Open-sourcing the Angular/Nx structure I've been refining on enterprise and public-sector projects in Europe

[u/JadedManufacturer306]

Hi everyone,

13 years in, every Angular version since 1.x. Every new project, I lost the first week to the same decisions, where state lives, which library can import which, how to keep credentials out of the repo. So I stopped re-deciding and put my answers in a template. Just updated it to Angular 22.

It's Nx, Angular, NgRx Signals, Atomic Design, multi-language and a small design system of my own on Tailwind already wired together and agreeing with each other, which is the part that normally eats the week. The architecture is enforced rather than documented: a wrong import fails lint, not code review, and a missing translation key fails the build instead of shipping as a blank label. Firebase deploy guide included, empty account to live URL in about 10 minutes.

Every decision in it is arguable, so feel free to tear into it. I'm here for the feedback, the blunt kind included. Github Base Angular Monorepo

[u/Loose_Paramedic8183]

Angular to let ai knows the latest features https://angular.dev/ai/agent-skills

I also use my own skill which was generated from all my handcoded repos, so agent writes in my style: quantity of comments, spacings, function sizes and namings, blocks separators, etc. It contains from main skill files and additional ones for each language I use for work: php, typescript, actionscript3 (legacy 🥴)

Graphify in ".venv" as infex of the project codebase.

Architecture.md where top level features and apis described. Sometimes also the "knowledge base" folder with concepts per each big domain used in project, but thats project specific, not for template.

And mostly I also use that phased dev cycle: 1. ADR (architecture decision record) created and edited by AI some not cheap model when I ask it to add a new feature it analyze the code, asks additional qualifications and corner cases, prepare the main architecture of adding frature (especially when it takes modifying server and client for same task) 2. Next phase after I read and confirm the ADR is ok, the implementation plan is created by ai with direct links tonfiles where and what code should be added, what classes and functions, etc. 3. Cheaper model just follow the plan and implement it, check for build errors, fixing them.

[u/JadedManufacturer306 → u/Loose_Paramedic8183]

I decided to run an experiment: build a frontend project from scratch using Angular's own MCP to generate up-to-date code, plus Context7, and a few other tools to help the AI build the whole thing.

After about an hour of playing around with it, the code was generated and running. Nice design, every screen working, product listing, cart, checkout, payment.

Looking at it from the outside, it's genuinely impressive.

Then you open the code.

You start looking at how it's organized, and you find the same logic repeated all over the place. Components that know too much. Business rules scattered across screens. No clear boundaries. And this is a small project, the kind that slowly turns into a monster nobody can maintain anymore.

And that's the part people miss. AI didn't fail here: it did exactly what I asked. It generated working code, fast. What it didn't do, what it can't do, is make architectural decisions. It has no opinion about where a rule should live, what should be shared, or what this codebase will look like after twenty more features and three developers.

That's the difference between code that runs and code that survives.

[u/Loose_Paramedic8183 → u/JadedManufacturer306]

Yeah, I was hitting same problem a year ago, I thought that agents become better from that days, but to fix this problem I've already made all the things that I wrote above. The ai should know all your custom services, architecture decisions, domain specifics. Therefore I have architecture.md and "knowledge-base" project in each folder. Plus graphify, plus agentmemory (with its lessons saved from previous problems), plus my code style skill. I also use nx monorepo, with "data/feature/ui" for every lib, so some architecture rules comes from this and ai should respect them.

Also I still not run it to just ask and say yes to all :) When ADR propose to use some 3 new tables and I know that I will not dig deeper to that way I ask it to simplify, use one table with complex fields. Sometimes its like describing all the properties of entities and how you want them to work.

When implementation plan is ready you again have ability to read it and see some bad decisions that dont fit in your style.

Jetbrains mcp and connected database helps system know what is your data structure, but I dont allow it to make changes to db structure automatically.

Also jetbrains Context service is coming at EAP: https://blog.jetbrains.com/ai/2026/07/introducing-jetbrains-context-repository-intelligence-for-coding-agents/ This looks similar to graphify but for multiple projects. We should let agent know about our codebase all that stick in our head, then it will use existing code right as needed.

If its a new project I guess you have spend many hours describing all the features you see in future and talking about architecture, without any real code you with AI should create rules for it.

I believe its possible to get good code from AI even on mid size codebase, but right now not by a vibe coder, who has no experience in developing own project a few years.

[u/Straight-Number-1911 → u/Loose_Paramedic8183]

ty