LOCKEDIN / FORWARD-DEPLOYED ENGINEERING 101
Understand it.
Then build it.
You can be an experienced engineer and still be new to agents. Start with what each thing is and how it helps a person do useful work. Explore 48 original introductions across software, agents, cloud, security and delivery. Start here without a model key; each topic connects to deeper instruction and practice.
- 101UnderstandPlain language, visual walkthrough, vocabulary
- 102Build with guidanceOriginal lessons, examples and knowledge checks
- 103Practise and explainRunnable labs, failure cases and handover
- 01Connect a model
- 02Provide a tool
- 03Run and inspect
An open-source software framework
What is LangChain?
LangChain is a software framework with building blocks for applications that use language models. You use it from languages such as Python or JavaScript to connect a model, give it tools and run an agent loop. LangChain is not a model, a programming language or a replacement for your application's security rules.
It can save you from writing every model integration and tool-calling loop yourself. You still need to understand the task, validate tool inputs and test the behavior you deliver.
CONNECT IT TO WHAT YOU KNOW
Start with something familiar.
If you have used a web framework to assemble routing, handlers and middleware, the role is familiar: LangChain provides building blocks and abstractions for assembling model-and-tool applications.
LangChain is a software framework. It does not supply the business authority of a tool or guarantee that an agent's answer is correct.
Words worth knowing
- Framework
- Reusable software that supplies structure and common building blocks for your application.
- Integration
- Code that connects your application to another model, tool or service.
- create_agent
- LangChain's entry point for configuring and running an agent loop.
ONE EXAMPLE / FICTIONAL CASE
Watch the work take shape.
Think about the maintenance assistant. LangChain helps connect the model to a lookup function. Your own application still decides which procedures the signed-in person can read and whether any action may run.
- 01Connect a model
- 02Provide a tool
- 03Run and inspect
Connect a model
Choose a model integration. The model will interpret the request and propose a response or tool call.
A model that accepts your application's messagesFROM RECOGNITION TO REASONING
Draw the smallest useful one-tool agent.
- 01
Name the model, one read-only tool and the task.
- 02
Put identity and data scope outside model-supplied arguments.
- 03
Add a maximum number of tool calls and an insufficient-evidence result.
A four-part diagram: model, tool, trusted context and stop rule.
Compare your reasoning when you are ready
The framework coordinates calls, while trusted application context limits which data the tool may read. The loop must stop even when the model keeps requesting more work.
Keep notes in your own working copy. Moving through these cards does not record completion.
TURN THE IDEA INTO USEFUL WORK
You can now go deeper.
Use LangChain for model, tool and agent-loop building blocks. Your application remains responsible for access, limits and useful results.
Academy lessons use your existing training access. Free guides stay open.