Qoder JetBrains Plugin - Understands your backend's real complexity, not just syntax

@john_lunsford_phd Thanks John! very good question. this touches on an area where we have some capabilities today, with room to grow.

Current capabilities:

1. Contextual analysis during tasks:

Qoder scans your project structure before making changes:

• Analyzes project files, configuration, and database schemas

• Identifies what components are related to your task

• Plans changes based on understanding the existing architecture

2. Code quality issue detection:

During code generation and fixes, Qoder can catch common issues:

• Example from our Spring Boot demos: When adding async event handling, Qoder not only added @Async to the event listener but also added @EnableAsync to the main class. A step 95% of developers forget

• Real case: When asked to fix SQL injection, Qoder didn't just parameterize the query—it found an existing repository method that should have been used instead, essentially flagging duplication and suggesting the proper architectural pattern

3. Auto-fix capability:

During complex tasks (like database migrations), Qoder can automatically detect and fix configuration errors without human intervention. In our MySQL to MongoDB migration benchmark, it auto-fixed 3 errors vs. competitors requiring manual intervention for each.

@alexcloudstar Love the honesty, Alex! Rapid prototyping vs real software is exactly the bar we're trying to clear. The Spring bean graph + DB schema awareness isn't just marketing. It's what lets the plugin understand your actual architecture, not just code or text patterns.

Your 120K-file monolith test sounds perfect. That's exactly the complexity we built this for. Curious how it handles your migrations and circular deps; would genuinely appreciate hearing what breaks (or doesn't).

If you do try it, feel free to ping us with feedback. Real gnarly codebases are where we learn the most. Thanks you!

@zhiqi_shi Love the energy, Zhiqi! Hope it makes your backend work smoother. Would love to hear your thoughts after trying it!

@hello_leo Thanks Leo～ Excited to hear it's useful for you. Let us know how it goes!

@cruise_chen Thanks Cruise! Stoked it's helping with your builds. Always curious to hear how engineers are using it.

@cata Great question. The main difference is architectural understanding vs. code(text) pattern matching.

Copilot excels at autocomplete and syntax-level suggestions. Qoder goes deeper: we parse Spring's ApplicationContext, database schemas, and framework semantics at startup. So when you're coding, the AI knows your actual dependency graph, not just your file structure.

It's built specifically for complex backend architectures where structure matters as much as syntax.

@kaixin_feng Thanks for asking the questions on complex scenarios.

Multi-tenant/sharding: Limited support currently,. we understand static patterns (tenant_id columns, separate schemas) but dynamic routing logic is an area we're actively improving. If documented in your agents.md file, Qoder will use that context.

JPA relationships: Yes, beyond annotations. We parse entity relationships (@OneToMany, cascades, etc.) and trace them through your service layer. So we know what depends on what when you make changes.

Best for: Static schemas with clear relationships. Working on: Dynamic sharding and runtime-determined routing.

Would love to hear about your setup, as real-world feedback helps us prioritize! And what multi-tenant approach are you using?

@pasha_tseluyko  Hah，appreciate that Pavel! 😄 Yeah, the "vibe coding" era has been... interesting. But real backend work (complex Spring apps, gnarly database schemas, circular deps) needs tools that actually understand the architecture. Glad this resonates with you. Would love to hear how it works for you～

@luke_pioneero Thanks Luke! That's exactly the gap we saw. backend work is so much more than syntax. Appreciate the support!