Marcus Thorne analyzes the architectural shift from monolithic LLM contexts to Model Context Protocol micro-agents, detailing production failure modes.
Marcus Thorne evaluates the shift from brittle HD maps to real-time VLM sensor fusion in 2026 autonomous vehicle architectures.
Marcus Thorne dissects the breaking points of Model Context Protocol at scale, analyzing state divergence, P99 latency penalties, and orchestration bottlenecks.
An empirical analysis of end-to-end autonomous driving architectures, examining multi-camera sensor fusion latencies and production failure modes.
A hands-on analysis of Model Context Protocol (MCP) runtimes, sub-agent orchestration, and the hidden networking bottlenecks breaking multi-agent systems.
A hands-on analysis of end-to-end neural autonomous driving architectures, sensor fusion bottlenecks, and why deterministic safety layers remain mandatory.
An empirical analysis of Model Context Protocol (MCP) in 2026 enterprise clusters, exposing latency bottlenecks, serialization lockouts, and deadlocks.
Architecting resilient multi-agent runtimes for enterprise automation using the Model Context Protocol (MCP) and deterministic sub-agent execution pipelines.
Executive Agentic Engineering Brief • Desktop Autonomous Systems Unlike structured API-to-API automation, Anthropic’s Computer Use capability treats the graphical user
Executive Synthesis Key Architectural Takeaways & RAG Extraction Empirical benchmarking across SWE-bench Verified and production repository migration tasks reveals distinct
