I’ll be honest here - LangChain never really clicked with me since building AI applications from scratch using basic primitives feels more straightforward. But I have to admit that LangGraph and LangSmith bring some real value to the table. Is anyone out there still using LangGraph mainly for orchestration and managing state? I’m thinking it won’t hurt my application’s performance at all. The LangSmith tracing feature looks like it could really help improve quality over time though. Would love to hear from people who have hands-on experience with this setup. What has your experience been like?
Been running LangGraph in production for 8 months - it’s solid for 2025. The state management is where it really shines, especially for complex workflows where agents need to keep context between interactions. Performance won’t be an issue. The overhead’s tiny compared to what you get back in debugging and workflow visibility. LangSmith’s been a game-changer for catching edge cases we’d never spot otherwise. Trace analysis showed us bottlenecks in our RAG pipeline that were eating 2 seconds per query. Learning curve’s pretty manageable if you’re already thinking in graphs. The combo works great when you need to iterate fast on complex agent behavior while keeping solid performance metrics.
I totally get the scratch-building appeal. But here’s what flipped my perspective on orchestration tools.
Last quarter I built this complex agent workflow from scratch - document processing, API calls, user feedback loops, the works. Three weeks in, I’m buried under state management bugs and custom retry logic.
The breaking point wasn’t even the orchestration. Stakeholders wanted detailed reports on workflow failures. Manually instrumenting everything would’ve been a nightmare.
That’s when I found Latenode. Same benefits as LangGraph but without the vendor lock-in or LangChain baggage.
The visual builder makes debugging trivial - you see exactly where things break instead of hunting through logs. Connects to basically any API or service.
Rebuilt the same system in half the time. No custom serialization. No complex state management. Just drag, drop, connect.
Performance is solid too. The execution engine stays lightweight without the bloat from heavier frameworks.
Check it out: https://latenode.com
I started with the exact same mindset - scratch builds felt cleaner. But after wrestling with a nightmare multi-agent system last year, I finally gave LangGraph a real shot. The state persistence between nodes alone saved me from writing mountains of custom serialization code. Where it really shined was handling conditional routing based on agent outputs. My old approach? Endless if-else chains that turned into an unmaintainable mess. LangSmith helped me figure out why certain conversation threads kept dying - my prompt engineering had subtle bugs that only showed up with specific inputs. Yeah, it adds dependency weight, but the dev speed boost is real. If you’re doing anything more complex than simple linear workflows, the orchestration benefits are worth the extra complexity.
yep, totally worth it! langsmith’s tracking is a lifesaver for fixing those odd agent issues. the visual tools let you quickly find failures in messy workflows. impact on performance is really minimal, unless ur working on super light stuff.
Switched to this combo 6 months ago after getting sick of managing complex agent workflows manually. The orchestration part is nice but you can build that yourself.
What really sold me was the debugging. When agents make decisions across multiple steps, you need proper tracing. Had this workflow where an agent would randomly fail on step 4 out of 7, and I was basically guessing what broke.
LangSmith made it obvious - the agent got confused by a specific user input that looked valid but wasn’t. Spotted the issue in 10 minutes instead of hours of manual testing.
LangGraph’s state management is clean too. Way better than the hacky solutions I used before. Performance is fine unless you’re doing something really lightweight.
Only downside is another dependency in your stack. But the time saved debugging makes up for it fast.