Unverified50% confidenceSolutionExact time
In multi-turn tool-calling agentic scenarios, system prompts occupying thousands of tokens compress the space available for intermediate reasoning steps and tool return results, and hitting the token limit causes task failure.
1
Sources
50%
Confidence
Long-term
Relevance
10/2/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedA single execution-type agent exhibits three typical problems during long-running tasks: goal drift, shortcut-taking, and mid-task cessation80% similarUnverifiedThe sub-agent pattern breaks complex tasks into multiple independent subtasks, where each sub-agent has an isolated context and returns results to the orchestrator upon completion.79% similarUnverifiedCommand-line-centric agents suffer from interaction friction such as opaque task progress, difficulty intervening in intermediate steps, and context management that relies on manual input.79% similarUnverifiedBecause agents can proactively combine multi-step operations, the damage caused by a successful prompt injection is far greater than that of a static program vulnerability.78% similarUnverifiedThe intelligent agent system adopts a closed-loop architecture of perception–planning–execution, decomposing complex tasks into sub-task sequences through reasoning frameworks such as ReAct and Chain-of-Thought.78% similar
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