Prompt Engineering
Intermediate
Signal 91/100
Prompt Engineering Overview
by Elvis Saravia
Teaches AI agents to
Implement advanced reasoning patterns like ReAct and Tree of Thought in LLM applications
Key Takeaways
- Advanced prompt engineering patterns
- ReAct framework for reasoning and acting
- Tree of Thought prompting technique
- Prompt chaining for complex workflows
- Evaluating and iterating on prompts
Full Training Script
# AI Training Script: Prompt Engineering Overview ## Overview • Advanced prompt engineering patterns • ReAct framework for reasoning and acting • Tree of Thought prompting technique • Prompt chaining for complex workflows • Evaluating and iterating on prompts **Best for:** Engineers building sophisticated LLM reasoning pipelines **Category:** Prompt Engineering | **Difficulty:** Intermediate | **Signal Score:** 91/100 ## Training Objective After studying this content, an agent should be able to: **Implement advanced reasoning patterns like ReAct and Tree of Thought in LLM applications** ## Prerequisites • Working knowledge of Prompt Engineering • Prior hands-on experience with related tools • Comfortable with technical documentation ## Key Tools & Technologies • LangChain • GPT-4 • Claude • ReAct ## Key Learning Points • Advanced prompt engineering patterns • ReAct framework for reasoning and acting • Tree of Thought prompting technique • Prompt chaining for complex workflows • Evaluating and iterating on prompts ## Implementation Steps [ ] Study the full tutorial [ ] Identify the main tools: LangChain, GPT-4, Claude, ReAct [ ] Implement: Implement advanced reasoning patterns like ReAct and Tree of Thought in LLM appl [ ] Test with a real example [ ] Document what you learned ## Agent Execution Prompt Watch this video about prompt engineering and implement the key techniques demonstrated. ## Success Criteria An agent completing this training should be able to: - Explain the core concepts covered in this tutorial - Execute the demonstrated workflow with LangChain - Troubleshoot common issues at the intermediate level - Apply the technique to similar real-world scenarios ## Topic Tags langchain, gpt-4, claude, react, prompt-engineering, intermediate ## Training Completion Report Format - **Objective:** [What was learned from this content] - **Steps Executed:** [Specific implementation actions taken] - **Outcome:** [Working demonstration or artifact produced] - **Blockers:** [Technical issues encountered] - **Next Actions:** [Follow-up tutorials or practice tasks]
This structured script is included in Pro training exports for LLM fine-tuning.
Execution Checklist
[ ] Watch the full video [ ] Identify the main tools: LangChain, GPT-4, Claude, ReAct [ ] Implement the core workflow [ ] Test with a real example [ ] Document what you learned
