LangChainCompanyLangChainLangChain is the company behind the LangChain framework, LangGraph runtime, Deep Agents, and LangSmith, a commercial platform for tracing, evaluating, deploying, monitoring, and improving agents.LangSmithLangGraphOpen companyAgent Framework
LangGraph
LangChain's MIT-licensed runtime builds agents as graphs with shared state in Python and JavaScript, with or without LangChain. It adds checkpoints, human interrupts, and streaming. LangSmith Deployment offers paid hosting.
The 30-Second Take
Pick LangGraph if your agent branches, waits for people and must survive restarts.
It is LangChain's MIT-licensed runtime for agents built as graphs of steps that share state. GitLab runs production agents on it.
- Best fit
- Stateful agents with branches and approval steps that must survive failures and waits.
- Main constraint
- Engineers report overhead on linear workflows, and breaking changes in releases before 1.0 shipped in October 2025.
- First move
- Build one workflow with a Postgres checkpointer, interrupt its riskiest action, and test resume and cancel.
Why
Watch the overhead: a workflow that runs in a straight line is cheaper as a loop in your own code. yeos.ai dropped it once its graphs got harder to debug than its business logic, and checkpoints pile up without cleanup.
61 practitioners, 96 sources reviewed, Updated Nov 1, 2026How this is measured
- Operating stack
- AI Application Platform
Comparisons
How does LangGraph compare with the alternatives?
LangGraph vs CrewAI
- Agent Frameworks
GitLab, Wayfair and Grab run production agents on LangGraph; CrewAI's named production accounts are its own customer stories, and Pydantic evaluated both and built its own. Pick LangGraph to write every step down with checkpoints, CrewAI for role-based crews with a managed builder.
LangGraph vs OpenAI Agents SDK
- Agent Frameworks
Named teams run production agents on LangGraph's checkpointed graphs; the Agents SDK leaves durability to Temporal or another engine. Pick LangGraph when your code controls the next step across providers, the Agents SDK when a model-driven loop on OpenAI models covers the work.
LangGraph vs AI SDK
- Agent Frameworks
LangGraph is a graph runtime for TypeScript agents with checkpointed state, interrupts, and LangSmith Deployment. The AI SDK puts model calls, tool loops, and streaming UI across providers into your own code. Teams often run a LangGraph agent behind AI SDK UI through Vercel's LangChain adapter.
Operator Insights
What are teams learning from building on LangGraph and running it in production?
Mikolaj WawrzyniakAuthor of the GitLab engineering articleGitLab
GitLab Duo Agent Platform, whose agent flows for GitLab engineers and customers compile from YAML into LangGraph graphs.
GitLab blog, published Read the write-up (opens GitLab blog in a new tab)
Observation
GitLab chose LangGraph as the foundation of GitLab Duo Agent Platform, then built a YAML layer on top that cut its own code per agent flow by 45%.
- Takeaway
- Use LangGraph as the runtime and give flow authors a higher-level definition on top, so each new flow is a configuration file that compiles into the graph.
- What happened
- GitLab researched agent frameworks and selected LangGraph for durable execution and traceability (GitLab blog, Sep 22, 2026). Hand-wired graphs ran to 450 or more lines of Python per flow, which GitLab found too low-level to scale. Its Flow Registry now compiles YAML flow definitions into LangGraph flows, and GitLab says that reduced its own code per agentic flow by 45%.
“We researched available AI frameworks and selected LangGraph, an agent runtime and low-level orchestration framework from LangChain, as the foundation for GitLab Duo Agent Platform.”
GitLab - Public engineering write-up
- Team metrics reported
Deployment details
GitLab Duo Agent Platform, whose agent flows for GitLab engineers and customers compile from YAML into LangGraph graphs.
- Public engineering write-up
- Team metrics reported
- Team
- GitLab Duo Agent Platform team
- Workload
- Agent flows for GitLab engineers and Duo Agent Platform customers
- Product version
- LangGraph under GitLab's Flow Registry
- Measurement
- 45% less of GitLab's own code per agentic flow, self-reported
Farshid BahramiCo-author, Wayfair Tech BlogWayfair
Wayfair customer service: every new comment on a supplier-transfer ticket triggers the workflow, which decides in about one second whether an associate must step in.
Wayfair Tech Blog, published Read the write-up (opens Wayfair Tech Blog in a new tab)
Observation
Wayfair runs Wilma, its supplier-transfer ticket flagger, as an event-driven LangGraph workflow that beat its human targets with 95% precision and 97% recall.
- Takeaway
- Decide what code can decide before the model runs, and give each kind of input its own prompt.
- What happened
- Wilma runs on an event-driven pipeline using LangGraph (Wayfair Tech Blog, Jan 15, 2026). The graph identifies the comment author in code before any model call, then classifies with an author-specific prompt. Against target baselines of 80% precision and 90% recall, Wilma reached 95% precision and 97% recall, cut time to resolution 29% against the period before it, and cleared about 65% of tickets without a person in early results. Wayfair monitors it in Arize.
“Wilma significantly outperformed its original target human baselines of 80% precision and 90% recall, achieving 95% precision, 97% recall, 99.8% reason accuracy and 99.7% timely flagging…”
Wayfair Tech Blog - Public engineering write-up
- Team metrics reported
Deployment details
Wayfair customer service: every new comment on a supplier-transfer ticket triggers the workflow, which decides in about one second whether an associate must step in.
- Public engineering write-up
- Team metrics reported
- Team
- Wayfair machine learning and customer service technology
- Workload
- Flagging supplier-transfer ticket comments that need an associate
- Product version
- Event-driven LangGraph workflow, monitored in Arize
- Measurement
- 95% precision and 97% recall against 80% and 90% targets; 29% faster resolution
Buying and deployment
What a team building on it should verify before production traffic grows.
Sourced from LangChain documentation
Signals
What is the current evidence saying about LangGraph?
GitLab, LinkedIn, Wayfair, Grab and Tiendanube run LangGraph in production, and builders praise its control flow while reporting checkpoint, resume and upgrade problems. Each finding links to its public sources.
Practitioner sentiment, all practitioners
+25 Positive net
of 62 sources that take a side, each author counted once.
How this figure is madeTeams and leaders have 18 accounts; GILD prints their sentiment from 20.
Current sentiment
Positive, mixed and negative sources
The score counts them as 23 positive, 30 mixed and 8 negative votes, one per author.
Across 79 sources the read is positive. Explicit control flow draws praise in 22 of the 25 sources that discuss it, and 9 of 15 report it holding up in production. Complexity is the most frequent concern, raised in 10 sources, followed by breaking changes in 9, and 8 of the 25 that describe a framework choice replaced LangGraph.
Build one pilot agent to measure the glue code and debugging time the framework adds.
Evidence field. All 96 sources, one mark each.
Arrange by
Each mark is one source: positive, mixed, negative, no opinion stated, or documentation (not counted).
| Group | Sources | Positive | Mixed | Negative | No opinion stated and not counted in the score | Documentation, checked and not counted |
|---|---|---|---|---|---|---|
| Positive | 24 | 24 | 0 | 0 | 0 | 0 |
| Mixed | 30 | 0 | 30 | 0 | 0 | 0 |
| Negative | 8 | 0 | 0 | 8 | 0 | 0 |
| Not counted | 17 | 0 | 0 | 0 | 17 | 0 |
| Documentation | 17 | 0 | 0 | 0 | 0 | 17 |
| Quarter | Sources |
|---|---|
| Q1 2025 | 12 |
| Q2 2025 | 9 |
| Q3 2025 | 6 |
| Q4 2025 | 10 |
| Q1 2026 | 13 |
| Q2 2026 | 13 |
| Q3 2026 | 12 |
| Q4 2026 | 4 |
| Documentation, checked | 17 |
By sentiment
17 documentation pages check facts and are not counted.
Hover a mark for a quick look, click it or press Enter to open its source.Tap a mark to open its source, then step to its neighbors with Previous and Next.
What practitioners praise
Top praise of 4. Each mark is a source on it; filled marks praise it.
Most common concerns
Top concern of 3. Each mark is a source on it; filled marks raise it.
All 96 sources behind these findings
- Self-hosting LangGraph without Agent Server: worker ownership and crash recoveryNeitherSearch4661, building a FastAPI service on LangGraph and PostgreSQL (self-described: Own background workers in place of Agent Server, with PostgreSQL checkpoints), Reddit post, r/LangChain, published Oct 27, 2026
- interrupt() re-runs the whole node on resumerahulladumor, Reddit user building an approval step (self-described: A Graph API node that asks a person before the agent sends an email), Reddit post, r/LangChain, published Oct 21, 2026
- LangGraph overviewLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- Runtimes, frameworks, and harnessesLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- PersistenceLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- CheckpointersLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- InterruptsLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- Use time travelLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- StreamingLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- Functional APILangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- Graph APILangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- Run a local serverLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- StudioLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- DeploymentLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- Release policyLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- What's new in LangGraph v1LangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- LangSmith DeploymentLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- Cloud platform featuresLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- LangGraph.js overviewLangChain (Official LangGraph and LangSmith documentation), Product documentation, checked Oct 12, 2026
- A self-hosted GitLab review agent on LangGraph.js after 1,000 merge requestsProfessional-Pear351, maintainer of the open-source langgraph-harness (self-described: A GitLab agent on LangGraph.js that reviews merge requests, resolves issues and chats, in production since June 2026), Reddit post, r/LangChain, published Oct 7, 2026
- [BUG] Resuming after a tool error re-runs the tool node, repeating a side effect that already happenedFurkhanShaikh, GitHub user filing an issue (self-described: Quickstart agent with a checkpointer and a payment tool that times out after committing), GitHub issue, published Oct 4, 2026
- From Supervisor to Deep Agents: Re-Architecting a Production GTM Assistant Without Breaking TrustAniruddha Laud and Anshul Pahwa, AI engineers, Apollo.io (self-described: Apollo.io AI assistant for go-to-market teams), Conference talk, Interrupt NYC 2026 (LangChain YouTube channel), published Sep 29, 2026
- How Airbnb builds Trust for Guests and Hosts using AI Agents with LangGraphPedro Rodriguez, Director of Engineering, ML, Airbnb (self-described: Airbnb trust agents deciding guest and host cases), Conference talk, Interrupt NYC 2026 (LangChain YouTube channel), published Sep 29, 2026
- CrewAI and LangGraph both reported a connected integration that delivered nothingyiddo_bhushan, operations at Shogo (self-described: Wiring an agent to a team channel through framework integrations), Reddit post, r/AI_Agents, published Sep 25, 2026
- How GitLab reduced code-per-agentic-flow ratio by 45%Mikolaj Wawrzyniak, GitLab Duo Agent Platform team (self-described: GitLab Duo Agent Platform, whose production agent flows compile from YAML into LangGraph graphs), Engineering blog post, GitLab blog, published Sep 22, 2026
- LangGraph for complex handoffs, CrewAI for role-based workApart-Currency7380, Reddit commenter (self-described: Choosing between CrewAI and LangGraph for multi-agent handoffs), Reddit comment, r/LangChain, published Sep 22, 2026
- I built the same agent in Strands, LangGraph, and CrewAI, and recorded every LLM call to see how they actually differsunnydachs, Independent developer (self-described: Same digest agent built in Strands, LangGraph, and CrewAI; 27 recorded runs), Personal blog post, dev.to, published Sep 21, 2026
- Comment on: Show HN: Pizza Bot - An inbox for AI agents that work in the backgroundjd_, Hacker News commenter (self-described: Pizza Bot team; background agents with checkpointing and human-in-the-loop), Hacker News comment, published Sep 16, 2026
- Harness, Loop, and Graph: What I Learned Building the Same AI Agent Three Different WaysAli Suleyman TOPUZ, Software architect writing on agent design (self-described: Same agent built as a harness, a loop, and a LangGraph graph), Personal blog post, dev.to, published Aug 28, 2026
- Why We Removed LangGraph From Our AI PlatformNicola Richli, yeos.ai (self-described: yeos.ai enterprise AI platform serving multiple customers), Company blog post, dev.to, published Jul 27, 2026
- How Bridgewater Built an AI Analyst That Does Hours of Expert Research in MinutesBrendan McManus, Michael Ran, and Santi Weight, Applied AI team, Bridgewater Associates (self-described: PAT, an internal AI analyst used by hundreds of investors), Conference talk, Interrupt 26 (LangChain YouTube channel), published Jul 24, 2026
- Building ToyotaGPT: 50+ Production Agents, One Config File, Zero Architecture ReviewsRavi Chandu Ummadisetti and Kordel France, Head of agent AI and product research, and head of AI engineering, Toyota (self-described: ToyotaGPT, Toyota's enterprise agent platform with 50+ agents in production), Conference talk, Interrupt 26 (LangChain YouTube channel), published Jul 15, 2026
- Eval-Driven Development, LLM-Generated SQL, & the Cost-Uncertainty-Lag Triangle: Rippling's PlaybookSenthil Velu Sundaram and Akash Ashok, Rippling AI team (self-described: Rippling AI assistant over the employee graph), Conference talk, Interrupt 26 (LangChain YouTube channel), published Jul 13, 2026
- How LATAM Airlines Built Intelligent Agents in Aviation | Interrupt 2026Nico Venegas and Claudio Urbina Lara, LATAM Airlines AI team (self-described: LATAM Concierge travel agent, about 4,000 daily users), Conference talk, Interrupt 26 (LangChain YouTube channel), published Jun 30, 2026
- astream_events v3 dropped cache and reasoning token detailsjasonhanna, GitHub user filing an issue (self-described: Production agents moved to v3 streaming, monitored in Arize Phoenix), GitHub issue, published Jun 16, 2026
- Comment on: Show HN: Brightdeck - an OOXML-compatible AI presentation makermfn-throw, Hacker News commenter (self-described: Two-person team building an AI presentation editor), Hacker News comment, published Jun 13, 2026
- The Etsy Gifting Assistant: From Prototype to Production | Interrupt 26Derrick Kondo, Engineer, GenAI Enablement team, Etsy (self-described: Etsy gifting assistant, about three senior engineers and one designer), Conference talk, Interrupt 26 (LangChain YouTube channel), published Jun 8, 2026
- Moved from Google's Agent Development Kit to LangGraphBitter-Pride-157, Reddit user writing on their own blog (self-described: Agent workflows with complex state and loops), Reddit post, r/LangChain, published May 25, 2026
- Comment on: Agentic Coding Is a Trapdbrecht_, Hacker News commenter (self-described: Switchplane, a local-only project published under salesforce-misc), Hacker News comment, published May 4, 2026
- Scaling LangGraph's Postgres checkpointer in productionTadeo Donegana Braunschweig, AI engineer on Tiendanube's merchant copilot team (self-described: Tiendanube's conversational copilot for merchants, a LangGraph multi-agent system with more than 120,000 conversations a week), Engineering blog post, author's blog, published Apr 28, 2026
- LangGraph in Production: Building Stateful AI AgentsAnil Gulecha, Co-Founder & CTO, Kalvium Labs (Kalvium Labs, six LangGraph agents built for clients, including document review and approval workflows), Engineering blog post, Kalvium Labs blog, published Apr 27, 2026
- Why I Stopped Using LangGraphDeadLocker, Developer with a traditional software engineering background (self-described: Used LangGraph in 8 of 10 AI projects), Personal blog post, dev.to, published Apr 23, 2026
- langgraph 1.1.7 broke OpenTelemetry instrumentation with a TypeErroraidandaly24, GitHub user filing an issue (self-described: LangGraph agents instrumented with opentelemetry-instrumentation-langchain), GitHub issue, published Apr 17, 2026
- Swapping the model in a LangGraph multi-agent system is an integration projectm3m3o, builder of a LangGraph shopping assistant (self-described: A LangGraph shopping assistant with 5 agents, moved from Llama 3.1 70B to Llama 4 Maverick), Reddit post, r/LangChain, published Apr 13, 2026
- Long tool calls (~180s+) silently re-executed from checkpoint on LangGraph CloudMarioAlessandroNapoli, GitHub user filing an issue (self-described: Deep agents dispatching sub-agents that run 3 to 10 minutes on LangGraph Cloud, EU, Plus tier), GitHub issue, published Apr 5, 2026
- Comment on: Ask HN: Learning resources for building AI agents?7e10, Hacker News commenter (self-described: Full-stack MERN developer, built a Google Analytics 4 agent), Hacker News comment, published Apr 4, 2026
- Comment on: The Claude Code Source Leak: fake tools, frustration regexes, undercover modeossa-ma, Hacker News commenter, self-described, Hacker News comment, published Mar 31, 2026
- From firefighting to building: How AI agents restored our team's core productivitySneh Agrawal, Rishi Raj, Ayan Chatterjee, Wen Zhong Tan, and Sai Reddy Kakumanu, Grab (self-described: Grab's Analytics Data Warehouse team, answering data questions from over 1,000 users a month with a multi-agent system), Engineering blog post, Grab Tech Blog, published Mar 19, 2026
- Memory leak: _checkpointer_put_after_previous coroutine chains accumulate with default durability="async"celyrt2-alt, GitHub user filing an issue (self-described: Graph run with a checkpointer that has write latency, such as Postgres), GitHub issue, published Mar 10, 2026
- Comment on: I built a time-travel debugger for AI agentsredhanuman, Hacker News commenter (self-described: LangGraph agent in production), Hacker News comment, published Mar 9, 2026
- Comment on: Building an Autonomous AI Sysadmin with LangGraph, Ansible, and SQLitemichael-elias, Hacker News commenter (self-described: Solo AIOps agent that acts on infrastructure), Hacker News comment, published Mar 2, 2026
- Comment on: Cord: Coordinating Trees of AI Agentssriku, Hacker News commenter (self-described: Team product build), Hacker News comment, published Feb 21, 2026
- Comment on: Show HN: Agent framework that generates its own topology and evolves at runtimeomhome16, Hacker News commenter, self-described, Hacker News comment, published Feb 12, 2026
- LangGraph [1.0.6] Bug - Agent infinite looping until recursion limit error is hitjacobreesmontgomery, GitHub user filing an issue (self-described: Text-to-SQL agent on Azure OpenAI with a Databricks schema), GitHub issue, published Jan 30, 2026
- Comment on: Benchmarking OpenTelemetry: Can AI trace your failed login?jcims, Hacker News commenter (self-described: Building an SRE agent with access to source code, CI/CD and infra control plane), Hacker News comment, published Jan 29, 2026
- Comment on: Ask HN: Anyone using Claude Agent SDK in production?dragonmage65535, Hacker News commenter (self-described: Team running LangGraph in production), Hacker News comment, published Jan 24, 2026
- Comment on: AI hallucinate. Do you ever double check the output?7777777phil, Hacker News commenter (self-described: Research automation built with LangGraph over two months), Hacker News comment, published Jan 23, 2026
- Incompatibility between langgraph-cli and langgraph-api >= 0.7.0farouk09, GitHub user filing an issue (self-described: Backend project using langgraph-cli and langgraph-api), GitHub issue, published Jan 21, 2026
- Flag Early, Fix Faster: Real-Time Intervention for Supplier Transfers with WilmaFarshid Bahrami, Atharva Deo, Roger Bock, Ying Jiang, and Luming Wang, Wayfair (self-described: Wayfair customer service: flags supplier-customer tickets that need an associate, in about one second per comment), Engineering blog post, Wayfair Tech Blog, published Jan 15, 2026
- Lessons Learned from Building LinkedIn's First Agent: Hiring AssistantKarthik Ramgopal, Distinguished Engineer, and Daniel Hewlett, Principal AI Engineer, LinkedIn (self-described: LinkedIn's generative AI platform and the Hiring Assistant agent), Conference talk transcript, InfoQ (QCon London 2025), published Dec 31, 2025
- Comment on: Show HN: Sim - Apache-2.0 n8n alternativethreecheese, Hacker News commenter, self-described, Hacker News comment, published Dec 12, 2025
- Pydantic AI with Samuel ColvinSamuel Colvin, founder of Pydantic (self-described: Choosing an agent framework for Pydantic Logfire before building Pydantic AI), Podcast episode, Software Engineering Daily, published Dec 4, 2025
- Comment on: Python is not a great language for data scienceaussieguy1234, Hacker News commenter (self-described: Open source developer, built Tunnelmole), Hacker News comment, published Nov 25, 2025
- Comment on: Agent design is still hardmunro, Hacker News commenter, self-described, Hacker News comment, published Nov 22, 2025
- Comment on: Wrapping my head around AI wrappers_fat_santa, Hacker News commenter (self-described: SaaS app team), Hacker News comment, published Nov 20, 2025
- Comment on: Wrapping my head around AI wrappersembedding-shape, Hacker News commenter, self-described, Hacker News comment, published Nov 20, 2025
- Comment on: LangChain raises US$125M to build the platform for agent engineeringshcallaway, Hacker News commenter (self-described: Team agents on the LangGraph TypeScript SDK, hosted on LangGraph Platform for about a year), Hacker News comment, published Oct 21, 2025
- Comment on: Ask HN: Do you roll your own agent or use a framework?jamesbriggs, Hacker News commenter (self-described: Aurelio Labs team; built its own graphai framework), Hacker News comment, published Oct 8, 2025
- Comment on: Ask HN: Do you roll your own agent or use a framework?tag_coder, Hacker News commenter (self-described: Professional developer, built agents in previous roles), Hacker News comment, published Oct 7, 2025
- Comment on: Ask HN: What are you working on (September 2025)?mahdiyar, Hacker News commenter (self-described: Builds open-source agent tools tinyAgent and Roundtable), Hacker News comment, published Sep 25, 2025
- The LinkedIn generative AI application tech stack: extending to build AI agentsKarthik Ramgopal and co-authors, LinkedIn Engineering (self-described: LinkedIn's agent platform behind Hiring Assistant, built on its messaging and memory infrastructure), Engineering blog post, LinkedIn Engineering Blog, published Sep 10, 2025
- Comment on: Ask HN: How are you scaling AI agents reliably in production?prohobo, Hacker News commenter (self-described: AI ecommerce analyst app; daily report per customer queued with BullMQ), Hacker News comment, published Aug 15, 2025
- Comment on: Open SWE by LangChainNeutralCrane, Hacker News commenter, self-described, Hacker News comment, published Aug 8, 2025
- AsyncPostgresSaver 2.0.23 fails to read channel values: NoneType object is not a mappingManuelAngel99, GitHub user filing an issue (self-described: Service reading checkpoints with AsyncPostgresSaver), GitHub issue, published Jul 27, 2025
- Run Cancellation Causes Loss of Streamed State Not Yet Persisted as a Checkpointibbybuilds, GitHub user filing an issue (self-described: Chat UI on LangGraph Platform with run cancellation), GitHub issue, published Jul 25, 2025
- Lessons from 6 Months of Building AI AgentsMariano Álvarez, Developer building AI agents (self-described: Six months of agent building, starting with LangGraph), Personal blog post, dev.to, published Jun 20, 2025
- Comment on: Building Effective AI Agentsdavedx, Hacker News commenter (self-described: Entrepreneur and programmer), Hacker News comment, published Jun 18, 2025
- Comment on: Building Effective AI AgentsiLoveOncall, Hacker News commenter (self-described: Team project at work), Hacker News comment, published Jun 17, 2025
- How LinkedIn Built Their First AI Agent for Hiring with LangGraph | LangChain InterruptDavid Tag, AI team, LinkedIn (self-described: LinkedIn Hiring Assistant and the agent framework used by 20+ teams), Conference talk, Interrupt 2025 (LangChain YouTube channel), published Jun 13, 2025
- How BlackRock Built Production AI Agents for Asset Management with LangGraph | LangChain InterruptBrennan Rosales and Pedro Vicente Valdez, AI engineering lead and principal AI engineer, BlackRock (self-described: Aladdin copilot, agents contributed by many engineering teams), Conference talk, Interrupt 2025 (LangChain YouTube channel), published Jun 12, 2025
- 0.4.4 ModuleNotFoundError: No module named 'langgraph.cache'ajhwb, GitHub user filing an issue (self-described: Following the LangChain RAG tutorial), GitHub issue, published May 15, 2025
- Langgraph Graph API Generates Unexpected Conditional Edge to END in v0.3.32+ Compared to v0.3.31sumanmichael, GitHub user filing an issue (self-described: Graph with conditional edges rendered through draw_mermaid), GitHub issue, published Apr 24, 2025
- Comment on: Quick Primer on MCP Using Ollama and LangChainjsemrau, Hacker News commenter, self-described, Hacker News comment, published Apr 14, 2025
- Iron Man inspires Cisco's AI-driven platform engineerHasith Kalpage, CISO and Platform Engineering Director, Outshift by Cisco (Outshift's JARVIS platform engineer, with over 15 sub-agents serving internal engineers through Backstage, Webex, Jira, and a CLI), Interview, Network World, published Apr 1, 2025
- Comment on: We chose LangGraph to build our coding agentfour_fifths, Hacker News commenter, self-described, Hacker News comment, published Mar 25, 2025
- Comment on: We chose LangGraph to build our coding agentjeffspinny, Hacker News commenter, self-described, Hacker News comment, published Mar 25, 2025
- Comment on: We chose LangGraph to build our coding agentleopoldj, Hacker News commenter, self-described, Hacker News comment, published Mar 25, 2025
- Comment on: We chose LangGraph to build our coding agentTimPC, Hacker News commenter, self-described, Hacker News comment, published Mar 25, 2025
- Comment on: We chose LangGraph to build our coding agentdiego898, Hacker News commenter, self-described, Hacker News comment, published Mar 25, 2025
- Comment on: Why we chose LangGraph to build our coding agentKydlaw, Hacker News commenter (self-described: Team evaluation in November 2024), Hacker News comment, published Mar 24, 2025
- Comment on: Why we chose LangGraph to build our coding agentmokarma, Hacker News commenter, self-described, Hacker News comment, published Mar 24, 2025
- Comment on: Why we chose LangGraph to build our coding agentCharlieDigital, Hacker News commenter (self-described: Series-C former YC startup Motion, hiring C# devs, per profile), Hacker News comment, published Mar 24, 2025
- Why we chose LangGraph to build our coding agentSagi Medina, Qodo (self-described: Qodo's coding agent, from first prototype to production), Engineering blog post, Qodo blog, published Mar 21, 2025
- Comment on: Ask HN: What agentic AI frameworks have you used, and did you like them?joshSzep, Hacker News commenter (self-described: Solo toy project built twice), Hacker News comment, published Mar 18, 2025
- langgraph-checkpoint-postgres (psycopg.OperationalError: sending query and params failed: SSL error: bad length) encountered across multiple versionshubhamnegikellton, GitHub user filing an issue (self-described: ReAct agent with AsyncPostgresSaver and a connection pool), GitHub issue, published Mar 6, 2025
- Comment on: Agno: Agent framework 10,000x faster than LangChaintomnipotent, Hacker News commenter, self-described, Hacker News comment, published Mar 6, 2025
Mar 2025 to Oct 2026.
79 sources from practitioners, by month and sentiment.
Where It Fits
Where does LangGraph belong in the stack?
LangGraph is Core across Build, supports Operate, and touches Model, Data, and Evaluate.
- Business area
- Product & Engineering
- Function
- Software Development
- Operating stack
- AI Application Platform
- Primary role
- Agent Orchestration Framework & Runtime
Model
Model APIs: Touches
Model APIs, touches. LangGraph nodes call any model provider through LangChain's chat model integrations or the provider's SDK. LangGraph supplies no models.
Model gateway: Touches
Model gateway, touches. A node can choose a model in code. A gateway handles rate limits and cross-provider fallbacks, along with spend controls.
Build
Orchestration: Core
Orchestration, core. The Graph API and Functional API define agent steps and branches in Python and JavaScript. The runtime adds three checkpoint durability modes, interrupts, time travel, subgraphs, and streaming.
Tool use: Supports
Tool use, supports. Tool calls run as graph steps. An interrupt holds an action for human approval. LangChain integrations or your code supply tool definitions and MCP connections.
Data
Retrieval: Touches
Retrieval, touches. Your code runs retrieval in a node, and the store keeps memory across threads. A retrieval product handles document indexing and vector search.
Evaluate
Evaluation: Touches
Evaluation, touches. Nodes are functions your team can unit test. Time travel replays a saved checkpoint. An evaluation tool such as LangSmith supplies datasets, evaluators, and experiments.
Operate
Observability: Touches
Observability, touches. Stream modes expose updates, checkpoints, tasks, and debug events. Studio shows local runs step by step. Production traces go to LangSmith when LANGSMITH_TRACING is set, or to your tooling.
Cloud deployment: Supports
Cloud deployment, supports. The CLI packages a graph into an Agent Server for LangSmith Deployment in LangChain's cloud, hybrid, self-hosted, or standalone setups. The library also runs in your services, where your team owns scaling.
Guardrails: Touches
Guardrails, touches. LangGraph interrupts pause graph execution for external input, including approval or review of tool calls. Teams implement the screening decision in the interrupted workflow.
Market mapThe layers LangGraph covers, and who else owns each one.
Orchestration & agent frameworks
Tool use & integrations
Cloud deployment & capacity
Model APIs
Model gateways & routing
- LiteLLM
- OpenRouter
- Portkey
- Vercel AI Gateway
4 more layers on the full map. Core, Supports and Touches describe coverage. They say nothing about quality.