Emmanuel Agbavwe's Work | ContraWork by Emmanuel Agbavwe
Emmanuel Agbavwe

Emmanuel Agbavwe

Web3 Dev: Bridging tech logic & users via collaboration.

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Cover image for iGetAlgo: Automated Web3 Platform &
iGetAlgo: Automated Web3 Platform & DeFi Ecosystem I gave life to the iTools ecosystem, transforming static design concepts into a fully functional suite of DeFi applications on the Algorand Blockchain. While collaborating with designers, I was solely responsible for engineering the entire logic, backend automation, and blockchain integration that powers the platform. Membership Automation & Data Integrity 100% Member Validity: Engineered a robust, automated validation system using CRON jobs to handle periodic membership checks. Backend Infrastructure: Developed the supporting logic using an Upstash database to ensure high-performance data retrieval and secure user-status management. System Reliability: Built the foundational logic that ensures premium features and rewards remain accurate and secure without manual oversight. iTools: The Functional Core I built out the entire logic and functionality for the iTools suite, ensuring real-time accuracy for all on-chain data: iStake: Developed the functional logic for the RETI Staking dashboard, including live on-chain data fetching for node status, block probability, and staker leaderboards. iSwap: Engineered a non-custodial trading interface by integrating the Haystack router API to aggregate liquidity and provide optimal trade rates. iSwim: Developed the data-driven portal for Tinyman liquidity pools, calculating and visualizing TVL and APY for various Algorand Standard Assets (ASAs). Key Technical Contributions Blockchain Engineering: Implemented the secure frontend logic required to interact with the Algorand SDK for wallet connectivity and transaction management. Logic-to-UI Integration: Translated high-fidelity designs into a "pixel-perfect" responsive experience, ensuring complex financial data remained legible and interactive. Performance Optimization: Leveraged specialized data-fetching and caching strategies to keep live financial charts and leaderboards accurate during high-traffic periods.
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Cover image for Ghetto Market: High-Performance NFT &
Ghetto Market: High-Performance NFT & Digital Marketplace I developed Ghetto Market, the primary digital marketplace for the Ghetto Pigeons project. The core challenge was building a visually intensive platform using Next.js that maintained elite performance levels despite a heavy load of high-resolution digital assets. Long-Term Strategic Development Iterative Partnership: Managed the project’s technical evolution over a 12-month period, maintaining consistent progress while adapting to the client's pace and payment milestones. Agile Scope Management: Successfully executed numerous design and functional alterations, demonstrating the flexibility to pivot features while ensuring the final product remained aligned with the project owner's vision. Stakeholder Collaboration: Engaged in regular meetings to translate evolving business requirements into technical solutions that stayed relevant to the target audience. Key Contributions & Impact Custom Image Rendering Engine: Developed a high-efficiency solution using the Intersection Observer API combined with native HTML elements. This allowed for "lazy loading" that significantly reduced bandwidth consumption and improved initial page load times. Performance Engineering: Successfully navigated Vercel’s optimization limits by implementing intelligent media handling, ensuring the site remained fast and responsive even during high-traffic periods. Frontend Architecture: Utilized Next.js paired with Modular CSS to create a scalable, maintainable codebase that allows for "pixel-perfect" responsiveness across all devices. Web3 Synergy: Integrated the frontend with blockchain-backed assets, providing a seamless browsing experience for users interacting with the Ghetto Pigeons ecosystem.
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Cover image for ViewReward:
I led the technical journey
ViewReward: I led the technical journey of ViewReward, a learn-to-earn platform on the Algorand Blockchain, through two major architectural phases. This evolution focused on transforming a functional proof-of-concept into a production-ready application optimized for speed and user retention. - The Technical Evolution: Version 1 (React.js): Developed the initial MVP focusing on core blockchain connectivity and the "learn-to-earn" logic. Version 2 (Next.js Migration): Completely re-engineered the platform using Next.js. This move was driven by a need for better SEO, faster First Contentful Paint (FCP), and a more scalable structure. - Key Achievements: Token Visibility Engine: Built a custom token preview flow that allowed users to easily identify and verify reward tokens, directly leading to an increase in daily active users and time-on-site. Performance Optimization: Reduced page load times and improved the user experience by implementing Next.js-specific optimizations like image handling and route pre-fetching. Web3 Integration: Maintained seamless integration with the Algorand wallet and smart contracts across both versions, ensuring a secure and transparent earning process.
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