Uploaded October 2025 | Updated September 2026, 2 weeks ago

---

🚀 The LangChain 10 Days FREE Bootcamp is live: 10 lessons, free AI models only, from your first API call to a production grade RAG agent. Start with Day 0 for the roadmap and setup.

📺 Full playlist: youtube.com/watch?v=KJ3_NExk7-Q&list=PLW4pPr9JCovI&index=1

----------

Welcome to Episode 6 of the LangChain v1 Agents Series! In this episode, you'll learn different methods to configure agent prompts and understand when to use each approach for optimal results.

What You'll Learn:
- Two methods for configuring agent prompts in LangChain
- Using simple string prompts for basic agents
- Implementing SystemMessage for structured prompt handling
- Understanding the differences between prompt methods
- Choosing the right prompt method for your use case
- Testing and comparing agent behaviors with different prompts
- Best practices for production-ready prompt configuration

Tech Stack:
- LangChain v1 (latest prerelease)
- ChatOllama
- LangChain Core Messages
- Qwen 3 model
- SystemMessage class
- Custom helper tools
- Python 3.x

Two Prompt Methods Explained:

Method 1 - Simple String Prompt:
- Direct string instruction to the agent
- Simplest and most readable approach
- Easy to modify and understand
- Perfect for basic use cases and prototyping
- Minimal code overhead

Method 2 - SystemMessage Prompt:
- Structured message object from LangChain Core
- Better integration with chat models
- More explicit about message type
- Professional approach for production systems
- Clearer separation of system vs user messages

When to Use Each Method:
- String Prompt: Simple agents, quick prototypes, basic chatbots
- SystemMessage: Production chat agents, complex systems, professional applications

Code Repository:
github.com/laxmimerit/Langchain-v1-Agents

Full Playlist
youtube.com/playlist?list=PLc2rvfiptPSR2fnZQLmq5TB36E0S0hdW4

Langchain v1 Projects Playlist
youtube.com/watch?v=xOE1yDFGePA&list=PLc2rvfiptPSQzrdPe5apNAq1bbBROUXKh&pp=0gcJCaIEOCosWNin

📚 Learn More with My Udemy Courses
🔥 MCP Mastery: Build AI Apps with Claude, LangChain and Ollama
udemy.com/course/mcp-mastery-build-ai-apps-with-claude-langchain-and-ollama/?referralCode=31C17C306A59601B8689

🚀 Agentic RAG with LangChain & LangGraph
udemy.com/course/agentic-rag-with-langchain-and-langgraph/?referralCode=C0BCC208F53AF2C98AC5

🧠 LangGraph with Ollama
udemy.com/course/langgraph-with-ollama/?referralCode=B646DCB44A189BEBC20C

⚡ Ollama and LangChain
udemy.com/course/ollama-and-langchain/?referralCode=7F4C0C7B8CF223BA9327

🔧 Fine-Tuning LLM with Hugging Face Transformers
udemy.com/course/fine-tuning-llm-with-hugging-face-transformers/?referralCode=6DEB3BE17C2644422D8E

📖 NLP with BERT in Python
udemy.com/course/nlp-with-bert-in-python/?referralCode=063516494616C76907CD

🌐 Connect with Me
Website & Blogs: kgptalkie.com
LinkedIn: linkedin.com/in/laxmimerit
GitHub: github.com/laxmimerit
Twitter (X): twitter.com/laxmimerit

📌 Support the Channel
👍 Like the video if it helps you
💬 Comment your doubts & feedback
🔔 Subscribe for free weekly AI & Data Science content

#DataScience #MachineLearning #LangChain #LangGraph #Ollama #Python #AI #DeepLearning #NLP #GenerativeAI #LLM #HuggingFace #BERT