The ever-so careful Anthropic ! Meticulously daling with the fundamentals the complete exact opposite of OpenAI (Oh wait they are ex-OpenAI emplyess by the way .. right ?)
Anthropic’s new Research feature adopts a multi-agent architecture where a lead Claude model orchestrates specialized subagents that search the web and other tools in parallel, enabling dynamic, breadth-first investigations that outperform single-agent approaches. Achieving dependable performance required careful prompt engineering—teaching agents how to delegate, scale effort, choose tools, and think aloud—as well as bespoke evaluation methods that combine LLM-as-judge metrics with human review. While the system delivers significant accuracy and speed gains, it also introduces engineering and economic challenges such as heavy token consumption, stateful error handling, and complex deployment, all of which demand rigorous observability, iterative testing, and robust production safeguards.
#claude #anthropic #research #multiagent #airesearch #webresearch #perplexity #searchgpt #tavily #aiagents #promptengineering #llmasajudge #aiorchestration #parallelprocessing #breadthfirst #tokenoptimization #aiobservability #productionai #aitools #aievaluation
https://www.anthropic.com/engineering/built-multi-agent-research-system
Anthropic’s new Research feature adopts a multi-agent architecture where a lead Claude model orchestrates specialized subagents that search the web and other tools in parallel, enabling dynamic, breadth-first investigations that outperform single-agent approaches. Achieving dependable performance required careful prompt engineering—teaching agents how to delegate, scale effort, choose tools, and think aloud—as well as bespoke evaluation methods that combine LLM-as-judge metrics with human review. While the system delivers significant accuracy and speed gains, it also introduces engineering and economic challenges such as heavy token consumption, stateful error handling, and complex deployment, all of which demand rigorous observability, iterative testing, and robust production safeguards.
#claude #anthropic #research #multiagent #airesearch #webresearch #perplexity #searchgpt #tavily #aiagents #promptengineering #llmasajudge #aiorchestration #parallelprocessing #breadthfirst #tokenoptimization #aiobservability #productionai #aitools #aievaluation
https://www.anthropic.com/engineering/built-multi-agent-research-system
The ever-so careful Anthropic ! Meticulously daling with the fundamentals the complete exact opposite of OpenAI (Oh wait they are ex-OpenAI emplyess by the way .. right ?)
Anthropic’s new Research feature adopts a multi-agent architecture where a lead Claude model orchestrates specialized subagents that search the web and other tools in parallel, enabling dynamic, breadth-first investigations that outperform single-agent approaches. Achieving dependable performance required careful prompt engineering—teaching agents how to delegate, scale effort, choose tools, and think aloud—as well as bespoke evaluation methods that combine LLM-as-judge metrics with human review. While the system delivers significant accuracy and speed gains, it also introduces engineering and economic challenges such as heavy token consumption, stateful error handling, and complex deployment, all of which demand rigorous observability, iterative testing, and robust production safeguards.
#claude #anthropic #research #multiagent #airesearch #webresearch #perplexity #searchgpt #tavily #aiagents #promptengineering #llmasajudge #aiorchestration #parallelprocessing #breadthfirst #tokenoptimization #aiobservability #productionai #aitools #aievaluation
https://www.anthropic.com/engineering/built-multi-agent-research-system
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