Is LangChain still the best framework for setting up multi step agents in production or should we pivot to LlamaIndex right now to hit our Friday deployment deadline?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Is LangChain still the best framework for setting up multi step agents in production or should we pivot to LlamaIndex right now to hit our Friday deployment deadline?
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (2)
Classes come from the query-classifier (a local Laya model). 2 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT2 real searches · gpt-6
LangGraph production agents documentation durable execution persistence human in the loop 2026 LangChain Google ↗
LlamaIndex Workflows production agents documentation multi-step workflows observability deployment 2026 Google ↗
- Agent Workflows: Multi-Step Orchestration for end-to-end automation · llamaindex.ai
- Observability · developers.llamaindex.ai
- langgraph · langchain-ai.github.io
- docs/src/oss/langgraph/persistence.mdx at main · langchain-ai/docs · github.com
- LangGraph - Python API Reference · reference.langchain.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
LangGraph production agents documentation durable execution persistence human in the loop 2026 LangChain OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
LlamaIndex Workflows production agents documentation multi-step workflows observability deployment 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 |