archive
These are submissions and public concepts, not production case studies. The oversized flagship and project links make it easy to inspect what was actually framed or built.
Deriv AI Talent Sprint • lablab.ai — Built an autonomous penetration testing platform for the Deriv AI Talent Sprint.
Finance / workflow prototype challenge • Devpost — Built a concept-driven finance workflow prototype modeling loans as living assets across origination, monitoring, and execution stages.
AI Agent innovation sprint • Devpost — Presented an AI-native deal execution concept focused on procurement, compliance evidence, and graph-backed commercial workflows.
Agentic Commerce on Arc • lablab.ai — Created a knowledge refinery marketplace where AI agents and human reasoning interact through decentralized verification ideas.
Agentic AI Hackathon with IBM watsonx Orchestrate • lablab.ai — Developed a hierarchical agentic AI framework for IBM watsonx Orchestrate hackathon work.
Qubic | Hack the Future • lablab.ai — Presented a whitepaper and tokenomics concept connecting AI, blockchain, and yield-backed evolving NFTs.
AI Genesis • lablab.ai — Proposed and built a browser extension for audio-to-sign-language accessibility workflows.
Scored environments
Exact outcomes are more useful than victory language: top 100, 9 of 9 puzzles, and 22nd nationally out of 538 competitors.
CALICO Fall '25 • CALICO / UC Berkeley ecosystem — Placed 22nd on a country level out of 538 competitors in the CALICO Fall '25 competition.
CS50x Puzzle Day 2025 • Harvard CS50x — Solved all 9 out of 9 puzzles in Harvard's CS50x Puzzle Day challenge.
M(IT)^2 2025 Winter Contest • MIT-aligned contest ecosystem — Competed in the winter contest and ranked among the top 100 participants.
The sprint loop
The deadline forces choices. The goal is to protect the core idea, prove one end-to-end path, and make the limitations legible.
Translate the theme into one user problem and one claim the prototype can realistically demonstrate within the event window.
Test the uncertain integration, model behavior, or workflow before polishing the surrounding interface.
Present what works, what remains conceptual, and what would need validation before the idea belonged in production.
What the archive reveals
A ranked contest, a working prototype, and a whitepaper concept answer different questions. The page should make those differences visible.
CALICO, CS50x Puzzle Day, and M(IT)^2 provide externally constrained results that can be stated exactly.
The hackathon records show how a broad theme became a user, workflow, architecture, and public submission page.
Security, finance, accessibility, agents, and blockchain show breadth; the result labels clarify whether each entry was scored, built, or conceptual.
Technology coverage
Technologies represented across open-source contributions.
Next Steps

Open source earns its keep by removing real friction, not by looking good in a portfolio. Here's what separates a package worth adopting from one that's just decorative.

My repo has four apps and three shared packages, and most commits only touch one of them. Rebuilding everything on every push would mean paying compute for work that didn't need doing — Turborepo's whole job here is refusing to do that.

The search optimization acronym explosion shows how industry terminology evolves faster than practices do. AISO, AIO, and GAIO largely repackage what GEO and AEO already meant.

A practical checklist for assessing open-source maintainer health and package reliability before adding it to your dependency tree.
Case studies of built systems.
Background and expertise.
Longer-form case studies with architecture and outcomes.
Scholarships, rankings, and other source-labeled milestones.
Reusable public code beyond time-boxed events.
Technical decisions and lessons explained in depth.