Hey folks!
It’s been a while since my last update — and the past month hasn’t been all about Fidely.
Between studying for a project management course 📚 and other work commitments, time has been tight.
But I still managed to make progress on one crucial piece: the first version of the Fidely landing page!
The First Landing Page is Live!
The landing is focused on shop owners, as they are my primary target customers.
It’s based on the mockup I shared last month, and I’m happy to finally have something concrete online:
👉 fidely.pulbasso.dev
For the tech stack, I used:
Next.js
React
TailwindCSS
I deployed the landing on Netlify. Technically, it could be fully exported as a static site, but for now I decided to skip this step to keep things simple.
Is it perfect? Absolutely not.
But I strongly believe it’s way better to launch an imperfect first version and improve iteratively, rather than chase perfection and risk getting stuck.
Why Small Wins Matter
Even though Fidely is still small, it’s surprisingly complex:
So many moving parts, from the app logic to the business aspects.
With limited time available, I need incremental results to stay motivated and keep pursuing my goal.
Seeing the landing live, even in its raw form, gives me a sense of progress and something tangible to build upon.
🤖 Evolving My AI Workflow
Lately, I’ve been integrating AI more and more into my development process — and I’m slowly finding my own balance.
A few personal thoughts:
“Vibe coding” with AI is dangerous:
Sure, it gives you a quick solution, sometimes even working code. But it often hides key implementation details, which leads to a shallow understanding of your codebase.
Without that deep knowledge, evolving your app later becomes a nightmare.
Guided AI usage is key:
Using AI purposefully, with focused prompts, while maintaining control over the architecture and code structure, has proven the most effective path for me.
It dramatically speeds up development without sacrificing code quality or maintainability.
AI for brainstorming:
Having your codebase in context and using AI to discuss architecture or design choices is a game-changer. What used to take hours of solo research can now be condensed into a few minutes of collaborative ideation.
Currently, my tools of choice are:
✅ Cursor + Claude for personal projects
✅ GitHub Copilot for work
Early Comparisons
My initial impression?
Cursor + Claude 3.5 feels ahead in quality and reasoning, especially on complex tasks.
GitHub Copilot with GPT-4o seems a bit behind, but I’ve used it less intensively, so the comparison may not be entirely fair.
In personal testing, I’ve noticed better answers from OpenAI’s GPT-4o on ChatGPT compared to the same model used via Copilot.
For now, I find myself leaning heavily on Claude inside Cursor — but I’ll keep testing.
That’s it for this month.
It may not have been the most productive period for Fidely, but even small steps like launching the landing keep the momentum alive.
Stay loyal 😄
