Hongyin Luo
Co-Founder & CTO, Subconscious
9 posts by Hongyin Luo
Subconscious Raises $5.1 Million to Build the Inference Platform for Long-Running Agents
MIT researchers discovered a way to dynamically compress up to 80% of an AI agent’s context to make it much more efficient and accurate. Now, they’re turning that core technology into an opinionated inference platform to power agents that run can faster, for longer, at a lower cost with no changes to the underlying hardware, AI models, or apps that use them.
Subconscious + GLM-5.2 Makes "/compact" Obsolete
Model-driven context engineering improves agent inference and reasoning
Subconscious Cache: Reliably Capture Your Agent Context
We introduce an inference runtime optimization specifically for agent systems with automated context pruning and the underlying caching technology to make it happen.
Context Intelligence is the Key for AI Agents: March 2026 Benchmarks
The benchmarks are in. Training models to manage their own context sets a new frontier across browser control, computer use, and coding.
Better Call TIM: Filling out forms with an agent
Thread Inference Model (TIM) outperforms frontier browser agent.
The End of the Agent Dev Paradox
We want flexibility and rigidity, we want a do-it-all blackbox but with complete observability, and we want tools for fast prototyping and performance tuning all at the same time in the same agent.
Make Agent Frameworks Trainable
Agent frameworks cannot generalize. Something that can is inevitable.
Agents Without Training Wheels: The Model Agent
It's time to remove the training wheels from Agents. The model agents are here.
Introducing Subconscious: Build Flexible, Capable Agents
Backed by MIT research on a co-designed AI model and runtime, Subconscious is an inference engine for AI agents that allows for strong reasoning across external tool calls and virtually unlimited context.
