PILLAR 01Sub-Brand Architecture

AI Research & Innovation

Deconstructing frontier theoretical machine learning into architectural breakdowns, mathematical proofs, and runnable code.

Core Research & Technical Scope

Local LLMs (vLLM, Ollama)Quantization (AWQ, GGUF, INT4/FP8)FlashAttention & MoEMamba / State Space ModelsCUDA & OpenAI Triton Kernels

Pillar Publications & Deep Dives(1)

Research Paper20 awgust 2026

Autonomous LLM Agents: Planning Loops, Tool Interfaces, and Failure Recovery

A comprehensive guide to autonomous LLM agent systems, explaining multi-step compound errors, ReAct loops, verbal reflection memory, Agent-Computer Interfaces, and failure recovery.

#llm-agents#react#reflexion#tool-use#machine-learning#agent-computer-interface#python312