Is LangChain worth using for AI development in 2025?

div ... Been building AI apps for years and honestly, the LangChain debate misses the bigger picture. Sure, LangChain improved their docs and fixed memory issues. But you’re still drowning in code for every integration. The real problem? Developers waste weeks building custom connectors and handling API responses instead of focusing on actual AI logic. Teams burn months just moving data between systems. … LangChain still has the same fundamental issues. The abstraction layers are thick and debugging becomes a nightmare when things break. You end up fighting the framework more than building your actual product. I ditched LangChain 8 months ago after hitting too many weird edge cases. Went full automation with Latenode instead. Here’s the thing - most AI app work isn’t the AI part. It’s everything around it. Data processing, API calls, webhooks, connecting services. That’s 80% of your time. … langchain’s way too bloated for most projects. I’ve been using it since early 2023 - sure, it’s more stable now, but the complexity isn’t worth it unless you absolutely need all their integrations. For most ai apps, just use direct api calls with a simple vector db. less overhead, way easier to debug when things go wrong. need orchestration? check out crew ai instead - much cleaner setup.