Context Engineering w systemach wieloagentowych | LIVE AI_devs 4
overment
Feb 18, 2026
Effective AI agents fail when they lose the thread of complex tasks, not because the underlying LLM is unintelligent. Engineers must shift from 'Prompt Engineering'—designing static instructions—to 'Context Engineering,' which involves architecturally managing what information stays in the agent's active memory to ensure reliability and cost-efficiency.
Key insight: Modern AI agents struggle significantly when their context window exceeds 40-60% capacity; sophisticated systems now use multi-layered 'observer' and 'reflector' agents to compress and archive past interactions, allowing agents to maintain high performance far beyond their native context window limits.
