Model intelligence is no longer the constraint for automation
9 days ago
- #Context Engineering
- #AI Automation
- #Model Intelligence
- Model intelligence is no longer the main constraint for automation; the real bottlenecks are specifying intent and context engineering.
- Tasks require three components: problem specification, context, and a solver (model with tools).
- Mathematics is an 'easy target' for LLMs due to complete problem specifications, whereas real-world tasks are 'hard targets' with fuzzy specs and scattered context.
- Improving raw model intelligence has diminishing returns; better specs and context pipelines are crucial for automation.
- Short-term solutions include making context accessible, building intelligent memory systems, and expanding context windows.
- Long-term breakthroughs needed: capturing structured internal context, cheap/fine-tuning custom models, continuous learning, and model 'brain surgery.'
- Agents will excel in 'easy targets' like science but face challenges in corporate automation until spec and context systems mature.