Today's Talk explores productivity challenges and solutions for AI engineers, focusing on an application called Contoso Chat. The end-to-end workflow is examined from a productivity perspective, introducing the concept of Exposure to AI. Building an AI application involves ideation, augmentation, and operationalization stages. Provisioning and setup are crucial steps, with infrastructure as code being a productivity tool. GitHub Codespaces and development containers provide consistent development environments. Azure AI Inference API allows easy iteration and prototyping. AI-assisted evaluation involves training AI models and using evaluators for grading responses. Custom evaluators can be created. Overall, the Talk emphasizes the importance of productivity throughout the AI engineer's journey.

Hello, everyone. Today we are going to explore AI-powered end-to-end testing. Unlike unit tests, UI testing has a huge layer of obstructions between the source code and the rendered UI. The source code includes HTML, CSS, and TypeScript, which are transpiled into JavaScript and bundled with tools like Webpack. AI can generate tests effectively for standard websites or blogs, but it may struggle with niche applications behind strict authorization or on-premise tools. AI-powered end-to-end testing for complex scenarios requires our guidance. We use meaningful data test IDs and follow the page objects model pattern. Additionally, we rely on useful tools like the end-to-end test helper in-browser extension and the continue IDE extension. Now, let's proceed to the demo, where we will create tests for the Pokemon application, including the ability to filter by name or type. We will navigate to the Pokemon details page and use our extension to manage settings and prompts. Additionally, we will create the details page object together and generate the test file. The Pokemon details page has 105 elements. We can view the elements for debugging purposes, including page object name, Pokemon details page, and system message. We will copy the page object and save it to a file. We need to make it exportable. Then, we will use the extension to create an end-to-end test and pass the context. I will use all the open files, including the page objects and the test case itself. I will send them to EI along with the predefined prompt. There is a system message and additional information we need to be aware of. The test runs successfully, and that concludes this part.

Today's Talk discussed integrating context into AI coding tools using the MoloContext protocol (MCP). The demos showcased the use of Conduit, an MCP tool, for bug tracking and feature addition in software development. The Talk also highlighted the use of Fetch in Cursor to summarize GitHub issues and create Jira bug reports. It demonstrated how Conduit can be used to manage issues, make code changes, and perform Git commits. Additionally, it explored the integration of Conduit with Windsurf to add a user interface for the conduit application. The Talk also touched upon implementing MCP in the AIDER AI coding system and using MCP and Windsurf for Conduit integration. Overall, it emphasized the importance of context and choosing the right tools for efficient software development workflows.

I'm Tejas Kumar, a software developer with over 20 years of experience. AI agents are defined as entities that act on behalf of users or groups to produce specific effects. Agents consist of an orchestration layer, a language model, and tools represented as JSON functions. Langflow is an open-source tool that allows users to build their own AI agents by connecting language models and tools. Composio is a tool that enhances agent capabilities by offering integrations and apps, such as Google Calendar integration. MCP (Model Context Protocol) is a way to share context with models and extend their capabilities. It allows functions to be made available to models over standard input/output or an HTTP endpoint. MCP can be used with GitHub to perform various tasks like searching and fixing code issues. The Talk covered the basics of AI agents, building agents with Langflow and enhancing them with Composio, and using MCP with GitHub. The speaker encouraged audience questions and exploration of these concepts.

Let's talk about writing your first Vip plugin. VIT, rollup, and Vip plugin are important tools in front-end development. Rollup is a bundler that can bundle JavaScript files into a single file. VIT goes through all the plugins and transforms files to JS modules. VIT and rollup have similar plugin architectures, allowing the use of existing rollup plugins in VIT. I'll discuss three plugin properties: resolve ID, load function, and more. Let's take a deeper look at the transform function. The resolve ID function determines the ID of the file or module, and the load function reads the file or module and returns its content. The transform function actually transforms the file or module into something else. For example, it can modify the code depending on the file extension. We can transform the result object into code by using object keys and map. This allows us to extract specific data and include it in the output. By making the code flexible, we can add additional information like 'built at' and utilize it for various purposes, such as displaying branch name or commit hash during deployment. You can implement various functionalities in the Vip plugin, such as reading Markdown files, implementing file-based routing, and creating domain-specific languages.

Welcome to the session on microfrontends. Microfrontends allow for independent implementations and local development. It is possible to develop and integrate microfrontends locally using an emulator and achieve automatic updates. Fine-tuning modules and user experience can be done using a discovery service. Rules can be created in the discovery service to selectively load microfrontends for specific browsers. AI can be leveraged to generate AI-enhanced variants and compare them with the original implementation. Microfrontends are highly portable and can be used in different applications. Code isolation and enhanced performance are important considerations in microfrontends. The benefits of microfrontends include improvements in file name changes and performance overhead. The Netflix application is a case study for microfrontends. Overall, microfrontends offer various benefits and opportunities for architectural discussions.

Hello everyone! I'm Anthony Fu, a coaching member of Vit, Vue, and Nuxt. Today, I'll share my findings and practices in exploring ESLink and its ecosystem. ESLink v9.0 released 7 months ago with the new FlatConfig, which simplifies plugin configuration and provides full control and customization in JavaScript. Migrate legacy config to FlatConfig with eslink-migrate-config CLI and use eslink-config-inspector for visualized step tool. Flag config utilities make config customization easier and allow project-aware configs. ESLink is a powerful AST toolkit and can be used as a formatter. Use ESLink for maintaining stylistic rules and customize it to fit your project's needs.

Hello, JS Nation! Today, I'll show you how I created gamified karaoke using Web Speech API. The Web Speech API has two parts: speech recognition and speech to text. It was originally built for karaoke but can also be used for forms and dictation. There are some quirks with the speech recognition API, such as limited microphone input and variation in implementation and privacy concerns across browsers. The speaker demonstrates how to implement speech recognition in a karaoke application and tests its error matching capabilities. Other interesting points include voice interface design considerations and the value of engaging in fun and unproductive side projects.

Hey, my name is Mikhail Levchenko. I've changed my job and became a full-time developer productivity engineer. Let me share a little story. Imagine being a wealthy trader in 15th century Europe. Delivering spices for profit was not an easy task. Middle East nations heavily taxed any traders. But the Portuguese sailed around Africa using the Mariner's Astrolabe. Fast forward, Gerardo Mercator invented a map perfectly suited for deep ocean navigation. The Dutch East India Company became the new king of the spice trade. Developer productivity is about building a cozy environment for developers, solving hard problems, and identifying process bottlenecks. It focuses on the whole development process as a product. By leveraging this perspective, you can drive change among developers and other roles. Observing developer processes as a product involves meeting stakeholders, formulating a vision, creating a model and metrics, finding productivity problems, and proposing solutions. The stakeholders include developers, CEOs, CTOs, engineering managers, and other roles involved in software development. The goal is to make everyone more productive, guided by the motto of happier developers building better software faster. There are three highlighted frameworks in this talk: DORA, DEVX, and Mertrix. DORA focuses on speed and reliability with metrics like acceleration frequency, lead time, failure rate, and recovery time. DEVX addresses the human factor with metrics related to feedback loops, cognitive load, and flow state. DX4 is a recent metric that combines DORA and DEVX, introducing proprietary metrics for top management. It includes a failure rate to encompass reliability and a percentage of time spent on new features. Engineer-developed metrics like the reliability metrics from Dora and the percentage of time spent on new features are valuable additions. Talking to top management about changes is made easier with a cool metric. Research concerning metrics, consult stakeholders, and read literature to improve understanding. Try prototypes before developing custom tools as a last resort. Confirm success with empirical metrics. Release managers often feel constantly interrupted and overwhelmed by the task of supervising a release. Sharing the role with the entire team proved to be ineffective, leading to forgotten procedures. Automation and streamlining of the release process improved satisfaction and reduced delayed releases. Make developer productivity part of company goals and culture code. Advocate for developers to top management. Drive change by starting small, experimenting, and using tools as a last resort. Find ways to make teammates more productive.