
Build an autonomous airline assistant from scratch with agent-driven workflows for triage, flight modification, and cancellation. Validate requests against policies and escalate to humans; compare react-based reasoning with open AI.
Sign up at openai.com, log in, and open the dashboard or API keys to create your secret key. Copy it and save it securely for use in the project.
Clone the repository, switch to the start branch, set up a Python environment, install requirements, and export the OpenAI API key to run a basic autonomous app.
Build a basic react reasoning in action skeleton with data models, an executor, and agents; map thought, action, and observation to drive automated task execution via the OpenAI API.
Implement the react loop by iterating thought, action, and observation using a base agent and multiple agents, tracking total interactions until a final answer is produced.
Learn to create simple tools for the react executor, including a calculator tool and a people search agent, wrap them as tools, and integrate with the main agent.
Learn to handle tools execution within a multi-tool agent, including selecting actions, validating tool types, inspecting parameter signatures, and simulating ChatGPT-driven parameterization.
Build a memory-enabled brain for a react executor that thinks through prompts, recalls past messages, and uses the OpenAI API to return structured responses.
Refine the React paradigm implementation by organizing code, adding a Wikipedia search tool and a today tool, and updating the main agent with clear instructions.
Implement observation, choosing action, and execution action in a React-based autonomous app, wiring prompts, tools, and parameter handling to drive iterative backtracking and execution.
Wrap up the first version of the autonomous question-answering app by reorganizing code under version 1 and running checks. Prepare for version two, focused on the OpenAI API using functions.
Begin building the autonomous app by adding a timestamped, colored debug printer and a JSON wrapper for OpenAI functions, then set up an agent runner for an airline Q&A example.
Implement an app runner with a looping workflow that constructs and sends a ChatGPT payload to the OpenAI API, incorporating context, system messages, tools, and history tracking.
Explore how OpenAI function calling works, passing tools and parameters to guide the LLM in choosing and executing functions like weather lookups or baggage transfers, enabling autonomous apps.
learn to handle tool execution by building a function map, validating tool calls, and executing available tools. update a partial response with results and prepare for subsequent agent-driven tasks.
Discover next steps for building autonomous applications by exploring retrieval, augmented generation, rogue agents, memory agents, and semantic search, with deeper insights into genetic and autonomous system design.
Unlock the potential of autonomous applications with our groundbreaking course, “Building Autonomous Apps using AI Agents from Scratch.” Tailored for developers looking to master the art of agentic software creation without relying on frameworks. That is correct. no third party libraries!
Learn to develop autonomous systems that not only perform tasks but understand and adapt to user needs in real-time
In this course, you will understand the underlying technologies behind transformative applications like AutoGPT, Anthropic’s Compute, and Devin AI, along with agentic frameworks including CrewAI, LangChain, and LlamaIndex.
This course offers a deep dive into the mechanics of building intelligent apps from the ground up. Learn to develop autonomous systems that not only perform tasks but understand and adapt to user needs in real-time.
What You Will Learn:
• Framework-Free Development: Start with the basics and advance to building complex autonomous applications entirely from scratch. Gain a comprehensive understanding of the internal workings of each component and learn how to optimize algorithms effectively.
• Explore Cutting-Edge Models and Applications: Understand the underlying technologies behind transformative applications like AutoGPT, Anthropic’s Compute, and Devin AI, along with agentic frameworks including CrewAI, LangChain, and LlamaIndex.
• The ReAct Prompt Methodology: Delve into the ReAct prompt—a synergistic approach combining reasoning and action in language models. Learn how it integrates within AI agent workflows to autonomously perform multiple tasks based on user inputs.
• Advanced Prompt Engineering: Master the crucial skill of crafting prompts that direct AI models to provide optimal, context-aware responses, essential for complex reasoning and user interactions.
• Interactive Code-Along Sessions: Engage in detailed, real-time coding tutorials throughout each module, allowing for immediate application of concepts and techniques. This hands-on approach ensures you solidify your understanding and enhance your coding proficiency.
• Capstone Project: Apply everything you’ve learned by developing an autonomous airline customer service application. This final project will showcase your ability to create sophisticated, interactive AI systems that are both innovative and practical.
Course Benefits:
By the end of this course, you will not only understand the theoretical aspects of creating autonomous AI applications but will also possess the hands-on experience needed to develop state-of-the-art intelligent systems. You’ll emerge with the skills to create apps that not only function autonomously but also truly engage with and understand user interactions.
Who Should Enroll:
This course is ideal for developers and software engineers curious about AI agent development and those aspiring to pioneer the next generation of intelligent applications.