A visual roadmap of essential roles and tasks for developing production-ready AI agents from idea to launch.
A small pilot project to assess the AI agent's core concept and technical viability.
Rapid Prototyping, Python, LangChain, LLM APIs, Streamlit
Examining data sources to assess their structure, quality, biases, and possible value.
Data Analysis, Statistics, Pandas, NumPy, Matplotlib, SQL
Crafting precise prompts to steer an LLM toward generating the intended response.
LLM Behavior, Creative Writing, Logical Reasoning, JSON
Developing core machine learning models for the agent or fine-tuning domain-specific models.
Fine-tuning a pre-trained model for a targeted domain with a compact, high-quality dataset.
Generating, storing, and retrieving vector embeddings for Retrieval-Augmented Generation (RAG).
Evaluating agent performance with reliable datasets and metrics to track improvements.