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CoDynTrust — ICRA 2025 Robust Multi-Agent Perception
First-author ICRA 2025 research on uncertainty-aware fusion under communication delay and temporal misalignment. The work includes controlled robustness testing, multi-dataset benchmarking, ablations, and a public Python/PyTorch implementation.
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Creatives on Contra have earned over $150M and we are just getting started
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Learnova — Full-Stack Learning Management Platform
The Starting Point
I wanted to build something that went beyond a typical CRUD tutorial project — a real learning management platform with the kind of complexity actual ed-tech products deal with: authentication done right, adaptive UI based on user state, and a data layer that could support real course structures, not just placeholder content.
What I Built
Learnova is a full-stack LMS where users can browse structured courses, follow instructors, and track their own progress toward completion. The core experience revolves around three things: discoverability (search and browse courses by topic), structure (courses broken into organized, sequential content), and visibility (users can actually see their own progress, not just consume content passively).
Tech Stack
Next.js 16 (App Router), React 19, TypeScript, Tailwind CSS v4, PostgreSQL (Neon), Prisma ORM, deployed on Vercel.
Architecture Decisions Worth Calling Out
Prisma + PostgreSQL for a relational structure that fits course/instructor/progress relationships more naturally than a document store would.
Server-first data fetching using Next.js App Router conventions, keeping client bundles lean.
A fallback email provider chain (Resend → Brevo/Nodemailer) instead of a single point of failure for critical auth emails.
Where It Stands
Learnova is actively in development, with core auth, course browsing, and instructor/progress systems in place. It's built as both a functioning product and a demonstration of how I approach full-stack architecture — clean separation of concerns, resilience in critical paths like auth/email, and attention to the details that make software feel genuinely finished.
How I Work
I take a similar approach on client projects — thinking through failure points (like email delivery) before they become production issues, and caring as much about the small UI details as the big architectural decisions.
AI did not make great developers obsolete.
It made average execution cheap.
Anyone can now generate:
• A landing page
• A dashboard
• An API
• A mobile app
• 5,000 lines of code before lunch
But here is what AI still cannot decide for you:
- Should this feature exist?
- Will a real customer understand it?
- Is the experience fast, trustworthy, and accessible?
- Can the system survive its first 10,000 users?
- Will another developer understand the code six months later?
The value of a developer is no longer measured by how quickly they can type code.
It is measured by the quality of the decisions they make before, during, and after the code is written.
AI can help you build almost anything.
Taste tells you what is worth building.
Engineering judgment makes sure it actually works.
The developers who win this decade will not compete against AI.
They will combine AI speed with the product thinking, creativity, and technical depth that AI cannot replace.
What is one skill you believe becomes MORE valuable as AI gets better?
#FullStackDevelopment #AI #CreativeAIFlow #WebDevelopment #ProductEngineering #BuildInPublic
Writing good acceptance criteria. AI can turn a loose prompt into a lot of plausible code fast, so I spend more time defining success before the build and proving it afterward.
AI Voice Assistant | Conversational AI Agent with OpenAI, Vapi & React
Designed and developed an intelligent AI voice assistant capable of understanding natural language, maintaining conversational context, and completing user requests through natural voice interactions. The solution combines modern speech recognition, large language models (LLMs), and text-to-speech technologies to create a human-like conversational experience for web applications.
