We’ve been using smolagents, which takes this approach, and are impressed.
Slight tangent, but as a long term user of OpenAI models, I was surprised at how well Claude Sonnet 3.7 through the desktop app handles multi-hop problem solving using tools (over MCP). As long as tool descriptions are good, it’s quite capable of chaining and “lateral thinking” without any customisation of the system or user prompts.
For those of you using Sonnet over API: is this behaviour similar there out of the box? If not, does simply pasting the recently exfiltrated[1] “agentic” prompt into the API system prompt get you (most of the way) there?
Not sure if I correctly understand your question. I was saying that Sonnet 3.7 in the desktop app is good out-of-the-box at orchestrating tools exposed as MCP servers and asking whether that behaviour is also present over the Anthropic API or, if not, whether copy-pasting the exfiltrated system prompt gets you there.
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We’ve been using smolagents, which takes this approach, and are impressed.
Slight tangent, but as a long term user of OpenAI models, I was surprised at how well Claude Sonnet 3.7 through the desktop app handles multi-hop problem solving using tools (over MCP). As long as tool descriptions are good, it’s quite capable of chaining and “lateral thinking” without any customisation of the system or user prompts.
For those of you using Sonnet over API: is this behaviour similar there out of the box? If not, does simply pasting the recently exfiltrated[1] “agentic” prompt into the API system prompt get you (most of the way) there?
[1] https://news.ycombinator.com/item?id=43909409
How does it compare to MCP servers?
Not sure if I correctly understand your question. I was saying that Sonnet 3.7 in the desktop app is good out-of-the-box at orchestrating tools exposed as MCP servers and asking whether that behaviour is also present over the Anthropic API or, if not, whether copy-pasting the exfiltrated system prompt gets you there.