March 2026 Summaries

Trezy's diverse career path spans from being a professional drummer and filmmaker to becoming a software engineer and open source contributor, highlighting his work with PixieJS, game development, and participation in projects like AT Proto and Blue Sky. He underscores the significance of data sovereignty for game developers and the transformative potential of decentralized platforms. Trezy also provides insightful advice for those looking to contribute to open source projects, advocating for experimentation and embracing the idea of sharing incomplete work.

Enterprises are increasingly concerned about their brands' visibility in AI-powered search engines like ChatGPT and Gemini, where traditional SEO strategies are insufficient due to the different nature of AI crawlers. Unlike Google's crawlers, which index pages based on relevance, AI crawlers aim to extract meaning and feed it into a model, often skipping over JavaScript-heavy sites that don't render content quickly enough. The solution proposed by Harper involves addressing this infrastructure issue by pre-rendering HTML snapshots for AI crawlers, ensuring they receive complete and structured content rather than a JavaScript shell. This approach enables more efficient crawling and better brand representation in AI search results, while also allowing brands to control what bots can access through tools like robots.txt and sitemap.xml. Harper's pre-rendering system can manage significant workloads, distributing rendering tasks and caching results to optimize performance. Ultimately, the strategy includes both infrastructure optimization to ensure AI crawlers can access content and traditional content strategies like structured data and clear headings, which become relevant once the delivery problem is solved, allowing brands to maintain control over their narrative in AI search environments.

The Harper platform offers a range of features to enhance web applications, including caching and low-latency roundtrips, but this guide specifically focuses on setting up basic authentication using Harper. The process involves configuring the Harper server for authentication, creating a User table schema, and utilizing the Resource API for endpoints like sign up, sign in, sign out, and authentication checks. The setup requires disabling local authorization and enabling session-based authentication in the Harper configuration file to secure user data. The guide walks through cloning an example application, setting up roles, defining the User table schema, and integrating it with Harper's API resources to manage user sessions. It details the implementation of resources for signing up, signing in, signing out, and checking user authentication, and concludes with steps to protect routes within the application, ensuring authenticated access to certain areas while redirecting users appropriately based on their authentication status.

Harper, a company recognized for its innovative digital solutions, has achieved significant milestones, including delivering substantial financial benefits to a $1B+ retailer by implementing edge-deployed acceleration, which led to a 47x return on investment without requiring platform changes. Harper has been acknowledged in the 2026 Gartner Hype Cycle for Digital Commerce as a sample vendor and won two Data Breakthrough Awards for its open-source data platform and in-memory solution. The company is noted for enhancing web personalization by addressing data delivery issues, improving HNSW vector search speed with int8 quantization, and outperforming competitors like Vercel in live app performance. Harper's approach to agentic engineering emphasizes the importance of explicit architecture for scalable AI coding, while its innovative backend solutions support diverse applications, from sandbox games to AI-friendly web optimization.

Modern application stacks are inherently complex, often comprising numerous specialized components such as databases, caches, and messaging systems, which, while individually effective, collectively create a fragmented and challenging environment for developers and AI systems. In the agentic era, where AI is increasingly involved in application design and deployment, this fragmentation poses significant coordination and security challenges. A unified runtime offers a solution by integrating core infrastructure layers—data storage, caching, messaging, and application logic—into a single environment, reducing latency, simplifying security concerns, and improving performance and scalability. This architectural approach, which is gaining traction as AI becomes more integral to development processes, contrasts with traditional fragmented stacks by facilitating easier navigation and modification by AI systems, thus enhancing development efficiency. While some may fear a return to monolithic systems, the unified runtime model maintains modularity akin to microservices but within a coherent runtime, allowing for more efficient in-memory communication and avoiding the pitfalls of microservice sprawl. As the role of AI in software development grows, the simplicity and performance benefits of unified runtimes make them an increasingly attractive option for modern infrastructure design.

Agentic AI, once experimental, is now being deployed by 28% of organizations, according to Snyk's 2026 report. These systems autonomously perform tasks beyond simple chatbot functions, raising security concerns due to the extensive access credentials required to operate on conventional stacks. Many enterprises are hesitant to grant such access, fearing security breaches, since AI tools often depend on third-party packages and components that are not thoroughly monitored. Harper presents a solution with its unified runtime architecture, which consolidates database, application logic, caching, and API serving into a single codebase, eliminating the need for extensive credentials and reducing the attack surface. This approach allows AI agents to build and test applications locally without risking access to production environments, thus aligning performance with security needs. Harper's architecture, originally designed for performance and scalability, now also addresses the credential sprawl issue, offering a pathway for enterprises to safely integrate agentic AI by ensuring applications remain secure and performant.

Harper offers a comprehensive platform for full-stack development by integrating data modeling, API generation, and runtime execution. The tutorial walks users through the creation of a simple Todo application to showcase Harper's capabilities, including how to install and configure it locally, run a Vite application within the platform, and define a schema using a schema-first approach. Users learn to deploy tables, extend them with custom Resource Classes, and connect frontends to Resource-backed REST endpoints. The tutorial emphasizes Harper's ability to automatically generate REST APIs, perform full CRUD operations, and add backend validation logic, all while maintaining a clean frontend. By using Harper's Resource API, developers can intercept REST operations, modify data, and add custom logic, providing a streamlined development experience that enhances backend extensibility and application performance.

Harper platform offers a streamlined approach to integrating REST APIs into applications, demonstrated through the setup of a todo web app. The tutorial guides users through the installation and configuration of Harper on a local development environment, highlighting its features such as in-memory cache, seamless database integration, and automatic REST API endpoint generation. Users learn to set up Harper Studio, manage applications and databases, and configure their apps to leverage Harper's capabilities. The tutorial explains the schema-first approach for creating tables and attributes, enabling efficient CRUD operations through auto-generated REST endpoints, and demonstrates how to integrate these endpoints into the application for fetching, updating, and deleting records. Additionally, it highlights the ease of development and deployment on Harper, both locally and on its cloud platform, Harper Fabric, emphasizing minimal setup requirements compared to traditional full-stack application development.