
Manus Wide Research: What Happens When 100 Agents Read for You at Once?
Last Updated on August 29, 2025 by Editorial Team
Author(s): R. Thompson (PhD)
Originally published on Towards AI.
Inside the mechanics, guardrails, and surprising edge cases of parallel research
If youβve ever tried to compare 120 products, scan 300 funding calls, or pull signals across 1,000 web pages, you know the bottleneck. One agent going deep is great for a single report, but volume kills the calendar. Wide work is messy. It needs many eyes at once, the way a newsroom or a trading floor hums when the clock is loud. Wide Research is Manusβs attempt to capture that rhythm of human collaboration and replicate it at machine scale.
Wide Research is a new model developed by Manus that utilizes multiple agents working in parallel to tackle large research tasks efficiently. Emphasizing the importance of thoroughness without compromise, it seeks to deliver well-structured outputs across various domains, while simultaneously learning from each run to improve future results. The article discusses the functionality, advantages, and practical applications of this new system, highlighting its impact on industries ranging from finance to design and showcasing its capability to enhance decision-making processes. Ultimately, it proposes adopting a broad approach to research initially, followed by a deeper dive into crucial aspects for better clarity and effectiveness.
Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming aΒ sponsor.
Published via Towards AI