I see a lot of hype, but I want to see actual, working implementations. Can someone point me to some concrete examples of agentic AI in a professional or technical setting?
I am looking for use cases that go beyond just 'chatting with documents'. I mean scenarios where the system:
- Interacts with databases to generate reports.
- Manages API calls across different services.
- Performs autonomous research tasks.
Links to open-source examples or case studies would be appreciated.
Agentic AI implementations in enterprise settings utilize frameworks like LangGraph to orchestrate multi-step workflows that dynamically interact with databases and external APIs through iterative error-correction and state management.
1 answer
You are conflating autonomous automation with true agentic reasoning, but if you want to see systems that actually bridge the gap between intent and execution, look at the integration of LangGraph or CrewAI within enterprise data pipelines. These frameworks are being used to build multi-step workflows where a controller model iterates on SQL queries based on schema inspection and error feedback loops rather than just spitting out static code.
For a concrete implementation, investigate how logistics firms are deploying these agents to reconcile shipping manifests across disparate ERP systems through autonomous API chaining. It requires rigorous guardrails for any production environment, but the shift from deterministic scripting to state-aware agents is currently the most significant trend I see in high-compliance architectures.
I appreciate the insight, Ken West. I’ll admit I’m still a little confused by the logistics implementation details, but I am very grateful you took the time to explain this concept.
Thanks for this, Ken West. I'm honestly a bit nervous about implementing state-aware agents in our pipeline, but your point about guardrails makes me feel slightly more confident about the risks involved.