If you’ve been following the LLM space, you know that fine-tuning models with weight updates is expensive and slow. Enter Agentic Context Engineering, or ACE. Think of it as giving an AI an 'evolving playbook' rather than trying to rewire its brain.

Most AI systems suffer from 'context collapse'—where details get lost the more you talk to them. ACE fixes this by using a three-part team: a Generator, a Reflector, and a Curator. Instead of rewriting instructions from scratch, they incrementally update a modular set of insights. The result? We’re seeing massive accuracy boosts in financial reasoning and autonomous agents, all while keeping computational costs down.