I am a frontend engineer and actively use AI. I caught myself that i never write code manually, only if i have to tweak some styling. I feel lazy and dumb compared to pre-AI era. Even if i have to write some small changes in code that take like 2 minutes - it is easier to spend those 2 minutes explaining everything in details to AI and point out what and how it needs to change. Because i dont have to think about the process, i only explain the idea and desired solution - then wait until its done to review.

Thats some kind of degradation. But the thing is that the quality is amazing. My productivity and speed increased significantly.

But there is a frustrating thing. The laziness started affect even review process. I feel like i dont want to spend time to read and check all the changes - i will better ask another AI to do it. And it works! I use Claude for like 95% of work, then switch to GPT to review everything properly. They have different personalities so you have different points of view. I consider GPT as a nerd - it catches a lot of gaps and inconsistencies that Claude misses. So i like to close them both in one room to debate.

What i really do care a lot is a comprehensive documentation. I spend a huge amount of time for planning and brainstorming with AI, then i document everything properly. All those MD files about architecture, composition recipes, cheat sheet… All of it should lie on surface, not to be buried somewhere deep in code. Every cold session starts with all the docs where everything is explained properly with references and examples to prevent AI to skim or give lazy answers. When i need to implement some big feature i structure a proper ready-to-execute plan so every next agent with fresh context reads it - analyzes what was done - figures out what is the task for this session - and goes ahead with all the changes, then report. It can be dozens of chats working sequentially on some big thing; in the end i will run some workflow to review all the implementation, then ask GPT to audit changes, and i will look myself only when AI approves that everything looks great. Then i can tell what and why has to be redone because i dont like how we have it now.

In my setup the documentation for AI outweighs the code (instruction files on every level, rule files that load by file type, subagents with roles, hooks around every edit). The most weightful part:

- A catalog of silent failures. 36 numbered traps that compile fine but render broken. Every entry is a real failure that shipped at least once: cause, symptom, fix.

- A "polish" rule. When you tell AI "make it better", its reflex is to ADD decorative stuff. So there is a written rule that polish means subtraction, with a list of patterns i rejected in real reviews.

- CI that fails when docs drift from code. The component registry is checked against source files. Because docs that lie are worse than no docs.

- A runtime verifier (WebMCP). An agent drives a real Chrome browser, clicks through the page, watches the console, takes screenshots at 3 viewports.

Basically I stopped writing code and started engineering the environment that writes the code. Every file exists because AI failed at something once, and i wrote it down so it wont happen again.

The biggest problem for me is motivation. I remember that feeling how you got stuck - cant figure out something for hours, searching right solution, trying, and then FUCK YEAH FINALLY, and the satisfaction: YOU NAILED IT. I dont have it anymore. I feel confident even in things where i have no expertise at all. Thats like: meh AI can handle it.

I think my system solves the quality question, but increases the laziness/motivation problem. I made it safe to be lazy.

So two questions:

1. How does your AI setup look like? I mean real files and rules, not just how you prompt.

2. Has anyone actually solved the motivation part?

user:	dimonb19a
created:	June 3, 2026
karma:	2
about:	Frontend & UI/UX Design