General

Accessibility Work and Its Impact on Future AI

Published Oct 28, 2019

Updated Feb 14, 2023

5 min read

This article was written over 18 months ago and may contain information that is out of date. Some content may be relevant but please refer to the relevant official documentation or available resources for the latest information.

If you have ever had trouble reading something due to the size or color of font used, or had a hard time hearing the person next to you at a loud concert, then you have had the same accessibility experience many with disabilities deal with every day.

Those with sight, hearing, and motion impairments have a harder time getting access to information on the web. The main problem is most websites do not design with these use cases in mind.

There are approximately 1 billion people around the world that have some form of a disability according to the World Health Organization. What this means is as high as 15% of the world’s population are unable to effectively use a large number of websites on the web.

How can we ensure all users have equal access to content? How can developers, as they create websites, express themselves inclusively on the web?

Accessibility work, also known as a11y, strives to improve the web experience for those with disabilities in an effort to ensure web content and experiences are available and equal for everyone.

Rob Dodson, a Developer Advocate for Chrome at Google, is one of the advocates working to better web accessibility.

Fundamentally, accessibility is defined as a person’s ability to be able to access something, whether that be information, physical access, or even the ability to work comfortably. When we speak of accessibility for the web, we usually mean technical access, which includes the ability to read a web page, book a plane ticket online, or order food from a website. The goal for accessibility work is to help people interact with their environment and remove the impediments a person may experience in doing so.

It is easy for those without disabilities or impairments to take things like vision for granted. If you are able to effectively see your computer screen and consume information, you don’t think about how your experience might be impacted if you could not see the website you are viewing.

Most accessibility problems stem from user experience design, and can even be as simple as color contrast on a website. If text on a page has low contrast with the background color, it’s not just an access issue but also a usability issue; anyone viewing the page will have a hard time seeing the content clearly.

User efficiency also comes in to play when designing websites for accessibility. When considering the experience for users with motor impairments, or persons with a limited range of motion, it becomes more apparent as to why we need to be considering accessibility. These users may only be able to move a finger to activate a switch device, or use a similar sip and puff device to navigate the page. For these users, the ability to skip a menu and use the site with less button clicks becomes fundamental for efficient navigation.

But we must look further than the simple goal of helping everyone have equal access to the web. Accessibility is one of the key pieces in building the future of the web. If we look to many of the cutting edge products today, we begin to realize that many such as Amazon Alexa or Google Home began as accessibility technology. As AI becomes more integrated into our everyday lives, we often take for granted the text to speech capabilities we rely on was once only used for a calculator for the blind.

In following this concept of how accessibility work accelerates advancement of technology, we must take note of the significance of semantics when developing websites. Adding semantics to a web page will not only improve the experience for visually impaired or blind users today by improving the ability for screen and braille readers to work effectively, but it may also help lay a foundation for how future AIs understand and interact with our pages. As we build AIs, we must train them and teach them what it means to be a web page, and this comes with adding semantics.

Voice interactions, a technology increasingly relied on for communicating with digital assistants and AIs, are also an assistive technology. Voice interaction allows users with motor or vision impairments to access content and perform certain actions more easily than having to directly manipulate a switch device or screen reader. And much like voice interaction technology may help a blind person navigate the world around them they cannot see, it also can help tell users where to go in a foreign country where they cannot read or understand the native language.

Soon, AI will be able to help us around our homes. Ideas like this are being beta tested today. If Amazon Alexa were able to reliably help a user fix a toilet or install plumbing while the user was working on a project, we will have successfully leaped into the future. With more semantic content available for AI to consume, enablement of this type of assistance could be possible faster.

While developers work harder to understand the importance of accessibility, bodies such as WAI-ARIA (Web Accessibility Initiative — Accessible Rich Internet Applications) and WCAG 2.0 (Web Content Accessibility Guidelines) are working on improving web standards. Currently tools like aXe and WAVE can be used today to help audit a site to see how well it meets these standards.

Though still in the standardizing phase, there is hope in early accessibility work in JavaScript that will hopefully have a large impact in the accessibility community. Items like the inert attribute for HTML will make it easier to build accessibility modal dialogs. Focus-ring and evangelizing the importance of, is key for users with motor impairments.

To learn more about accessibility, you can check out a11ycasts, a YouTube show Rob produces focused on accessibility and his free accessibility udacity course.

This Dot is a consultancy dedicated to guiding companies through their modernization and digital transformation journeys. Specializing in replatforming, modernizing, and launching new initiatives, we stand out by taking true ownership of your engineering projects.

We love helping teams with projects that have missed their deadlines or helping keep your strategic digital initiatives on course. Check out our case studies and our clients that trust us with their engineering.

About the author(s)

Tracy Lee
Partner, This Dot Google Developer Expert (Angular, TC39, Web) RxJS Core Team & Lead for RxJS Learning Team Contributor to Angular, RxJS, EmberJS

Key Strengths:
- Teaching developer relations strategies
- Influencer marketing
- Developing brands
- Community strategies and maintenance
- Creating product launch strategies
- Leading marketing operations efforts & standards
- Effective conference presence & speaking strategies
@ladyleet @ladyleet

Increasing development velocity with Cursor

If you’re a developer, you’ve probably heard of Cursor by now and have either tried it out or are just curious to learn more about it. Cursor is a fork of VSCode with a ton of powerful AI/LLM-powered features added on. For around $20/month, I think it’s the best value in the AI coding space. Tech giants like Shopify and smaller companies like This Dot Labs have purchased Cursor subscriptions for their developers with the goal of increased productivity. I have been using Cursor heavily for a few months now and am excited to share how it’s impacted me personally. In this post, we will cover some of the basic features, use cases, and I’ll share some tips and tricks I’ve learned along the way. If you love coding and building like me, I hope this post will help you unleash some of the superpowers Cursor’s AI coding features make possible. Let’s jump right in! Cursor 101 The core tools of the Cursor tool belt are Autocomplete, Ask, and Agent. Feature: Autocomplete The first thing that got me hooked was Autocomplete. It just worked so much better than the tools I had used previously, like GitHub Copilot. It was quicker and smarter, and I could immediately notice the amount of keystrokes that it was saving me. This feature is great because it doesn’t really require any work or skilled prompting from the user. There are a couple of tricks for getting a little bit more out of it that I will share later, but for now, just enjoy the ride! Feature: Ask If you’ve interacted with AI/LLMs before, like ChatGPT - this is what the Ask feature is. It’s just a chat feature you can easily provide context to from your code base and choose which Model to chat with. This feature is best suited for just asking more general questions that you might have queried Google or Stack Overflow for in the past. It’s also good for planning how to implement a feature you’re working on. After chatting or planning, you can switch directly to Agent mode to pick up and take action on something you were cooking up in Ask mode. Here’s an example of planning a simple tic-tac-toe game implementation using the Ask feature: Feature: Agent Agent mode lets the AI model take the wheel and write code, make edits, or take other similar actions on your code base. The goal is that you can write prompts and give instructions, and the Agent can generate the code and build features or even entire applications for you. With great power comes great responsibility. Agents are a feature where the more you put into them, the more you get out. The more skilled you become in using them by providing better prompts and including the right context, you will continue to get better results. The AI doesn’t always get it right, but the fact that the models and the users are both getting better is exciting. Throughout this post, I will share the best use cases, tips, and tricks I have found using Cursor Agent. Here’s an example using the Agent to execute the implementation details of the tic-tac-toe game we planned using Ask: Core Concept: Context After understanding the features and the basics of prompting, context is the most important thing for getting the best results out of Cursor. In Cursor and in general, whenever you’re prompting a chat or an agent, you want to make sure that it has all the relevant information that it needs to provide an answer or result. Cursor, by default, always has some context of your code. It indexes your code base and usually keeps the open buffer in the context window at the very least. At the top left of the Ask or Agent panel, there is an @ button, and next to that are badges for all the current items that have been explicitly added to the context for the current session. The @ button has a dropdown that allows you to add files, folders, web links, past chats, git commits, and more to the context. Before you prompt, always make sure you add the relevant content it needs as context so that it has everything it needs to provide the best response. Settings and Rules Cursor has its own settings page, which you can access through Cursor → Settings → Cursor Settings. This is where you log in to your account, manage various features, and enable or disable models. In the General section, there is an option for Privacy Mode. This is one setting in particular I recommend enabling. Aside from that, just explore around and see what’s available. Models The model you use is just as important as your prompt and the context that you provide. Models are the underlying AI/LLM used to process your input. The most well-known is GPT-4o, the default model for ChatGPT. There are a lot of different models available, and Cursor provides access to most of them out of the box. Model pricing A lot of the most common models, like GPT-4o or Sonnet 3.5/3.7, are included in your Cursor subscription. Some models like o1 and Sonnet 3.7 MAX are considered premium models, and you will be billed for usage for these. Be sure to pay attention to which models you are using so you don’t get any surprise bills. Choosing a Model Some models are better suited for certain tasks than others. You can configure which models are enabled in the Cursor Settings. If you are planning out a big feature or trying to solve some complex logic issue, you may want to use one of the thinking models, like o1, o3-mini, or Deep Seek R1. For most coding tasks and as a good default, I recommend using Sonnet 3.5 or 3.7. The great thing about Cursor is that you have the options available right in your editor. The most important piece of advice that I can give in this post is to keep trying things out and experimenting. Try out different models for different tasks, get a feel for it, and find what works for you. Use cases Agents and LLM models are still far from perfect. That being said, there are already a lot of tasks they are very good at. The more effective you are with these tools, the more you will be able to get done in a shorter amount of time. Generating test cases Have some code that you would like unit tested? Cursor is very good at generating test cases and assertions for your code. The fewer barriers there are to testing a piece of code, the better the result you will get. So, try your best to write code that is easily testable! If testing the code requires some mocks or other pieces to work, do your best to provide it the context and instructions it needs before writing the tests. Always review the test cases! There could be errors or test cases that don’t make sense. Most of the time, it will get you pretty close to where you want to be. Here’s an example of using the Agent mode to install packages for testing and generate unit tests for the tic-tac-toe game logic: Generating documentation This is another thing we know AI models are good at - summarizing large chunks of information. Make sure it has the context of whatever you want to document. This one, in particular, is really great because historically, keeping documentation up to date is a rare and challenging practice. Here’s an example of using the Agent mode to generate documentation for the tic-tac-toe game: Code review There are a lot of up-and-coming tools outside of Cursor that can handle this. For example, GitHub now has Copilot integrated in pull requests for code reviews. It’s never a bad idea to have whatever change set you’re looking to commit reviewed and inspected before pushing it up to the remote, though. You can provide your unstaged changes or even specific commits as context to a Cursor Ask or Agent prompt. Getting up to speed in a new code base Being able to query a codebase with the power of LLM’s is truly fantastic. It can be a great help to get up to speed in a large new codebase quickly. Some example prompts: > Please provide an overview of this project and how to get started developing with it > I need to make some changes to the way that notifications are grouped in the UI, please provide a detailed analysis and pseudo code outlining how the grouping algorithm works If you have a question about the code base, ask Cursor! Refactoring Refactoring code in a code base is a much quicker process in Cursor. You can execute refactors depending on their scope in a couple of distinct ways. For refactors that don’t span a lot of files or are less complex, you can probably get away with just using the autocomplete. For example, if you make a change to something in a file and there are several instances of the same pattern following, the autocomplete will quickly pick up on this and help you tab through the changes. If you switch to another file, this information will still be in context and can be continued most of the time. For larger refactors spanning several files, using the Agent feature will most likely be the quickest way to get it done. Add all the files you plan to make changes to the Agent tab’s context window. Provide specific instructions and/or a basic example of how to execute the refactor. Let the Agent work, if it doesn’t get it exactly right initially, you can always give it corrections in a follow-up prompt. Generating new code/features This is the big promise of AI agents and the one with the most room for mixed results. My main recommendation here is to keep experimenting. Keep learning to prompt more effectively, compare results from different models, and pay attention to the results you get from each use case. I personally get the best results building new features in small, focused chunks of work. It can also be helpful to have a dialog with the Ask feature first to plan out the feature's details that the Agent can follow up on and implement. If there are existing patterns in your codebase for accomplishing certain things, provide this information in your prompts and make sure to add the relevant code to the context. For example, if you’re adding a new form to the web page and you have other similar forms that handle validation and making back-end calls in the same way, Cursor can base the code for the new feature on this. Example prompt: Generate a form for creating a new post, follow similar patterns from the create user profile form, and look to the post schema for the fields that should be included. Remember that you can always follow up with additional prompts if you aren’t quite happy with the results of the first.. If the results are close but need to be adjusted in some way, let the agent know in the next prompt. You may find that for some things, it just doesn’t do well yet. Mentally note these things and try to get to a place where you can intuit when to reach for the Agent feature or just write some of the code the old-fashioned way. Tips and tricks The more you use Cursor, the more you will find little ways to get more out of it. Here are some of the tips and patterns that I find particularly useful in my day-to-day work. Generating UI with screenshots You can attach images to your prompts that the models can understand using computer vision. To the left of the send button, there is a little button to attach an image from your computer. This functionality is incredibly useful for generating UI code, whether you are giving it an example UI as a reference for generating new UI in your application or providing a screenshot of existing UI in your application and prompting it to change details in reference to the image. Cursor Rules Cursor Rules allow you to add additional information that the LLM models might need to provide the best possible experience in your codebase. You can create global rules as well as project-specific ones. An example use case is if your project has some updated dependency with newer APIs than the one on which the LLM has been trained. I ran into this when adding Tailwind v4 to a project; the models are always generating code based on Tailwind v3 or earlier. Here’s how we can add a rules file to handle this use case: ` If you want to see some more examples, check out the awesome-cursorrules repository. Summary Learn to use Cursor and similar tools to enhance your development process. It may not give you actual superpowers, but it may feel like it. All the features and tools we’ve covered in this post come together to provide an amazing experience for developing all types of software and applications....

Apr 18, 2025

11 mins

AICursor

“It Sounds a Little Dystopian, But Also Kind of Amazing”: Conversations on Long Term AI Agents and "Winning" Product Hunt with Ellie Zubrowski

Ellie Zubrowski doesn’t walk a traditional path. In the three years since graduating from a university program in Business Administration, she biked across the U.S., studied Kung Fu in China, learned Mandarin just for fun, and completed the #100DaysOfCode challenge after deciding she wanted a career switch. That same sense of curiosity and willingness to jump into the unknown now fuels her work as a Developer Advocate at Pieces, where she leads product launches, mentors job seekers, and helps developers learn how to best leverage Pieces’ Long-Term Memory Agent. Her journey into tech was guided not just by a want to learn how to code and break into the industry, but by a fascination with the structure of language itself. > “There are so many parallels between human languages and programming languages,” she says. “That realization really made me fall in love with software.” > We spoke with Ellie about launching a #1 Product Hunt release, her predictions for AI agents, and why conferences don’t have to break your budget. Launching LTM-2 to the Top of Product Hunt Recently, Ellie led the launch of Pieces’ Long-Term Memory Agent (LTM-2), which took the top spot on Product Hunt—a major win for the team and their community. > “I’m super competitive,” she admits. “So I really wanted us to win.” The launch was fully organic—no paid promotions, just coordinated team efforts, a well-prepared content pipeline, and an ambassador program that brought in authentic engagement across X, Discord, and Reddit. She documented their entire strategy in this blog post, and credits the success not just to good planning but to a passionate developer community that believed in the product. Following a successful performance at Product Hunt, Ellie is committed to keeping Pieces’ user community engaged and contributing to its technological ecosystem. > “Although I’m still fairly new to DevRel (coming up on a year at Pieces!), I think success comes down to a few things: developer adoption and retention, user feedback, community engagement, and maintaining communication with engineering.” Why AI Agents Are the Next Big Thing Ellie sees a major shift on the horizon: AI that doesn’t wait for a prompt. > “The biggest trend of 2025 seems to be AI agents,” she explains, “or AI that acts proactively instead of reactively.” Until now, most of us have had to tell AI exactly what to do—whether that’s drafting emails, debugging code, or generating images. But Ellie imagines a near future where AI tools act more like intelligent teammates than assistants—running locally, deeply personalized, and working in the background to handle the repetitive stuff. > “Imagine something that knows how you work and quietly handles your busy work while you focus on the creative parts,” she says. “It sounds a little dystopian, but also kind of amazing.” Whether we hit that level of autonomy in 2025 or (likely) have to wait until 2026, she believes the move toward agentic AI is inevitable—and it’s changing how developers think about productivity, ownership, and trust. You can read more of Ellie’s 2025 LLM predictions here! The Secret to Free Conferences (and Winning the GitHub Claw Machine) Ellie will be the first to tell you: attending a tech conference can be a total game-changer. “Attending my first tech conference completely changed my career trajectory,” she says. “It honestly changed my life.” And the best part? You might not even need to pay for a ticket. > “Most conferences offer scholarship tickets,” Ellie explains. “And if you’re active in dev communities, there are always giveaways. You just have to know where to look.” In her early days of job hunting, Ellie made it to multiple conferences for free (minus travel and lodging)—which she recommends to anyone trying to break into tech. Also, she lives for conference swag. One of her all-time favorite moments? Winning a GitHub Octocat from the claw machine at RenderATL. > “She’s one of my prized possessions,” Ellie laughs. Proof here. 🐙 Her advice: if you’re even a little curious about going to a conference—go. Show up. Say hi to someone new. You never know what connection might shape your next step. Ellie’s Journeys Away from her Desk Earlier this year, Ellie took a break from product launches and developer events to visit China for Chinese New Year with her boyfriend’s family—and turned the trip into a mix of sightseeing, food adventures, and a personal mission: document every cat she met. (You can follow the full feline thread here 🐱) The trip took them through Beijing, Nanjing, Taiyuan, Yuci, Zhùmǎdiàn, and Yangzhou, where they explored palaces, museums, and even soaked in a hot spring once reserved for emperors. > “Fancy, right?” Ellie jokes. But the real highlight? The food. > “China has some of the best food in the world,” she says. “And lucky for me, my boyfriend’s dad is an amazing cook—every meal felt like a five-star experience.” What’s Next? With a YouTube series on the way, thousands of developers reached through her workshops, and an eye on the next generation of AI tooling, Ellie Zubrowski is loving her experience as a developer advocate. Follow @elliezub on X to stay in the loop on her work, travels, tech experiments, and the occasional Octocat sighting. She’s building in public, cheering on other devs, and always down to share what she’s learning along the way. Learn more about Pieces, the long-term LLM agent. Sticker Illustration by Jacob Ashley...

Mar 28, 2025

4 mins

AIArtificial Intelligence

Intro to DevRel: 5 Reasons Why DevRel Teams Fail

Although Developer Relations (DevRel) defies traditional marketing strategies, prioritizing enhancing developer satisfaction ahead of promoting numbers that contribute to a sales funnel, it is still possible for DevRel teams to fail at delivering desired business objectives. And unfortunately, more often than not, this leads to the dissolution of DevRel efforts, and sometimes even role elimination. Below, I’ve compiled a list of five of the top reasons why DevRel teams fail. 1. Lack of Leadership Buy-In DevRel requires buy-in and support from executives and stakeholders within the company. Without buy-in, being able to work cross-functionally across the organization, get access to data needed for measuring success, have the ability to influence change within the organization, or get the budget for necessary activities to engage developers will be impossible. I asked Jason Lengstorf, the host and founder of Learn With Jason and previously on the Developer Relations team at Netlify and Gatsby, where he has seen companies fail at DevRel before: “Companies that want to invest in DevRel can collect as many well-known developers as they can, but giving them zero dollars and zero autonomy will force teams to rage quit or become content farms because that’s all you can do with no budget.” Other examples are departments not willing to share or give data that helps enable DevRel to understand the metrics they need to effectively baseline and track the success of their efforts. By not doing so, the DevRel team will not be able to justify their work to leadership, which will lead to those positions being cut first when budget cuts come around. Chris Woodruff, Founder of Advocatus, a Developer Relations consultancy, says “DevRel is seeing a lot of layoffs. It’s the easiest team for management to let go because they don’t fully understand the ROI and metrics. These are the holy grails of DevRel, and because they do not understand, they will always be the first teams to let go if management can’t see the actual return or how it affects the bottom line.” 2. Company Culture Fit If an organization's culture does not value collaboration and resists the presence of a DevRel team, DevRel will not be able to effectively advocate for developers or help teams be more successful with their target audience. Francesco Tisiot, Senior Developer Advocate at Aiven, an open-source data platform that makes setting up cloud databases simple, shared one of his experiences in his Developer Relations career. “I was one of the first DevRel hires in a company and we were in the marketing organization. Initially, there was pushback from engineering and product teams on our product feedback and feature requests since we weren't seen as experts. But, DevRel is about breaking barriers and building bridges, so, in leading by example, we demonstrated our technical knowledge and now have a strong impact on all the teams.” Michael Liendo, Senior Developer Advocate at AWS, an online platform by Amazon that provides scalable and cost-effective cloud computing solutions, shared how he was able to find the company culture fit within organizations he has served in the past. Being in a position of Developer Advocacy, and quite literally trying to advocate for developers that use the platform, he says, “Some of the biggest challenges for DevRel are actually internal. Engineers at many companies often focus on one piece of the product. As they're testing features, they may be creating workarounds without realizing they're workarounds. This means they often miss what a proper Developer Experience flow looks like. I've had to push for them to include me in design meetings, and get them to understand that I'm the Lorax--I speak for the community! A phrase I have been known to say is ‘this solves the problem, but it's not a solution’. I'm known for having a high bar for what is considered ‘good enough’ and though the end result is accumulated trust, it's a challenge to get there.” 3. Operating in Isolation DevRel cannot operate in isolation without integration with development, marketing, product teams, sales, or a subset of these. The team will struggle to make a significant impact. DevRel requires a collaborative approach and alignment and synergy with other teams. Francesco Ciulla, Developer Advocate at daily.dev, a professional network for developers that provides the latest tech news and articles, shares his thoughts on how DevRel organizations can be successful within larger organizations: “DevRel organizations can thrive within larger organizations by establishing clear communication channels and fostering meaningful collaborations. They must align their objectives with the company's goals and illustrate their value by sharing tangible outcomes from developer engagement.” 4. Lack of Strategy Proceeding into DevRel without a clear strategy will make it difficult for a DevRel team to establish its purpose within an organization and set priorities that will make an impact. There will not be a clear vision the team can drive towards, leading to wasted efforts and the inability to produce tangible outcomes. If DevRel does not have any goals set, they can only do their best to assume what efforts they should invest in to provide value to the organization. Worst yet, if they do not have any goals set, they may not choose to focus on providing value to the organization, but to a community that the organization has no interest in. Many DevRel experts have seen this happen time and time again in the community, and are always left scratching our heads. Many times, the “strategy” for an organization is to hire DevRel, but that is where the strategy stops. Decision-makers want DevRel professionals to come in and just “do what they do best”. Unfortunately, when decision-makers say this, they typically have an idea of what outcomes they want DevRel to drive, but don’t want to share those thoughts because they feel like DevRel professionals should know what to do. Expectations left open to interpretation often lead to a poor impression of the performance of the DevRel team by decision-makers, and those teams are never able to establish a sense of trust or direction within that organization. Jeremy Meiss, former Director of Developer Relations at CircleCI, says, “One of the biggest problems we have seen in this industry is the startups that were counseled by their VC, founders, or board that they need a DevRel team because the other similar companies had one and it was great for them. They push for it, and one of the early hires is DevRel. Generally, that DevRel hire is someone relatively new in the industry, so you can coax them to start at a new company without clear goals or objectives. New hires like this come in without a lot of experience in the field of DevRel and have not experienced it at different levels of companies. They are heavily pushed by marketing, the CEO, the CTO, and other departments into thinking DevRel should look a certain way, but don’t have the foundational knowledge to be able to push back because they are not yet in this area.” Jeremy’s illustrative explanation of why a lack of strategy ultimately results in the failure of a DevRel team within an organization is one that is common across many devtool startups that have popped up in recent years. 5. Lack of Metrics and Reporting A well-rounded set of DevRel metrics typically comes from multiple areas of the organization, whether that be marketing, sales, product, customer success, or customer support. Without free access to cross-functional team data, it is difficult to show the value and ROI of DevRel. Establishing a baseline set of metrics if you’re new within an organization, or understanding the baseline metrics that currently exist is critical in ensuring the success of your job in DevRel. Tessa Mero, Head of Developer Relations at Appwrite, has a very specific set of metrics her team focuses on. She shared a few of those metrics: - Growth of our GitHub Repo (stars) - Growth of our Discord Community - Improved engagement in Discord community - Growth of our Twitter followers and engagement - Growth of our Appwrite Cloud developers - Number of views or impressions on any video and written content, whether it's internal or externally created - Amount of content created weekly (written or video) - Number of projects created with Appwrite for Hackathon sponsorships - Number of attendees / questions at a conference talk - Number of connections at conferences - Number of community support questions answered, improving rate of responses AND rate of how fast we respond, in all public forums - Number of support tickets responded to - Number of community feedback taken and moved into our DX/Product discussions - Number of feedback from UI/UX perspectives and working with design team to follow up with the devs/users with what we did with the feedback - Number of engagement/activity from our Appwrite heroes/ambassadors This is just one example of and a subset of metrics a DevRel team should consider tracking, but what you track and how you track it is dependent on your goals and the product. Metrics and what your leadership considers a good ROI can vary greatly from organization to organization. I spoke to another Developer Relations expert in the industry and she shared her experience with the company she just left and the reason she left - and it was focused around metrics. She was initially interested in joining the team because of the lack of metrics. However, over time, as she got more experience and as she became more visible, her workload became difficult to prioritize. Since there were no metrics, there were no objectives to measure against to say what was good and what was bad. She felt like she didn’t know what she was doing well or not doing well. Once metrics began to be implemented, the company started pushing her to do more, and she had nothing to push back with because the high-level goals were not there. There was no way to prioritize the workload. The company started tracking things like page hits, unique visitors, unique views of videos, number of subscribers, activity on twitter, and other similar numbers, but it was hard to tie any of these back to the ROI for the company. How do you quantify and determine if 100 new subscribers on YouTube is better than 100 new subscribers on twitter? If you can’t quantify it, how do you prioritize it? What Successful DevRel Teams Do Differently With the nature of DevRel and the multitude of levers and factors that determine success and failure, it’s important to allow space for a team or set of individuals to experiment and iterate before making judgment calls. One company that serves millions of developers on its platform is starting up a new meetup program and testing the ROI of sponsoring meetups around the world. Since they are in the testing and experimentation phase, they don’t yet know how to measure success, and that is clear to leadership. The current strategy is sponsoring local meetups for a few months and seeing what the result is. Why are they so seemingly laid back in their approach? Is it the right approach? The reason for the relaxed nature of the testing phase is that they don’t want to be pushy to the meetup organizer to find something out or measure something. They are not expecting anything, but will evaluate what metrics they could use to establish success criteria. This approach is a thoughtful and empathetic one, and clearly, the DevRel team has an understanding of how to approach community members in a way that will not turn them off. Internally, the simple numbers they are looking at are the number of RSVPs, the number of attendees that show up, and the difference between the two. DevRel is naturally iterative and requires a team to experiment, test, and refine their strategies. Effectively engaging developers is not black and white, and a strategy that works for one community or company may not necessarily work for another. Furthermore, building domain expertise and gaining a deep understanding of the developer community they serve takes time. Experimentation and iteration help teams refine their knowledge, identify patterns, and develop strategies that resonate with developers. This expertise becomes an asset in driving long-term success. It’s also important to acknowledge that building domain expertise within a segment as well as building relationships and trust with developers in that segment takes time. The technology landscape changes quickly and new technologies are being released weekly. Developer sentiment is fickle and changes just as quickly regarding favored approaches and products. That being said, the above pitfalls remain common causes for DevRel teams to fail, and by remaining mindful of and vigilant against them, DevRel teams both new and old can succeed in supporting key business objectives like developer retention, community growth, and product development....

Feb 14, 2024

9 mins

DevRel

“Music and code have a lot in common,” freeCodeCamp’s Jessica Wilkins on what the tech community is doing right to onboard new software engineers

Before she was a software developer at freeCodeCamp, Jessica Wilkins was a classically trained clarinetist performing across the country. Her days were filled with rehearsals, concerts, and teaching, and she hadn’t considered a tech career until the world changed in 2020. > “When the pandemic hit, most of my gigs were canceled,” she says. “I suddenly had time on my hands and an idea for a site I wanted to build.” That site, a tribute to Black musicians in classical and jazz music, turned into much more than a personal project. It opened the door to a whole new career where her creative instincts and curiosity could thrive just as much as they had in music. Now at freeCodeCamp, Jessica maintains and develops the very JavaScript curriculum that has helped her and millions of developers around the world. We spoke with Jessica about her advice for JavaScript learners, why musicians make great developers, and how inclusive communities are helping more women thrive in tech. Jessica’s Top 3 JavaScript Skill Picks for 2025 If you ask Jessica what it takes to succeed as a JavaScript developer in 2025, she won’t point you straight to the newest library or trend. Instead, she lists three skills that sound simple, but take real time to build: > “Learning how to ask questions and research when you get stuck. Learning how to read error messages. And having a strong foundation in the fundamentals” She says those skills don’t come from shortcuts or shiny tools. They come from building. > “Start with small projects and keep building,” she says. “Books like You Don’t Know JS help you understand the theory, but experience comes from writing and shipping code. You learn a lot by doing.” And don’t forget the people around you. > “Meetups and conferences are amazing,” she adds. “You’ll pick up things faster, get feedback, and make friends who are learning alongside you.” Why So Many Musicians End Up in Tech A musical past like Jessica’s isn’t unheard of in the JavaScript industry. In fact, she’s noticed a surprising number of musicians making the leap into software. > “I think it’s because music and code have a lot in common,” she says. “They both require creativity, pattern recognition, problem-solving… and you can really get into flow when you’re deep in either one.” That crossover between artistry and logic feels like home to people who’ve lived in both worlds. What the Tech Community Is Getting Right Jessica has seen both the challenges and the wins when it comes to supporting women in tech. > “There’s still a lot of toxicity in some corners,” she says. “But the communities that are doing it right—like Women Who Code, Women in Tech, and Virtual Coffee—create safe, supportive spaces to grow and share experiences.” She believes those spaces aren’t just helpful, but they’re essential. > “Having a network makes a huge difference, especially early in your career.” What’s Next for Jessica Wilkins? With a catalog of published articles, open-source projects under her belt, and a growing audience of devs following her journey, Jessica is just getting started. She’s still writing. Still mentoring. Still building. And still proving that creativity doesn’t stop at the orchestra pit—it just finds a new stage. Follow Jessica Wilkins on X and Linkedin to keep up with her work in tech, her musical roots, and whatever she’s building next. Sticker illustration by Jacob Ashley....

Apr 25, 2025

3 mins

JavaScriptSoftware Engineering

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