# Bridging intent and execution in agentic systems

DevFeed: [Bridging intent and execution in agentic systems](<https://devfeed.tech/articles/bridging-intent-and-execution-in-agentic-systems-7594.md>)

Original publisher: [Read original article](<https://www.amazon.science/blog/bridging-intent-and-execution-in-agentic-systems>)

Author: Gaurav Gupta; Vatshank Chaturvedi

Published: 2026-06-08T17:00:00Z

Content type: article

Language: en

Sources: [Amazon Science homepage](<https://devfeed.tech/sources/amazon-science-homepage.md>)

Topics: [Agent Harness](<https://devfeed.tech/topics/agent-harness.md>), [AI Agent](<https://devfeed.tech/topics/ai-agent.md>), [systems](<https://devfeed.tech/topics/systems.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Terminal](<https://devfeed.tech/topics/terminal.md>), [cloud-infrastructure](<https://devfeed.tech/topics/cloud-infrastructure.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Code](<https://devfeed.tech/topics/code.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [cloud-and-systems](<https://devfeed.tech/tags/cloud-and-systems.md>), [code](<https://devfeed.tech/tags/code.md>), [conversational-ai](<https://devfeed.tech/tags/conversational-ai.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [llm](<https://devfeed.tech/tags/llm.md>), [software](<https://devfeed.tech/tags/software.md>), [tools](<https://devfeed.tech/tags/tools.md>)

## AI overview

The article argues that performance in agentic systems is fundamentally a systems problem involving the interaction between a large language model and its harness. It defines the intent-execution gap between model intentions and harness actions, shows that reducing this gap can improve benchmark results without task-specific tuning, and emphasizes the effects of tools, execution graphs, infrastructure, timeouts, and resource constraints. It also introduces Simple Strands Agent (SSA), a lightweight customizable harness, and argues that model-harness codesign is important because model families differ in tool use and feedback interpretation.

## Source excerpt

The harnesses that mediate between models and tools in agentic systems are becoming their own performance bottleneck, but a few simple design principles can fix what ails them.