JS Nation

JSNation 2023

This talk explores the use of AI in web development, including tools like GitHub Copilot and Fig for CLI commands. AI can generate boilerplate code, provide context-aware solutions, and generate dummy data. It can also assist with CSS selectors and regexes, and be integrated into applications. AI is used to enhance the podcast experience by transcribing episodes and providing JSON data. The talk also discusses formatting AI output, crafting requests, and analyzing embeddings for similarity.

In this talk, we'll take a look at the growing intersection of AI and web development. There's a lot of buzz around the potential uses of AI in writing, understanding, and debugging code, and integrating it into our applications is becoming easier and more affordable. But there are also questions about the future of AI in app development, and whether it will make us more productive or take our jobs. There's a lot of excitement, skepticism, and concern about the rise of AI in web development. We'll explore the real potential for AI in creating new web development frameworks, and separate fact from fiction. So if you're interested in the future of web development and the role of AI in it, this talk is for you. Oh, and this talk abstract was written by AI after I gave it several of my unstructured thoughts.

AI and Web Development: Hype or Reality

Wes Bos

Productivity Conference for Devs and Tech Leaders

Productivity Conf for Devs and Tech Leaders

Today's workshop focused on using AI tools in software development, particularly the AI tool Copilot. The session highlighted the benefits and limitations of AI tools, emphasizing the importance of context and specific test cases for optimal results. AI tools like Copilot can be useful for solving data structure and algorithmic problems, especially in job interviews. They are most effective when working in familiar languages or frameworks and can assist with boilerplate code and repeating patterns. However, it is essential to be mindful of code quality and tech debt and not overly rely on AI suggestions. Pair programming with AI and following TDD principles can enhance code quality and knowledge sharing. The session also covered refactoring and implementing the Fibonacci sequence, exploring AI model options, facilitating breakout rooms for collaboration, and using property testing to validate code. Overall, the workshop highlighted the potential of AI tools in software development while emphasizing the need for human guidance and review.

"Test, Code, Repeat: Master AI-Assisted Development" introduces developers to a transformative way of coding with AI as a collaborative partner. This workshop focuses on how iterative workflows, such as the ping pong pairing technique, enable an enhanced interaction between human creativity and AI efficiency.

Test, Code, Repeat: Mastering AI-Assisted Development

Marco Pierobon

Welcome to Chad GPT, Unleashed, Revolutionizing Web Development. I'll share my journey and lessons learned about GPT-03-Mini-High. TLDR: Good with slower-changing technologies, poor with rapidly moving ones. Let's test the application by building a vision board. User stories, requirements, acceptance criteria, and design principles were well-executed. Mobile responsiveness, accessibility, security, and scalability are important. LLM struggled with error handling and installation, but we managed to troubleshoot. The app creation process was painful, but we created a better version. Some end-to-end tests failed. Automated tests didn't consider challenges and project structure. Continuous integration failed during deployment, but manual deployment worked. Majority of LLM tools worked. AI's impact on hiring: current roles remain, but new hires are affected. AI enhances my abilities, reducing the need for hiring. Thank you for your time.

In this engaging talk, we will delve into the journey of building, testing, and deploying a web app while examining the capabilities and limitations of ChatGPT in web development. Through the lens of this comprehensive process, we will explore how AI-driven development techniques can contribute to a more efficient workflow and discuss the challenges that may arise. Attendees will gain a deeper understanding of how to effectively incorporate ChatGPT into their projects, focusing on striking the right balance between automation and manual efforts. Join us as we navigate the ever-evolving landscape of web development and investigate the role of AI in shaping our development strategies.

ChatGPT Unleashed: Revolutionizing Web Development from Idea to Deployment

Nikolay	Advolodkin

Today's Talk introduces Amazon Q Developer, an AI-powered conversational assistant that assists with software development lifecycle (SDLC) tasks. The speaker demonstrates building a 2048 game using Q Developer, which automatically detects the codebase and implements logic for the front end. The agent also generates tests for the code and helps identify bugs. Q Developer can generate documentation by analyzing the code and facilitate code reviews to find security vulnerabilities. The session covers error handling, deployment using AWS SAM, and debugging with Q Developer and CloudWatch. The speaker plans to deploy the application on EC2 in the future.

In this talk, we'll to cover key features of Amazon Q Developer and demonstrate how it can enhance a developer’s workflow. The session will include live demos of:<ul><li>/dev</li><li>@workspace</li><li>Code Scan</li><li>@git and @history from Q-Cli</li></ul>We’ll also showcase real-world customer case studies to highlight the practical applications of these features.

Supercharging Your Developer Workflow with Amazon Q Developer

Vikash Agrawal 

Abeetha Bala

Hello, everyone. I'm Mansa Hari, and I'm very excited to open the session on how AI can automate 70% of code review and reduce the burden on developers. AI can cut review time, automate PR suggestions, and identify code issues. Implementing AI code reviews can reduce manual review time, ensure high code quality, and accelerate development cycles. The future of AI in code reviews includes understanding business logic, intuitive code suggestions, and hybrid AI-human reviews. Tools like Co-Pilot can be used to automate code review tasks and improve code quality.

AI-driven code review tools are transforming the development lifecycle by automating repetitive checks and highlighting code smells. This session will explore how AI reduces manual effort, improves detection accuracy, and enhances the overall quality of code.

How AI Can Automate 70% of Code Review: Reducing Burden and Improving Code Quality

Manasa Hari

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.

This talk demonstrates how developers can get the most out of AI coding assistants by effectively managing the context they provide. Through practical examples with three popular assistants—Aider, Cursor, and Windsurf—I’ll show how to configure global and local context, manage it in real-time, and overcome common limitations. Attendees will also learn how to extend the assistants’ capabilities with a centralized knowledge service to maximize their productivity and accelerate software delivery.

Managing Context in AI Coding Assistants: Achieve Better Results with Fewer Hallucinations

Tim Kitchens

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.

Building generative AI applications requires a GenAIOps mindset that takes you on a journey from model selection to prompt ideation, prototype evaluation, and app deployment. In this talk, we’ll explore the GenAIOps journey from an AI Engineer perspective and identify productivity challenges, and the tooling solutions that can mitigate these issues and help streamline their developer experience.

AI Engineer End-to-End Workflow: Productivity Challenges and Their Solutions

Nitya Narasimhan

I'll walk through some of the ways I set up Cursor to help speed up my full stack workflow. The main thing to check is indexing the code base. Cursor also looks at the get graph file relationships. Another important setting is large context, which allows absorbing larger files and multiple files of context in the prompt window. Iterating on lints helps find and fix errors faster. Web search tools and uploading your own docs are also available to enhance the prompt window. These are all preferences, including auto select, YOLO mode, and models. Rules are also crucial as they guide the model to understand your workflow. Implement best practice error handling and adjust rules as the models and system prompts change. MCPs like sequential thinking, Postgres SQL, and Puppeteer help refine thoughts and automate workflows. Creating a product requirements document in a .md file allows AI to ground itself in project information. The game was successfully implemented and all items were checked off. Debugging strategies involve adding debug logs to help identify issues. Use commit messages to provide clear documentation for changes. Demonstrating the use of AI in debugging by setting up and utilizing debug logs. Showcasing the benefits of providing debug information to resolve issues. Overview of various topics including indexing rules, linting, MCPs, PRDs, tech stacks, and checklists.

Cursor is a breakthrough AI integrated development environment that enables rapid prototyping via its composer agentic mode.  In this talk I'll cover how to maximize productivity with Cursor from tips and tricks to complete nearly hands off workflows. By the end of this talk you’ll understand techniques such as using modular checklists to build tests, using and indexing docs, cursor rules, when to commit, roll back strategies to reduce hallucinations and Devops scripts the active cursor LLM can write and use to keep the code honest.

How to Master Cursor for Rapid Development

Mike Mikula

In this Talk, the speaker discusses the importance of analyzing bugs in software development. Analyzing bugs goes beyond just counting them; it helps improve processes, understand root causes, and gain insights through machine learning. The Talk emphasizes the need for proper communication with bugs and the importance of preparing the bug analysis environment. Automation and visualization can improve bug analysis efficiency, and a comprehensive analysis of different metrics is necessary to gain insights for improvement. The Talk also highlights examples of bug analysis and the use of machine learning for pattern recognition. Bug severity estimation using machine learning algorithms and the use of clustering for bug analysis are also mentioned. Overall, the Talk provides valuable insights on bug analysis and its role in improving software quality and productivity.

Is communication with bugs possible? It is important to understand them because there is valuable information underlying the bugs of software, and it promises quality improvements. Let's talk about how we can analyze reported issues to improve the future of the product by means of Artificial Intelligence.

Can Machines Learn Bug Language?

Mesut Durukal

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.

Think being an IC limits your impact? Think again. In this talk, we’ll explore Developer Productivity Engineering (DPE)—a growing field that’s all about making developers happier and helping them ship better software faster. This session will introduce the foundational principles of DPE, explore the SPACE framework, and teach you how to apply your engineering skills beyond just code. Expect to navigate through real-world case studies and gain insights from personal experiences. This session is your guide to leveling up your influence while staying true to the IC path.

Leveraging Developer Productivity Engineering Practices for Greater Impact as an IC

Mikhail Levchenko

Today's Talk introduces the use of large language models (LLMs) to enhance front-end development. LLMs can act like our brains by maximizing the good parts and minimizing the bad parts. A demo in Cursor, an IDE, showcases how LLMs can be used with the builder.io Figma plugin. The Talk emphasizes the automation of tasks, such as adding a settings button and resolving errors, with the AI agent. Feedback and manual verification are crucial to ensure desired results. Tests and continuous iteration are recommended for stronger guarantees of correctness. Monitoring and guiding the AI agents is important to stay on track. Connecting to other tools like Figma and using AI prompting can further enhance code generation. The CLI enables code base integration and parallel development. Visual prototyping and seamless updates are possible with the Builder tool. Overall, the Talk highlights how LLMs can revolutionize front-end development by automating tasks, improving efficiency, and facilitating collaboration.

AI tools are changing how we design, build, and test user interfaces. This talk looks at current AI technologies that are improving the frontend development process and how to use them, including:- Using Visual Copilot to convert Figma designs into production-ready code;- Implementing AI agents for automated code writing and testing;- Real-world examples showing how AI tools can improve development speed and joy.

AI-Powered Frontend Development: Building Better UIs Faster

Steve Sewell

Hello, Productivity Conference. We are Winsurf, a brand new AI-native code editor. Today, I'm going to show you how the product works, the guiding principles behind its development, and some tips and tricks on using AI in development workflows. Our agent is a powerful tool that abstracts away grunt work, making developers focus on building and shipping great products. It performs background research, predicts next steps, and automates decision-making. Windsurf integrates deeply into the application, understanding what you're doing and providing tools to achieve your goals. The agent can remember instructions and behave like an extension of yourself. Building for the future of intelligence, Windsurf aims to improve productivity and revolutionize coding with AI agents.

How Windsurf Breaks Through the Celling for Retrieval

Kevin Hou

Hello, welcome to my presentation on building your own Node system. I want to share my tips and mistakes so you can learn from them. Having a personalized system is valuable. I use a combination of Bullet Journal and Apple Notes. Logstick is my current system and I love it because it allows easy creation of notes and tags. The four core things that make a system work are engagement, easy search and retrieval, frictionless addition of new notes, and feeling supported. Note-taking provides peace of mind and eliminates the need to remember and search for information. Customize your note system to suit your preferences. Experiment with different note-taking apps and find one that works for you. Consistency matters more than the tool you use.

Do you feel overwhelmed by complex note-taking systems or frustrated by the endless search for the "perfect" app? In this talk, I'll show you how to create a personalized notes system that works for *you*, helping you organize your thoughts, manage your work, and focus on what really matters—whether you're coding, studying, or planning your next creative project.

Notes System That Will Let You Thrive: Craft Your Own Path to Productivity

Joanna Otmianowska

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.

In this talk, we will explore how to offload work to large language models and automate away most "busy work" in order to maximize and enhance productivity on a daily basis. We will do so mainly by exploring how LLMs can callfunctions.

Maximize Productivity with AI Agents

Tejas Kumar

Hello, everyone. My name is Krzysztof, and I will be talking today about developer tools, AI, and how we use both of those to create the next generation of developer tools. GitHub Copilot, released in 2021, revolutionized developer tools by automating boring parts of coding and keeping developers in a state of flow. Suggestions are shown directly in the editor and clearly separated from the real code. Chat interfaces, like Chat GPT, solve quality of response issues and are useful when flow doesn't exist. The next generation of tools focuses on structured exchange, user control, and iteration. GitHub Spark allows users to create small applications without focusing on code. Designing applications with the user in mind and handling ambiguity is important. Real-world software tasks require human guidance, and exploring new ideas beyond chat-based AI is necessary. Always consider the human aspect and ethical considerations when using AI-powered features.

AI has already changed software development. Tools like GitHub Copilot have become ubiquitous parts of the workflow of millions of developers. Like other well-known editor features (like autocomplete or tooltips), AI-in-editor increases productivity, reduces required context switching, and lets developers stay in the flow while focusing on important parts of their job. However, this was just a first step—with the rapid developments of large language models (LLMs), which have become more powerful and knowledgeable with every release and have excellent reasoning capabilities, we can do more. Nowadays, we see AI tools able to solve complex, repository-wide tasks or even generate whole applications. In the talk, I will demo some new AI tools coming from GitHub Next, such as Copilot Workspace or GitHub Spark. We will discuss emerging UX patterns, give advice on how to build your own AI tool and peek into the future of developer tools. All that while trying to answer the most important question—how to design applications using AI with humans in mind.

Building the Next Generation of AI Developer Tools

Krzysztof Cieślak

Today's Talk discussed the potential of AI to enhance managerial productivity. The importance of frameworks and Git in coding was emphasized, as well as the need to stay updated with new technologies. Various AI tools and their use cases were mentioned, with a focus on data security. The benefits of using AI agents and case templates for project management were highlighted. AI tools for presentations, automation, and bias in AI models were also discussed. The limitations of AI and ethical considerations were mentioned, emphasizing the need for human creativity and accountability. Overall, the Talk provided valuable insights into the role of AI in software development and engineering.

AI promises to revolutionise productivity for managers, from aiding in creative problem-solving and research to improving prioritisation and decision-making support. But can AI really help us stay unbiased? And how do we ensure its safe use without risking sensitive company data? This talk explores actionable strategies for leveraging AI tools effectively while maintaining ethical standards and safeguarding information. You'll leave with insights on whether AI can truly optimise your work and how to integrate it safely and responsibly in your managerial practices.

Can AI Truly Enhance Manager Productivity?

Vasilika Klimova

Today, we will use the clean coder framework to write a simple web application. Clean coder is a framework that aims to replace human programmers with AI by offloading most programming tasks. It is designed to be an autonomous programmer that can build applications overnight. It includes intelligent agents, such as a two-step planner agent and a front-end feedback agent. To configure CleanCoder, provide the Antropic API key, OpenAI API key, project folder path, and Todoist API key. CleanCoder can be used with Next.js and other applications. We can automate coding tasks, create projects, and set code and product rules. CleanCoder also has debugging and code control features. It allows for semantic search and enhances the coding process. CleanCoder is compatible with Next.js, FastAPI, Vue.js, and potentially C-Sharp. Future updates will include an improved manager agent and regular application updates.

Imagine replacing yourself with a multi-agent AI programmer to develop your production web application. That's exactly what we did at my startup takzyli.pl. To achieve this, we designed and used the Clean Coder - AI agent framework for autonomous code writing (https://github.com/GregorD1A1/Clean-Coder-AI), which is hopefully open-source project. If it worked for us, why shouldn't it work for you?In this workshop, I'll show you how to create an entire web application in an (almost) autonomous way and drastically reduce the time you or your employees spend on writing code.

How to Create a Web Application in an (Almost) Autonomous Way Using Clean Coder

Grigorij Dudnik

React Summit

React Summit 2024

Today's Talk covers native features in browsers, including upcoming ones and the Interop Project. Native features offer speed, compatibility, and improved debugging. Notable examples include dynamic viewport units, flexbox/grid gap, container queries, and motion path. The Interop Project ensures consistent web platform features across different browsers. Upcoming features like native CSS nesting and entry/exit animations are on the horizon.

Most developers closely follow the framework wars. So busy with these games, that we forget to check what new features HTML, CSS, and JavaScript offer us. Native modals, dynamic viewport units, and optional chaining are just some of the features you should use already! If you stopped following Web Platform development in 2015, it's time to refresh your knowledge. I will teach you to build applications tailored to 2024 and prepare you for the new Web Platform features that will appear in the coming years.

Webdevelopment Tailored for 2024

Andrzej Fricze

TechLead Conference

TechLead Conference 2024

The Talk discusses the challenges of dealing with people in software development and engineering. It offers debugging tools for human interactions, emphasizes taking ownership of one's actions and reactions, and recognizing power dynamics. The importance of setting boundaries for work-life balance and privacy at work is highlighted. Strategies for managing emotions and dysregulation are provided, along with techniques for repairing relationship ruptures. The Talk concludes by emphasizing the importance of relationship debugging tools and continuous personal growth.

“Hell is other people.” There are many talks on how to get started as an engineer and how to step into management, but there are few talks about how to be an adult in (professional) relationships. I’ve spent my career in small companies and startups, FAANG organizations, and opensource communities. Each of these spaces demands different things of the people in them, yet across these spaces all succeed and fail along the fault lines of a core set of soft skills: regulating emotions, setting boundaries, framing experiences productively, and letting go. In this talk, I share everything I’ve learned in my career that has helped my colleagues, mentees, and friends so that you may navigate the most difficult part of tech—people—with grace, empathy, and safety.

Managing Ourselves Managing Each Other

Rachel Nabors

React Summit US

React Summit US 2023

This Talk discusses the journey from thousands of Lint failures to zero in a codebase at Linton that is over 80 years old. The approach involved implementing rules, incentives, and tooling to address the issue. The tool called Checkup was used to visualize ESLint failures by team and lint rule, providing accountability and responsibility. The efforts resulted in cleaning up over 6,000 lint failures, with 55 contributors, and a 30% increase in perceived code quality.

Lint rules enable us to uphold code quality and minimize errors. It can positively impact developer productivity and happiness especially when working in a massive application with multiple teams working together. But what if your large scale application contains thousands of lint failures over the many years it has been running in production? This talk will explore actionable strategies for effectively addressing lint failures at scale so that we can once again rely on lint rules to ensure consistent code quality and streamline development processes, leading to a more robust and maintainable codebase.

Road to Zero Lint Failures: Tackling Code Quality Challenges at Scale

Chris Ng

Setting up the system and separating concerns are important in software development. Modular construction and prefab units are a new trend that makes construction quicker and easier. Architectural complexity can lead to a drop in productivity and an increase in defects. Measuring architectural complexity can help identify natural modules in the code. Best practices for avoiding architectural complexity include organizing code by business domain and using prop drilling. Atomic design and organizing a monorepo are recommended approaches for managing architectural complexity.

Prop drilling is fine. Duplication is great. Long functions are love. We talk a lot about bad complicated code because it’s easy to see the problem. But research shows engineers can work around self-contained bad code just fine. What really trips them up is something else entirely – architectural complexity. Architectural complexity makes your code hard to work with, causes 3x more bugs, halves productivity, and may even cause devs to ragequit. In this talk we explore what you can do.

Forget Bad Code, Focus on the System

Swizec Teller

React Summit 2023

GitHub Copilot is an auto-completion tool that provides suggestions based on context. Research has shown that developers using Copilot feel less frustrated, spend less time searching externally, and experience less mental effort on repetitive tasks. Copilot can generate code for various tasks, including adding modals, testing, and refactoring. It is a useful tool for improving productivity and saving time, especially for junior developers and those working in unfamiliar domains. Security concerns have been addressed with optional data sharing and different versions for individuals and businesses.

GitHub Copilot is an AI pair programmer that can help you write code faster and spend less time writing repetitive code.This session will cover some interesting use cases for Copilot that could shine a light on its possibilities. This ranges from prompting Copilot to suggest a function based on a comment, learning how to use a new framework, tackling a security or accessibility bug, better documenting your code, translating  code from one language to another, etc.Agenda: Introduction to CoPilot - What is Copilot - How can you use it - How it can help you write code faster - Copilot Labs experimental features I will pick examples from the React ecosystem and show how we can fix Security Vulnerabilities and Accessibility issues in some components.

Improving Developer Happiness with AI

Senna Parsa

TechLead Conference 2023

This Talk discusses the measurement and interpretation of tech lead, focusing on tech debt. Tech debt is a tool to temporarily speed up development but can have negative consequences if not managed properly. Various tech debt metrics, including heuristic metrics and second-tier metrics, can help identify and manage tech debt. Tech debt interest is crucial for measuring the impact of tech debt and allows for prioritization. It is important to collect and analyze tech debt metrics to ensure software and team health.

Hardly any people in Tech like when there's a lot of tech debt. And most of us would like when there's not too much of it. But how do we understand how much exactly we have of it? Where exactly does it sit? Which part of it is actually the most annoying? What would be the benefit for us if we spend time getting rid of it? When it comes to planning how you tackle your tech debt, all these questions deserve answers. Especially when we're asked about the ROI on our efforts to eliminate some annoying legacy stuff and build a new shiny module or service. Also, when we work on tech debt, we do want to tackle the most impactful parts of it first, don't we? This talk is about all of that: how we measure our tech debt, how we interpret the results of these measurements so that they give us the answers to the right questions, and how we guide our decision making with those answers.

A Quick and Complete Guide to Measuring Your Tech Debt and Using the Results

Anton Kazakov

This Talk discusses the foundation, formation, and iteration of process, emphasizing the benefits and building trust. It highlights the importance of optimizing processes, using life cycles and meetings to streamline workflow and avoid mistakes. Exposing work through demos and documentation fosters collaboration and provides more exposure opportunities. The Talk also emphasizes concise communication, tailoring processes to individual team members, and addressing challenges through effective communication. Automation is recommended to save time and streamline workflow, while maintaining a balance with personal interactions.

One way to get a good groan from your team is to mention the word “process”. Engineers in particular worry that process will mean their momentum will get slowed or halted, and usually have experience to justify that worry. With an understanding of workflow and high-level individualization, this doesn’t have to be the case. As a tech lead and now manager that has converted many process skeptics, I’m excited to show you my processes for process.

Processes for the Process-Averse

Tara Z. Manicsic

JSNation 2022

The Talk discusses imposter syndrome and reframes it as being a professional imposter. It emphasizes the importance of sharing and starting, embracing imposterism, and building inclusively for the web. The speaker shares personal experiences of being an imposter in various technical disciplines and highlights the significance of accessibility. The Talk concludes with the idea of building a collective RPG game to remove excuses for not making things accessible.

You know what impostor syndrome is, right!? Most all of us have felt that nagging feeling that we're faking it and that we're sure to be found out by all the experts around us at any moment.But before you go assuming this talk is the same ol' song and dance full of platitudes that encourage you to ignore that syndrome, let me clue you in on a little secret: there's no experts around you. Impostorism is not a syndrome at all, it's a pragmatic mindset and perspective, one we should all embrace and be proud of. In fact, it's vital to us getting our jobs done.

Confessions from an Impostor

Kyle Simpson

JSNation Live

JSNation Live 2020

This Talk discusses the speaker's coding journey, forming habits, and finding time for coding. The speaker recommends participating in the 100 days of code challenge and learning HTML, CSS, JavaScript, AngularJS, and D3.js. Building small projects and games is helpful for learning and growth. The importance of forming habits and overcoming resistance is emphasized, along with prioritizing consistency and focusing on details. Finding time is about reclaiming the 24 hours we all have and making small changes to accommodate coding. Keeping a log or notebook is important for tracking progress.

In this session, I am going to share my story on how I started coding, how I make time to work on side projects and how you can grow and advance in your career. After this talk, I hope you'll be inspired to work smarter, make new habits and continue pushing yourself even when things fall apart. I will present some helpful tips about self-motivation, time management, setting priorities and goals, staying organized, believing in yourself and keeping a balance between your career and personal life. Additionally, in this session, we are going to talk about building the habit of coding and the benefits of it. We are going to explore ways of finding mentors in your job and outside of it and also expanding your social network. This talk is not only about getting better at your 9 to 5 job but also about developing yourself. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

When You Think There Is No Time for Learning or Coding

Eleftheria Batsou

React Summit 2020

Kent C. Dodds discusses the consume, build, and teach approach to learning and upgrading oneself in a software development career. He emphasizes the importance of consuming curated content, learning from others, and applying different learning methods. Kent shares his experiences in creating personal projects, building projects to understand technologies, and learning through projects. He highlights the power of teaching, the benefits of learning clubs, and the importance of balancing personal life and learning. Kent also introduces Epic React, his workshop-focused approach to teaching React. 

How do you level up? How do you jumpstart your learning when getting into something new? Nobody has more than 24 hours a day, so how do you maximize the impact of your limited time? In this keynote, I'm going to tell you a bit of my own story, and some tips and tricks that I've learned so you can be as productive as you can be at learning new things and solidifying that knowledge so it's there when you need it. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

Consume ➡️ Build ➡️ Teach

Kent C. Dodds

JSNation Live 2021

The Talk covers various tips and features of using VS Code, including the command palette, Zen mode, external terminals, and debugging. It also highlights advanced editing and refactoring features, Git integration, and the use of dev containers. The speaker demonstrates how to set up a dev container for a Python app, run code in a container, and create and configure dev containers. The benefits of using dev containers are also discussed, such as eliminating manual configuration, handling dependencies, and facilitating team-based development.

How do you debug so easily in VS Code? How do codespaces work? What are those key combinations to edit code so quickly? What extensions are the ones I shouldn't code without? Get ready to hit the ground running in this fast-paced, demo-heavy talk that takes you through some of the best and most effective tips and tricks in VS Code. Learn how to setup your environment and customize it the way you like it. You'll walk out with several tips on how to be more efficient with one of the hottest tools on the Web today! <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

VS Code Can Do That!

John Papa

ReTool is a platform that focuses on building internal tools quickly. It offers easy integrations with databases and APIs, supports custom React components and JavaScript libraries, and provides extensive support and deployment options. Developers can try it out at retool.com.

Retool is a front-end as a service tool that is similar to React and can be 10x faster than coding a web app from scratch. We’ll focus on how and why it is used for internal tools at some of the fastest growing companies and take a minute to walk through how it works, where it’s a good fit and where it’s not. <a href="https://www.froala.com/wysiwyg-editor?pb=1"> </a>

#productivity