Naol Lamesa

I ve been working on some AI projects recently things like scheduled agents, API responders, and multi-agent systems that need to run continuously. One of the biggest headaches I ve run into is deployment.

Most cloud platforms (AWS, GCP, etc.) are built for stateless apps or short-lived functions. But for long-running, stateful agents, the kind that need to persist data, auto-recover from crashes, and expose custom endpoints it gets surprisingly messy. I ve spent so much time setting up VMs, Docker configs, and recovery logic than actually writing agent behavior logic.

I've been primarily using @Cursor as I like how it operates, enjoy that it's visual, and I am getting very comfortable with using it and being able to easily select different code bits and modify what I need....however....
I recently started using Gemini CLI in @Warp and I must say... I'm kinda liking it. I feel that it's able to do a lot more, faster without needing me to jump in. When I do jump in, it's simply to provide it guidence and direction.
I haven't done much with it yet, but I can see myslef now doing a combination of CLI and IDE development. I'm curious what everyone elses experience is! Or if you haven't used a CLI or IDE AI tool, why?
A bit of additional background, I'm not a develpoer but more of a "vibe coder" I can kinda understand different languages and don't mind diving into tech docs but I prefer AI do more of the coding than me :)

Hey Product Hunt Narayan here, builder of Metaflow

I ve worn two hats for most of my career.

Hat #1: engineer the one who loves clean abstractions and reliable systems.

Hat #2: growth marketer the one elbow-deep in campaigns, funnels, and dashboards, trying to find signal in the noise.