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Just set up a Playwright + Cucumber + TypeScript framework with parallel execution, HTML reports, and Azure DevOps CI/CD integration. Happy to help any team struggling with flaky tests or framework setup. Feel free to reach out!
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Fluffless: Deterministic AI Proposal Engine
Project Overview / TL;DR
A high-performance Next.js web application that forces LLMs to write hyper-direct, senior-level technical pitches by anchoring generation to a persistent, client-side profile vault.
The Problem:
The freelance market is flooded with generic, AI-generated proposals that read like bloated cover letters. Clients ignore them because they lack technical depth and focus on "marketing fluff" rather than execution. Additionally, existing tools create massive UX friction by forcing users to manually re-type their past work experience for every single pitch.
The Solution:
I architected and deployed Fluffless to solve both the output quality and the user friction. I bypassed standard AI wrappers to build a constraints-based engine that only generates technically sound, highly specific proposals.
Key Technical Execution:
Client-Side "Profile Vault": To eliminate repetitive data entry, I engineered a persistent LocalStorage architecture. Users input their raw technical resume once, and the application silently passes this base context to the AI for all future generations, reducing user input to just the target job description.
Heavyweight AI & Prompt Engineering: I integrated the Groq API utilizing the massive Llama-3.3-70B reasoning model. I engineered a strict, one-shot prompt architecture loaded with negative constraints to completely strip out default "AI-speak" (e.g., words like leverage, delve, seamless) and force a rigid 4-step psychological sales structure (Hook -> Proof -> Execution -> Technical CTA).
Native Streaming Architecture: When the standard Vercel AI SDK introduced silent failures due to protocol mismatches, I bypassed the abstraction entirely. I built a custom, native JavaScript fetch and TextDecoder implementation to guarantee 100% stable, low-latency text streaming directly to the UI.
My Role:
Lead Full-Stack Developer & Prompt Engineer
Tools & Technologies:
Next.js (App Router)
React
Tailwind CSS
Groq API (Llama-3.3-70B)
Vercel
Project Links:
Live Site: https://fluffless.vercel.app/
Nice work🔥👏
AI Agent Platform Light UI Landing Page with 3D Hero
A clean, minimal landing page built for an AI agent orchestration platform. Light aesthetic with holographic 3D product visuals, soft purple gradient background, and a full set of conversion sections.
Sections included:
3D holographic hero with stats bar
Features grid Cloud runs, Task monitoring, Memory & Context, Scalable Permissions)
Plug and play agents section with 4 use cases and metrics
4 step onboarding flow (Define, Compose, Test, Deploy)
Integrations / tools section
Fully responsive
Perfect for: AI platforms, automation tools, agent builders, SaaS startups
LiveDemo: https://agentfy.netlify.app/
Beautiful work 👍
Hey Contra community 👋
8 years in, and I still love the moment when a messy problem clicks into a clean solution.
I'm a full-stack developer with deep roots in PHP (Laravel & Symfony) and modern JavaScript React on the frontend, Node.js on the backend. I've built everything from monolithic enterprise apps to event-driven microservices.
What I actually enjoy: taking ambiguous product ideas and turning them into solid, maintainable systems. Architecture decisions, API design, database modeling that's where I spend most of my energy.
Open to contract work with teams who care about code quality, not just shipping fast.
What's everyone working on? Always curious to connect.
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