Choosing the best AI writing tool involves defining specific needs (speed, tone, editing, context) rather than chasing hype or irrelevant features. A pragmatic selection emphasizes iteration speed, revision controls, and context handling.
The author highlights a persistent issue in agentic workflows where AI agents have access to too many tools but lack judgment for selection. While the MCP standardized tool access, the distinct problem of intelligent tool selection for specific tasks remains unsolved, a gap ToolCairn was designed to fill.
An experienced AI agent builder in production criticizes engineers for overengineering solutions around LLMs, especially regarding tool selection. He advises trusting modern LLMs' inherent capability for this task by providing well-named and described tools, rather than building elaborate external systems.