Technology Stack
Agentic AI Stack
Building autonomous agents, multi-agent systems, and agent frameworks. The frameworks and tools I use to build, experiment, and ship real solutions.
- BuildReal solutions
- ExperimentContinuously
- StayUp to date
- ShareWhat I learn
- Planning
- Tool Calling
- Memory
- Multi-Agent
- MCP
- Human-in-the-Loop
- Observability
Agentic AI
Building autonomous agents, multi-agent systems, and agent frameworks.
Agents that plan, use tools and act — built with guardrails so they're safe to run in production.
Overview
Agentic AI goes beyond chat: agents break goals into steps, call tools and APIs, keep memory and hand work to other agents. I build these systems with graph-based orchestration, standard tool protocols like MCP and clear human-in-the-loop checkpoints.
The goal is always reliability — agents that behave predictably, can be traced and evaluated, and fail safely.
Key Focus Areas
- Single and multi-agent architectures
- Tool calling and API integration
- Model Context Protocol (MCP) servers
- Agent memory and state management
- Human-in-the-loop workflows
- Tracing, evaluation and guardrails
Tools & Technologies
A selection of the tools and platforms I work with.
LangGraph
LangChain
CrewAI- AutoGen
- Semantic Kernel
Pydantic AI
MCP
OpenAI
Claude- LlamaIndex
n8n
FastAPI
Python
PostgreSQL
Redis
Docker
My Experience Level
Not just tools — real hands-on experience.
- LangGraph85%
- Multi-Agent Design80%
- Tool Calling & Function APIs90%
- MCP Servers80%
- CrewAI / AutoGen70%
- Agent Evaluation70%
Real-World Applications
How I use these technologies in practice.
- Research and analysis agents
- Customer-support agents with escalation
- DevOps and code-review agents
- Document-processing pipelines
- Agents connected to internal tools via MCP
- Workflow automation across SaaS apps
Featured Projects
- Research CrewA multi-agent system that conducts in-depth research on any topic using specialized agents (researcher, critic, summarizer).LangChainCrewAIOpenAI
- MCP IntegrationsExploring Model Context Protocol (MCP) with real-world tools like Google Drive, Notion, GitHub, and custom APIs.MCPPythonNotion API
- AegiSense AI AssistantAn AI-powered assistant for identity and security operations. Uses RAG, tool calling, and guardrails to answer security questions and automate workflows.LangGraphFastAPIPostgreSQL
What's Next?
Continuously learning and exploring.
- Long-running agents with durable state
- Better evaluation suites for agent behaviour
- More open-source MCP servers
- Agent-to-agent protocols
Learning Resources
Articles and tutorials I've written on these topics.
New articles and tutorials on this topic are on the way.
Let's Build Something Amazing
Have a project in mind or want to collaborate? I'm always open to discussing new opportunities.
Let's Talk