LangChain
Hire LangChain developers who know when to stop using it
We prototype in LangChain and ship the parts worth keeping. On Cruise Search AI, that meant the LangGraph agent runtime and the provider interface. It did not mean every chain the prototype started with.
What you are getting
4 things that decide this
- 01Senior engineers who can say, chain by chain, which LangChain abstractions they kept in a production build and which they replaced with plain code, and why.
- 02Evals run against real test cases, not traces read after something broke. A trace shows what happened once. An eval shows what happens across a hundred inputs.
- 03A clear answer on the LangGraph line: when a stateful agent runtime earns its complexity, and when a fixed sequence of steps is the honest choice instead.
- 04You interview each engineer yourself. The chains, the prompts and the eval suite are yours from the first commit.
The role, precisely
LangChain is fast for getting a language model feature answering questions inside a day. That speed is real, and it is also not the hard part of the job.
The hard part is deciding, once a prototype works, which pieces of the framework a production system should keep. Our engineers have replaced LangChain chains with plain code about as often as they have shipped them. A thin wrapper around one prompt call is usually longer than the code it hides.
Cruise Search AI is a good example, built for a military and veteran cruise-booking site. The parts that survived were the provider interface and the LangGraph agent runtime underneath it. Redis held session state while a traveler described a trip in plain words. That distinction, kept versus replaced, is what a buyer is actually paying for.
The judgment a senior LangChain hire brings
Knows what to drop
Chains wrapping a single model call rarely survive review. They can point to the line where the wrapper stopped earning its place.
Runs evals, not traces alone
A trace explains one run after the fact. An eval scores the system against a fixed set of inputs before you ship a change.
Knows the LangGraph line
A fixed sequence of steps needs no graph. A conversation that branches on what the user says needs state that survives across turns.
Keeps the prompt visible
If a wrapper hides the exact request sent to the model, every debugging session starts by reading library source instead of your own code.
Versions prompts like code
Prompts live in your repository under review, not inside an object a framework assembles for you at runtime.
- PrototypeLangChain, fast to a working demo
- ProviderOne interface. Usually kept.
- ChainsReviewed. Often replaced with code.
- Agent stateLangGraph, where it earns it
- Eval suiteYours, scored before every change
- ProductionOnly what survived the review
The middle two stations are the judgment call. Skipping the review is how a prototype's shortcuts end up in production unexamined.
LangChain-adjacent systems in production
How hiring works
- 01
Describe the prototype or the problem
A free call about what your LangChain build does today, and where it breaks under real traffic or real users.
- 02
Meet the engineers
We shortlist engineers who have taken a LangChain prototype into production, and you interview them your own way.
- 03
They embed
Your codebase, your repository, your deploy process. One engineer owns the chain review and the eval suite, and answers for both.
- 04
They hand over
A documented list of what stayed, what got replaced, and the eval cases that prove it. Where a client wants it watched after launch, we stay on under a service level we agree. The first 2 months of support and maintenance are free, with every build.
Stack
Framework
Production layer
Practices
Bring us the prototype you are not sure will hold
Show us what it is built on today. The scoping call is free, and you will leave knowing which parts of the framework earn a place in production.
01Do we need LangChain, or should we call the model API directly?
Plenty of solid systems call the provider SDK directly and skip the framework entirely. LangChain earns its place when you genuinely expect to switch model providers, or when you want the LangGraph agent runtime underneath a stateful conversation. If neither applies, direct calls are less code and easier to debug.
02What changed with LangChain v1, and does our code need to move?
The core namespace narrowed to agents, messages, tools, chat models and embeddings. Legacy chains, retrievers, the indexing API and the hub module moved to a separate langchain-classic package. That makes an upgrade a scheduled project of updating imports, not a version bump you run without reading the changelog.
03How do you decide what to replace with plain code?
By reviewing every chain once the prototype works and asking what it would cost to remove. If the answer is fewer than fifty lines of direct code, the wrapper was adding indirection without removing real complexity. Usually the provider interface and the agent runtime survive, and chains wrapping a single prompt call do not.
04What is the difference between hiring for LangChain and LangGraph?
LangChain is the wider toolkit: a provider interface, prompt templates, retrieval helpers. LangGraph is the piece it uses for stateful, branching agents, and it is a separate decision from the rest of the framework. A LangChain hire should tell you plainly whether your problem needs LangGraph at all. Often a simpler sequence of calls does the job.
05Do you run evals, and what does that mean in practice?
Yes. An eval is a fixed set of inputs with a scoring method, run before a prompt or chain change ships. A trace tells you what one run did after the fact. An eval tells you whether the system got better or worse across many runs, which is the only honest way to know a change helped.
06What drives the cost of a LangChain build?
How much of the prototype survives contact with real production traffic, and how many chains need review and replacement. A retrieval feature answering read-only questions is straightforward. One driving actions like bookings or payments needs an eval suite and more testing before launch. Scoping calls are free. Where we must work inside an existing codebase, a paid two-week diagnostic ends with a fixed price.
