Three-Project Series

From Prompts to an Agentic System

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prerequisites
Basic Python • Web API usage
skills learned
Creating a chatbot that demonstrates specific human-facing characteristics, like empathy and altruism • Persona design • Advanced prompt engineering • LangChain chatbot development • RAG (retrieval-augmented generation) • agent reasoning
Jeremie Charlet
3 weeks · 2-8 hours per week average · INTERMEDIATE

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As its public face, a chatbot needs to project the values and character of the organization it represents. In this series of liveProjects, you’ll help out a local pet refuge by building an AI-powered chatbot that shares both the knowledge and the attitudes of that compassionate institution. Starting with prompt engineering and persona design, you’ll progressively layer in curated search, multi-use case handling, and callback scheduling. You’ll take advantage of OpenAI’s API along with LangChain and LangGraph to create a custom assistant that can deliver 24/7 pet care guidance. By the end, you’ll have a sophisticated AI agent that blends empathy, domain-specific knowledge retrieval, and intelligent routing.

These projects are designed for learning purposes and are not complete, production-ready applications or solutions.

here's what's included

Project 1 Designing Persona & Core Skills

In the first liveProject, you’ll create a basic chatbot that can reliably field questions in a way that’s consistent with the mission of the pet refuge. You’ll craft structured, effective prompts and design a persona for your chatbot, implement the basic functionality, and then test, refine, and improve your chatbot with iterative evaluation.

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Project 2 Add Curated Knowledge Base Search
In this second liveProject, you’ll add Retrieval Augmented Generation (RAG) to a pre-existing chatbot so that it can provide up-to-date and reliable responses to questions fielded by the pet refuge. First, you’ll connect your chatbot to a document store and test it on real pet care questions to ensure answers are grounded in reliable sources. Then, you’ll improve retrieval quality by expanding the knowledge base, refining queries to better capture user intent, and adding smart filters for more relevant, precise results.
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Project 3 Build a Reasoning & Workflow Agent

In the third liveProject, you’ll upgrade the capabilities of the RAG-enhanced chatbot, turning it into a multi-use-case agent using advanced reasoning, custom tools, and the ReAct framework. First, you’ll build a robust prompt chain with reasoning to classify queries and route them to the right path. Next, you’ll add practical tools and workflows with LangGraph to handle out-of-scope cases, capture user info, and blend retrieval with classification. Finally, unify everything into an agentic system that can choose tools, search knowledge, collect details, escalate when needed, and keep conversations natural.

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books resources

When you start each of the projects in this series, you'll get full access to the following books for 90 days.

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project author

Jeremie Charlet
Jeremie Charlet is a freelance data science consultant specializing in NLP, MLOps, and generative AI product strategy. He has over a decade of experience delivering AI-powered solutions for startups, scaleups, and the UK government. As a startup founder, he is currently focusing on applying AI to support people with meditation and mental health. In addition, he teaches data science and generative AI in leading French business and engineering schools and has mentored ML practitioners through study groups and professional communities.

Prerequisites

This liveProject series is for Python programmers ready to develop basic chatbots into sophisticated AI agents with accurate personas. You should be comfortable with Python scripting and eager to learn advanced prompt engineering, custom tool development, and agent frameworks.


TOOLS
  • Intermediate Python
  • Basics of Jupyter Notebook
TECHNIQUES
  • Basics of text processing
  • Basics of file management
  • Basics of data structures
  • Basics of prompt engineering
  • Basics of API Integration
  • Basics of Retrieval Augmented Generation

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from fellow participants and even more help with paid sessions with our expert mentors.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.