Been building Consile almost entirely with Lovable, and the thing I've found matters most isn't the AI generating code fast, it's having a real, repeatable process for verifying what it generates before it ships. Things like actually reproducing security findings against live endpoints instead of trusting a policy read, or independently confirming a claimed fix rather than taking "done" at face value.
Curious what others here have landed on. Do you have an actual verification process, or is it more ad hoc? What's caught you off guard that a quick glance wouldn't have?
Hey, I was wondering how many of you are coding from the phone - it's easier to do it with AI coding agents now, so I'm wondering how often developers are doing it.
Personally, I do some coding tasks daily from my phone and I'm curious how others are doing it?
A few months ago I made a small bet with myself: build and ship a tiny tool in one weekend, no overthinking, just vibes. I did it. It worked. People used it. And then something strange happened.
The weekend project taught me more about my own habits than any "proper" project ever had.
Recently stumbled across this Cursor pro-tip from Ian Nuttall on X: "1. ask it to recommend a folder structure
2. ask it to actually create the folder/files based on that this makes it 10x easier for me to get started and Cursor is more accurate using codebase cos it knows where to update files."
That got me thinking, what other pro tips are people using to generate better code, ship faster, organise your space better, etc. Drop em below:
Had a moment this week where a bug showed up in a part of the app I didn't write by hand, my agent did, and when someone asked me why it broke, my honest answer was "I'm not totally sure yet." That's a weird sentence to say out loud as the person who's supposed to own the code.
With code I wrote myself I can usually reason about a bug from first principles even before I open the debugger. With vibe-coded stuff I sometimes have to re-read the whole file like a stranger before I can explain anything, and the explanation ends up being "here's what I found after digging" instead of "here's why this happens."
The story started in 2019. I wanted to build my own company. Back then, I was running a service-based business as a developer, but deep down, I never felt connected to that model. I wanted to create a product that could grow while I slept. Something truly mine.
So I started building. From 2019 to 2024, I built the product almost entirely on my own. Every system, every architecture decision, every scalable practice, every multi-tenant layer. It was hard, but I always felt in control of the machine I was creating.
Lately I ve been wondering whether the one AI tool builds the whole product idea is actually what people want.
For a simple website or SaaS-style app, the workflow often ends up looking like this:
UI in one tool, backend somewhere else, auth/payment setup in another place, deployment on a different platform, and maybe an admin dashboard built separately.
That gives you flexibility, but it can also get messy fast especially for non-technical founders, small teams, or people trying to validate an idea quickly.
Quick question for those of you dealing with AI architecture and scaling.
Right now, we rely pretty heavily on n8n at our startup. It s been amazing for moving fast, tying APIs together, and automating workflows. But looking ahead, I'm trying to figure out the long-term play.
At what exact point does it make sense to move away from n8n (and paying for third-party LLM APIs) to actually build out a specialized, local RAG on physical hardware?
