agent-architectures

An interactive benchmarking dashboard to compare and visualize multi-agent architectures (single, hybrid, dynamic swarm) in real-time. Analyze tradeoffs in quality, latency, and cost. Inspired by Google's "Science of Scaling Agent Systems" paper and powered by LangGraph + Gemini.

Reactive, BDI, layered, and utility-based agent design patterns with runnable examples.

Cognitive Outsourcing (CO): edge-AI architecture empowering 0.8B–4B models with dynamic access to cloud LLM teachers, tools, and local caches via Suspend-and-Inject Generation (SIG). Keeps KV-cache intact across tool calls—up to 96% prefill savings and 1.57× speedup.

Deterministic companion demo for bounded mirror-recognition evaluation under explicit governance.

A collection of the messy problems I've hit, the weird fixes I found, and the refactors that finally made things behave. Basically, my debugging diary, but useful.

AI Agent Reference Architecture Patterns

AI learning and experimentation repo — structured study notes, code experiments, and research on RAG systems, agent architectures, and LLM evaluation methods.

Visual Streamlit playground implementing six LLM agent architectures (Single LLM, Tool Calling, ReAct, Plan-and-Execute, Reflection, Reflexion) on a shared event-driven runtime — showing how each plans, calls tools, and self-corrects.

Classical AI agent architectures are not obsolete: an LLM upgrades one component inside them and leaves the architecture standing. Twenty runnable before/after pairs, nine config-driven agents across all five architectures, and every claim shipping with the command that checks it.