Thomas Abraham
Full-Stack Engineer & Agentic AI Builder
10+ years building scalable systems across the UK, New Zealand, and India. Now pioneering AI-augmented engineering — systems that think, act, and self-correct.
React · TypeScript · C# · .NET · Azure · LangGraph · RAG · Multi-Agent Systems
Agentic AI Showcases
Five interactive demonstrations of AI systems that reason, act, and self-correct.
Recursive Portfolio Chatbot
A self-correcting RAG agent that answers questions about my background using a real LangGraph correction loop — pgvector retrieval (with mock fallback), Claude Sonnet generation, and a 'See Thoughts' toggle exposing the full trace.
Deep Research Agent
A plan-and-execute autonomous research agent — decomposes a topic, searches sources, cross-references findings, and emits a downloadable PDF. Every node streams its thoughts over SSE so the live trace is the demo.
Software Architect Crew
A 3-agent crew (PM → Coder → Reviewer) that takes a product prompt to reviewed code. Mermaid.js flowchart shows which agent currently holds the token; each agent's reasoning streams live over SSE.
Agent Playground
Live ReAct tool-use playground — Claude Haiku plans each turn against a small tool registry (weather, local time, portfolio recommender) and streams every thought, action, and observation over SSE.
Agent Skills Dashboard
Sample observability UI for agent runs — KPI strip, model latency-vs-success scatter, and per-tool accuracy. Metrics are placeholders today; the page is the aggregation surface that would sit over a production telemetry table.