Agentic AI

Multi-agent system – two AI reviewers independently evaluate the same claim, a third layer detects when they disagree, and a human decides what happens next.

Multi-agent market intelligence system – three specialist agents research any company and a manager synthesizes their findings, with built-in conflict detection.

DSPy replaces hand-written prompts with compiled programs that optimize themselves.

Building a planning agent that breaks any business goal into a dependency-ordered task sequence using a DAG and topological sort.

Python client that connects to a self-hosted AnythingLLM instance, giving it private document intelligence without sending data to the cloud.

Building an agent that runs real statistical analysis in Python before the AI sees a single number.

An AI assistant persistent memory across sessions without a database or server.

Building an AI agent that remembers past interactions, plans multi-step workflows, and decides when to act alone or escalate to a human. Here is how it works.

Building a two-agent AI workflow where a Researcher and Writer work together automatically. What I discovered about model-agnostic multi-agent architecture.

Building a working PDF knowledge agent in Flowise using drag-and-drop blocks, no code required. Here is how it works and what I learned.