DEV Community: Scot Gardner

Staying Organized as a Solo Developer: A Lesson in Time Management

Scot Gardner — Thu, 30 Jul 2026 13:00:12 +0000

As a solo developer building small, useful tools like Trial Guard, I've learned the importance of staying organized and managing my time effectively. With a community of over 3,965,806 amazing developers on DEV, it's easy to get caught up in the latest trends and technologies, but sometimes it's the simple things that can make the biggest difference.

I recall a time when I was working on a new feature for Trial Guard, a menu bar app that sends reminders for upcoming paid subscriptions, and I completely forgot about a free trial I had signed up for. The next thing I knew, I had been charged for a full year of service. It was a frustrating experience, and it's exactly why I built Trial Guard in the first place.

From a technical standpoint, one of the challenges I faced while building Trial Guard was implementing a reliable reminder system. I ended up using a combination of NSTimer and NSCalendar to schedule reminders, which has proven to be effective in ensuring that users receive timely notifications before they get charged. For example, I used the following code to schedule a reminder:

let timer = Timer(fireAt: reminderDate, interval: 0, target: self, selector: #selector(sendReminder), userInfo: nil, repeats: false)

One lesson I've learned from building and using Trial Guard is the importance of having a system in place to manage subscriptions and free trials. As developers, we often sign up for multiple services and tools, and it can be easy to lose track of what we've signed up for. By using a tool like Trial Guard, which sends up to three reminders before a paid subscription kicks in, we can avoid unexpected charges and stay focused on our work. With Trial Guard available for just $0.99, it's a small price to pay for the peace of mind that comes with knowing you'll never forget about a free trial again. You can check it out at https://go.sg1-labs.us/trialguard.

Building a Community Around Small but Mighty Tools

Scot Gardner — Mon, 27 Jul 2026 13:00:03 +0000

As a solo developer, I've learned that building a community around your work is just as important as the work itself. I've been fortunate enough to connect with many of you through my indie Mac app studio, SG1 Labs, and I'm constantly inspired by the creative ways you use my tools to streamline your workflows. One such tool is TalkBoard, which I built to simplify dictation, quick fixes, and clipboard management - essentially, the three features I found myself using most in other apps like Raycast Pro.

I recall a particular instance where I was working on a project in my RV, and I needed to quickly dictate some notes. I realized that I was jumping between multiple apps to get the job done, and that's when the idea for TalkBoard struck me. I wanted to create a tool that would allow users to focus on their work without the distractions of multiple apps. From a technical standpoint, one of the challenges I faced while building TalkBoard was implementing a seamless dictation experience. I achieved this by utilizing the NSSpeechRecognizer framework, which provides a robust and efficient way to recognize spoken words. By leveraging this framework, I was able to create a dictation feature that is both accurate and responsive.

One lesson I've learned from building and sharing TalkBoard with the community is the importance of listening to user feedback. By engaging with users and incorporating their suggestions, I've been able to iterate and improve the tool to better meet their needs. If you're interested in trying out TalkBoard, you can find it at https://go.sg1-labs.us/talkboard. As a community, let's continue to support and learn from each other, and I look forward to hearing about the creative ways you're using tools like TalkBoard to simplify your workflows.

SOLSTICE — feed the light, hold back the night (an ode to Alan Turing)

Scot Gardner — Thu, 23 Jul 2026 13:00:20 +0000

As I sit here in my RV, coding away on my latest project, I'm reminded of the wise words of Alan Turing, who said, "We can only see a short distance ahead, but we can see plenty there that needs to be done." This quote resonates with me, especially when it comes to the state of AI-generated code. I recall a particularly frustrating experience where I had to manually refactor a massive codebase generated by an AI model, only to realize that a tool like SlopClean could have saved me hours of work.

One of the key challenges in working with AI-generated code is that it often prioritizes functionality over maintainability. The code is typically a tangled mess of conditional statements and loops, making it difficult to understand and modify. However, by applying principles of modular design and separation of concerns, we can transform this "slop" into maintainable architecture. For instance, when using SlopClean, I've found that organizing code into smaller, independent modules makes it easier to debug and extend.

A technical insight that has helped me in this process is the concept of "code hygiene." This refers to the practice of writing code that is easy to read, understand, and modify. By enforcing strict naming conventions, removing unnecessary complexity, and using design patterns, we can create code that is not only functional but also maintainable. SlopClean's ability to run locally with oMLX and transform AI-generated code into production-ready code has been a game-changer for me, allowing me to focus on higher-level design decisions rather than getting bogged down in tedious refactoring.

One lesson I've learned from working with AI-generated code is the importance of striking a balance between automation and human judgment. While AI models can generate code quickly and efficiently, they often lack the nuance and context that a human developer can provide. By using tools like SlopClean to clean up and organize AI-generated code, we can create a more sustainable and maintainable codebase that will serve us well in the long run. As Alan Turing would say, "We can only see a short distance ahead," but with the right tools and mindset, we can create a brighter future for ourselves and our code.

What I Learned Switching Between Swift and AI Studio in the Same Week

Scot Gardner — Mon, 20 Jul 2026 13:00:04 +0000

As a solo developer building small, useful tools like Tab Reminder, my Chrome extension for scheduling tabs to reopen later, I often find myself switching between different programming languages and environments. Recently, I had to switch between Swift for a Mac app project and AI Studio for a machine learning experiment in the same week. This experience taught me a valuable lesson about the importance of context switching and how it can impact my productivity.

I recall a particular day when I was working on a feature for Tab Reminder, trying to debug an issue with the scheduling algorithm. I had spent hours staring at the Swift code, but couldn't seem to find the problem. I took a break and worked on my AI Studio project for a few hours, and when I came back to the Swift code, I was able to spot the issue immediately. This experience made me realize that taking a break and working on a different project can help me approach problems with a fresh perspective.

One technical insight I gained from this experience is the importance of using design patterns to reduce cognitive overhead when switching between languages. For example, using the Repository pattern in Swift and a similar pattern in AI Studio helped me to focus on the business logic of the application, rather than the language-specific details. This allowed me to switch between the two environments more easily and focus on the tasks at hand.

The lesson I learned from this experience is that context switching can be a powerful tool for increasing productivity, but it requires intentional effort to manage. By using design patterns and taking breaks to work on different projects, I can come back to my code with a fresh perspective and tackle problems more effectively. Whether I'm working on Tab Reminder or another project, this lesson has helped me to stay focused and deliver high-quality results.

Building the Smallest Real App to Demonstrate DigitalOcean

Scot Gardner — Thu, 16 Jul 2026 13:00:06 +0000

As a solo developer, I'm often asked about my workflow and the tools I use to build and deploy my apps, like Tab Reminder, a Chrome extension that helps users schedule tabs to reopen later. Recently, some friends wanted to see how I use DigitalOcean, so I decided to build them the smallest real app I could. The goal was to create something functional, yet minimal, to illustrate the basics of deploying an app on DigitalOcean.

I started by creating a simple to-do list app, focusing on the core functionality that would allow users to add and remove items. As I worked on the app, I realized that one of the key challenges was handling the persistence of data. This is where I applied a technical insight that has helped me in many of my projects, including Tab Reminder: using a simple, yet robust, data storage solution. In the case of the to-do list app, I used a lightweight database that could handle the small amount of data the app would store.

One of the lessons I learned from this exercise was the importance of keeping things simple, especially when demonstrating a concept or tool to others. By building the smallest real app possible, I was able to focus on the essential aspects of using DigitalOcean, without overwhelming my friends with unnecessary features or complexity. This approach also helped me to identify potential issues and areas for improvement, much like how I iterate on Tab Reminder to ensure it remains a useful tool for users who need to schedule tabs to reopen later. The experience reminded me that sometimes, less is more, and that building small, functional apps can be a great way to learn and teach others about new tools and technologies.

Dawn or Eclipse — a code-breaking ode to Turing you can't outsource to the machine

Scot Gardner — Mon, 13 Jul 2026 13:00:04 +0000

As I sat in my RV, sipping coffee and staring at lines of code, I couldn't help but think of Alan Turing. The father of computer science, Turing's work on the theoretical foundations of modern computer science is still widely influential today. I've always been fascinated by the story of how he cracked the Enigma code, and how that achievement played a significant role in the Allied victory in World War II. This got me thinking about the balance between human intuition and machine automation in our work as developers.

One particular challenge I faced while building Tab Reminder, a Chrome extension that allows users to schedule tabs to reopen later, was finding the right balance between automation and user input. From a technical standpoint, implementing the scheduling feature required a deep dive into Chrome's extension APIs, particularly the alarms API. I had to ensure that the extension could reliably store and retrieve scheduled tabs, even when the user closed their browser or restarted their computer. The key insight here was using the alarms API to trigger a background script that would reopen the scheduled tabs at the specified time.

One lesson I learned from this experience is that while automation can greatly simplify many tasks, there are still areas where human judgment and oversight are essential. For instance, when a user schedules a tab to reopen, they may have specific intentions or context in mind that the machine can't fully understand. By providing a simple, intuitive interface for scheduling tabs, Tab Reminder fills a gap that more automated solutions might overlook. You can try it out for yourself at https://go.sg1-labs.us/tab-reminder. As developers, we must recognize the limitations of automation and ensure that our tools and applications are designed to augment, rather than replace, human capabilities.

When Software Started Writing Software: A Developer’s History of AI

Scot Gardner — Thu, 09 Jul 2026 13:00:04 +0000

As I sit in my RV, coding away on my latest project, I often think about how far we've come in the world of software development. I recall a time when I was struggling to deploy a simple website, wasting hours on configuration and git pushes. That's when I created ShipDrop, a one-click hosting solution that allows vibe coders to drag, drop, and deploy their projects in seconds. While ShipDrop isn't directly related to AI, it has given me the freedom to explore more complex topics, like the history of AI in software development.

One interesting insight I've gained from my research is the concept of "meta-programming," where software generates other software. This idea has been around since the 1960s, but it has gained significant traction in recent years with the rise of machine learning and artificial intelligence. For instance, I've been experimenting with using AI-generated code to automate repetitive tasks in my own projects. By leveraging libraries like TensorFlow, I can create models that generate boilerplate code, freeing me up to focus on more complex problems.

One lesson I've learned from my journey into AI is the importance of understanding the underlying mechanics of the technology. As developers, it's easy to get caught up in the hype surrounding AI and machine learning, but it's crucial to take a step back and appreciate the intricacies of these systems. By doing so, we can create more efficient, effective, and robust solutions that augment our abilities as developers, rather than replacing them. With tools like ShipDrop streamlining my deployment process, I can focus on exploring the frontiers of AI and its applications in software development, and I'm excited to see where this journey takes me.

The Principle of Least AI

Scot Gardner — Mon, 06 Jul 2026 13:00:04 +0000

As I sat in my RV, surrounded by the quiet of the night, I was struggling to refactor a piece of AI-generated code that had been passed on to me. The code was a mess, with unnecessary complexity and duplicated logic. I spent hours trying to make sense of it, but it wasn't until I took a step back and applied the principle of least AI that things started to fall into place.

The principle of least AI states that you should use the least amount of artificial intelligence necessary to accomplish a task. This means avoiding the use of AI-generated code when a simpler, more maintainable solution is available. In my case, I was using an AI model to generate boilerplate code, but the resulting code was so convoluted that it was almost impossible to understand.

One technical insight that I've learned from working with AI-generated code is that it's often better to use a tool like SlopClean to refactor the code into a more maintainable architecture. SlopClean uses oMLX to run locally and can turn even the most spaghetti-like code into something that's actually usable. For example, by using SlopClean's --simplify flag, you can reduce the complexity of AI-generated code by removing unnecessary dependencies and flattening the code structure.

The lesson I learned from this experience is that while AI can be a powerful tool, it's not always the best solution. By applying the principle of least AI and using tools like SlopClean to refactor AI-generated code, you can create more maintainable and efficient software. This approach has saved me countless hours of debugging and has allowed me to focus on writing high-quality code that I can be proud of. Whether you're working on a small project or a large-scale application, the principle of least AI is an important consideration that can help you write better code and avoid the pitfalls of over-reliance on AI.

Building Apps with a Conscience: A Developer's Reflection

Scot Gardner — Thu, 02 Jul 2026 13:00:05 +0000

As I sat in my RV, sipping coffee and staring at lines of code, I realized that being an indie developer isn't just about building apps, but also about being responsible to our users. I've been working on a few projects, including Gemini, and I stumbled upon a problem that many of us face: keeping track of free trials. I've lost count of how many times I've been charged for a service I no longer use, simply because I forgot to cancel the free trial. That's when I built Trial Guard, a small menu bar app that reminds you when a free trial is about to end.

From a technical standpoint, implementing a reminder system like Trial Guard's requires a deep understanding of scheduling and notifications. One insight I gained while working on this project is the importance of using NSUserNotification in macOS to create custom, non-intrusive reminders. By leveraging this API, I was able to create three reminders that fire before the user is charged, giving them ample time to cancel or continue with the service.

One lesson I learned from building Trial Guard is that even the smallest apps can have a significant impact on users' lives. By providing a simple, one-time purchase solution to a common problem, I've been able to help users avoid unwanted charges and stay on top of their subscriptions. As developers, we often focus on building complex, feature-rich apps, but sometimes it's the small, thoughtful solutions that make the biggest difference. Whether you're working on a project like Gemini or just looking for ways to build apps with a conscience, I encourage you to think about how your work can positively impact your users' daily lives.

Popular Tags: How I Used Browser Storage to Efficiently Manage User Data

Scot Gardner — Mon, 29 Jun 2026 13:00:04 +0000

As a solo developer working out of an RV, I've learned to appreciate the importance of staying organized, especially when it comes to managing user data in my Chrome extension, Tab Reminder. One of the key challenges I faced was efficiently storing and retrieving user-scheduled tabs, which led me to explore the world of popular tags in browser storage.

During the development of Tab Reminder, I realized that using a simple key-value pair system wasn't enough to manage the complexity of user data. I needed a way to categorize and prioritize scheduled tabs, which is where popular tags came into play. By utilizing the localStorage API, I was able to store user-defined tags and associate them with specific tabs, making it easier for users to manage their scheduled tabs.

One technical insight I gained from this experience was the importance of using a robust data structure to store user data. In my case, I used a combination of arrays and objects to store tag information, which allowed me to efficiently query and update user data. For example, when a user schedules a new tab, I use the following code to store the tag information:

// Store tag information in localStorage
const tags = JSON.parse(localStorage.getItem('tags')) || {};
tags[tabId] = tagName;
localStorage.setItem('tags', JSON.stringify(tags));

One lesson I learned from this experience is that even small, useful tools like Tab Reminder require careful consideration of data management. By leveraging popular tags and a robust data structure, I was able to create a seamless user experience that allows users to efficiently manage their scheduled tabs. If you're interested in trying out Tab Reminder, you can check it out at https://go.sg1-labs.us/tab-reminder.

Simplifying Deployment for the DEV Community

Scot Gardner — Thu, 25 Jun 2026 13:00:04 +0000

As I sit here in my RV, coding away on my latest project, I'm reminded of the countless hours I've spent wrestling with deployment configurations. It's a problem many of us face, and one that I've tried to solve with ShipDrop. With nearly 4 million members, the DEV Community is a vibrant and diverse group of developers, each with their own unique needs and workflows.

One of the most significant pain points I've encountered (and heard from others) is the hassle of deploying small projects or prototypes. We've all been there - spending hours setting up a new repository, configuring git hooks, and debugging deployment scripts. It's a barrier to entry that can be frustrating, especially when all you want to do is share your work with the world.

From a technical standpoint, one of the key insights that led to the development of ShipDrop was the realization that many deployment platforms rely on complex configurations and git integrations. By stripping away these requirements and focusing on a simple, drag-and-drop interface, I aimed to create a tool that would let developers deploy their projects in mere seconds. For example, ShipDrop uses a combination of Node.js and AWS S3 to handle file uploads and hosting, allowing for fast and seamless deployment.

One lesson I've learned from working with the DEV Community is the importance of keeping things simple. As developers, we often get caught up in the latest trends and technologies, but at the end of the day, it's the small, practical tools that can make the biggest difference in our workflows. With ShipDrop, my goal is to provide a hassle-free deployment experience that lets you focus on what matters most - building and sharing your projects with the world. Whether you're a seasoned pro or just starting out, I hope ShipDrop can be a useful addition to your toolkit.

Building a Sense of Community as a Solo Developer

Scot Gardner — Mon, 22 Jun 2026 13:00:05 +0000

As a solo developer, I've often found myself working in isolation, with limited opportunities for feedback and collaboration. However, my experience with the DEV community has been a game-changer. I recall a particularly challenging project where I was struggling to deploy a simple website. A fellow developer on DEV pointed me to a solution that used a similar approach to what I've implemented in ShipDrop, my one-click hosting tool for HTML files.

From a technical standpoint, one of the key insights I've gained from working on ShipDrop is the importance of simplifying the deployment process. By handling the underlying configuration and git push, ShipDrop allows developers to focus on writing code, rather than worrying about the logistics of getting it live. For example, when working with Node.js, I've found that using a library like fs to handle file system interactions can greatly streamline the deployment process. By using fs to read and write files, ShipDrop can quickly and reliably deploy HTML files to a live server.

One lesson I've learned from my experience with the DEV community is the value of sharing knowledge and expertise. By contributing to discussions and sharing my own experiences, I've not only helped others but also gained valuable insights and feedback that have improved my own work. As I continue to work on ShipDrop and other projects, I'm grateful for the support and camaraderie of the DEV community, and I look forward to giving back and helping others in any way I can. Whether you're a solo developer like me or part of a larger team, I encourage you to join the DEV community and start sharing your own experiences and insights.