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Wearing all the hats
Nov 25 ⎯ February 2024, the first Local First conf (no pun intended) is happening in Berlin. As a local-first (previously offline-first) enthusiast, I’m thrilled to attend this conference with some friends. The talk that left a mark on me was the one given by Maggie Appleton, Home-Cooked Software and Barefoot developers. The plan So, after quitting my job in mid-March, I decided to try to be an Indie Developer and apply the “Barefoot developers” idea as much as possible. Spoiler, it ends up being harder than expected because “distribution is key”. That said, I just wanted to have fun by doing what I liked the most. Create software that can help someone (or just me, that’s also fine :P). The challenge definition was quite simple (and vague). Take a year to create (at least) 6 apps. The way to get productive would be to use AI as much as possible for the execution and plan. That would be the perfect excuse to “learn” to use these trendy tools to super-power me. Initially when I decided to start this journey, 6 different apps, with unscooped size, seemed a reasonable amount to achieve in a year. That should give like 2 months per app. Understanding that some of them would take more, and some others less. In my plans, I was considering using hackathons to boost push me even more, so I participated in 3! Local first I've also wanted to experiment a bit more with local first technologies. So I experimented with as many frameworks as possible in my old deplayer.app project. In some of the initial projects were super productive using tinybase + Cloudflare Workers and Durable Objects for the realtime. But soon I have found the limitations of choosing it for some projects so I had to find my next tool-of-choice. So, I finally put all the eggs in convex.dev (despite not being local-first) because it gave me much more complete and efficient framework to create rich apps with little infra and effort. The results I've created many apps such as the following ones and a couple more that I keep in private. Each one would deserve an specific article of what I’ve learnt. slidetime.app - A talk slideshow generator sunflare.app - A all-in-one photographer business platform cookery-1jy.pages.dev - A tool to get menu recommendations with what’s in your fridge inspire.sunflare.app - A design references library to collect UI patterns and later on be inspired and use them mythgrow.pages.dev - A (super-alpha) prototype game using LLMs to generate creatures and worlds to play at. By building so many different apps my learning pace has been accelerated a lot! Specially around AI, tools, patterns, prompt engineering, Local LLM Models, AI agentic programming, and sometimes vibe-coded a lot! which enabled me to explore many paths that I couldn’t even imagine before. Trying crazy mixes of frameworks, architectures, languages and whatnot as if I were a mad scientist brewing a magical potion. The reality is that I'm far to make money with any of them, for a very simple reason. I'm not optimizing for it. I'm learning and creating software that I enjoy creating, following the passion and inspiration. Rather than optimizing for money. That said, now I started to go deeper into marketing and how to, at least, be able to get some users that put pressure. What I want to hightlight in this article is that doing this Indie Developer path forced me out of the safe bubble. I had to think as a Product Owner, a Growth Hacker, a CFO, a Designed, etc.. Owning the E2E of the product requires having to cover many zones that you’re not used to. Distribution is key So I’m learning SEO and Marketing as I’m writing this, so I can try to get some traffic to some of my apps. I’m learning to wear the Growth Hacker hat. Despite not being very passionate about the topic itself. My Achilles heel? I have many! But there are two very evident. The first one you probably figured out by reading the apps names. I’m terrible finding good names and narratives behind the apps I create. Second one? Logos, I have not much idea on how to get a good logo. I’ve tried many AI tools, and tried to create one myself without getting one that convinces me a lot in almost all apps. In this regard, I created inspire.sunflare.app, so I can collect all UI design or general design references to get inspiration from or generate a prompt to quickly validate ideas.
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Why's everybody talking about vibe coding?
Nov 25 ⎯ The vibe-coding meme “Vibe-coding” is the word of 2025, according to Collins Dictionary Vibe-coding is everywhere, you can now find it in every tech-related online community, Telegram, Discord, Slack, X, Reddit, etc. Usually with a negative connotation, to denote that an application is low-quality or improvised without clear vision. Some of us even started using vibe- prefixed words in order to suggest that something is also low-quality, mediocre or improvised. (vibe-marketing, vibe-written, vibe-posting, vibe-leadership are just few examples that I’ve found looking my Telegram history) In the last year in software development industry, we faced the faster and probably more important shift in our jobs (and many others). Vibe-coding, is just the most memetic part of what is really happening. A bigger anti-memetic picture of such revolution is worth to be spread too. In this post, I will list some of the most interesting trends, that are fueled by vibe-coding, that I've been able to observe in the last 9 months. The <Prompt/> component spread It’s 2025 and what your app needs is a prompt to interact with your stuff. Starting from all major LLM model providers that have their own version of prompts. Followed by all traditional IDEs, or newly created ones with this specific purpose. One-by-one, all online products are adding a prompt to enhance (sometimes amazingly, many other times a little bit meh) your experience with the app. I’m sure others to pretend that is an AI company, or it did its homework to not be moved to the “legacy“. I gave https://slidetime.app a prompt — it worked, but the UX was… vibe-coding. As users, we’re gradually getting more used to interact with <textarea /> to get a piece of information or ask for a task to be done. And, as developers, it will be extremely hard to look back after this, and it is transforming how we work and the kind of applications we do. New ways of working Frankly, I haven’t seen this pace before in any other bubble. It’s really overwhelming. It didn’t happen one day by another though, each new toy related to usage of LLMs integrated in programming field started its own smaller revolution, on each iteration of each tool you can notice how the good ideas are copied between them. You can check how recent are their increase on interest (they are super new apps, after all), the interest on using these tools isn’t stopped growing over time. New open-source models and tools, proliferated at a huge pace. We’re optimizing our tools to work in a Factorio-mode, just because we figured out that the best Developer eXperience, happens to be also the best AI Agent eXperience. Good documentation about the why’s, lessons learned, documenting changes, etc. is also useful for the AI Agents, so they can laser focus on how a project is maintained and replicate known patterns. Horizontally scaling applications is superfast now, you just need to create an architecture to allow fast adoption of features and ask new replicable features at will. Refactoring is more needed than ever, you need to do checkpoints, stop adding features and accommodate code to be more scalable in the more frictionful parts. Running several code agents in parallel All agentic coder tools have their own version of parallel execution models. Just today, I updated Cursor to last version to see that they improved their support for agent execution in a project. But before that, all cloud agent services also provided an “ephemeral” coding agent execution. Some notable open-source projects exploring this approach are: - https://openhands.dev - https://opencode.ai - https://github.com/BloopAI/vibe-kanban - https://github.com/Ido-Levi/Hephaestus Proliferation of repository file-based task managers One of the major issues when you use LLMs to help you to code is how to properly manage the context, so the LLM has access to all the relevant information to perform the asked tasks without being overwhelmed. In order to solve this issue, many new applications appeared to manage tasks to be executed by Code Agents. These tasks, usually contain all the context gathered in “planning“ mode so when you just ask for execution, you can start with the context empty and the agent won’t need to read half of your project to perform a good job. Here you can find some examples that help to accomplish this job. https://www.task-master.dev https://github.com/BloopAI/vibe-kanban https://backlog.md Usually when you work with tasks like this you can ask for “I want to do X, because of y, look these files for examples on how to do it and create a task”, then you can just ask “implement task #23“ and see how the agent does the planned job. Proliferation of new standards Given that many Agent Coding tools are solving the same problems, it is normal that many new standards arise so you can share your project characteristics across tools. This is the case of AGENTS.md which allows you to give initial context to the LLMs to be more efficient working in your project. Or the quite recent Claude skills that are being translated to other CLIs and agentic coding tools with project like openskills. The main goal of such standards, is removing vendor locking and being able to use available tools in an interchangeable way. Proliferation of local and open sources models This is just an adjacent trend that I think is pretty relevant, almost each month new open source (or better said open weights) models are released. So you can run them in your personal computer, smartphone or in a rented cloud instance. Unfortunately, if you want to use such models for agentic coding, you’ll need super expensive hardware or cloud instances at the moment. Some examples of such open models are: Mistral, qwen3, glm and gpt-oss. New prompt techniques to improve the coding experience Many people tried to mimic a full engineering team, and others mapped all imaginable brainstorming methodologies and other skills as mere AI commands. https://blog.fsck.com/2025/10/09/superpowers/ https://github.com/obra/superpowers https://github.com/bmad-code-org/BMAD-METHOD I even myself learnt a lot of “vibe“ skills on what things work well, what others don’t and some are meh. And this learning could only happen by practice. https://blog.alexmaccaw.com/how-to-vibe-code-as-a-senior-engineer/ Trade-offs: Almost everything is experimental and gets outdated fast. So take this into account before betting in a vendor-lock-in solution or mass adoption. Don’t put all the eggs in the same basked. AI-related job titles getting really popular A new lore, related to AI programming, emerged and suddenly started to be popularized over social networks. Prompt Engineering, AI Engineers. Such jobs are incredibly well paid. I believe we're yet to see many few jobs related to AI appearing. Vive-coding is just a symptom Sure! Making jokes about how bad vibe coding is, some blatant low quality apps that are appearing, and so many examples on how this proliferation and trend is happening is fun. But don't miss the amount of rapid new toys that aren't stopping to improve and be more effective. These superpowers developers to be much more efficient developers each day. If you learn how to use these tools, you can go quite fast as compared to traditional old methods. Be open-minded, have fun trying different things. I’ve never got so fun by creating software than now. Links https://omny.fm/shows/better-offline/vibe-coding-is-bs-w-charlie-meyer#description https://knowyourmeme.com/memes/cultures/ai-artificial-intelligence https://newsletter.pragmaticengineer.com/p/vibe-coding-as-a-software-engineer https://nayafia.substack.com/p/introducing-antimemetics-my-new-book