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The Next Breakthrough In AI Agents Is Here
@ Y Combinator
04/08/25
Takeaways
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04/08/25
@ Y Combinator
Usable AI agents are finally here, with platforms like OpenAI's Deep Research and Google's tools leading the way, and now Manus has joined the competition as a brand new general-purpose AI agent that has taken the world by storm.
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Y Combinator Cast
04/08/25
@ Y Combinator
Manus is being called the most impressive AI tool ever tried, showcasing its capabilities as a sophisticated computer using AI, unlike its predecessors that were merely specialized chatbots.
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@ Y Combinator
Manus operates as a multi-agent AI system, coordinating a team of sub-agents to complete various tasks, from travel planning to financial analysis, rather than relying on a single neural network.
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04/08/25
@ Y Combinator
Manus employs a planner agent that creates a master plan by breaking tasks into manageable subtasks, ensuring precise execution and efficient task management.
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@ Y Combinator
The executor agent in Manus combines outputs from completed subtasks into a final synthesized output for the user, showcasing its sophisticated dynamic task decomposition algorithm.
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@ Y Combinator
Manus utilizes a technique called chain of thought injection, allowing agents to actively reflect and update their plans, enhancing stability and reasoning capabilities during complex tasks.
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@ Y Combinator
Manus can accomplish a wide range of real-world tasks, excelling in creating travel itineraries, detailed financial analyses, and educational content, while also assisting with database compilation and high-quality presentations.
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@ Y Combinator
To measure Manus' capabilities, the Gaia benchmark tests AI agents on reasoning, multimodal handling, web browsing, and tool proficiency, with humans scoring about 92% and OpenAI's deep research scoring around 74%. Manus achieved an impressive benchmark score of 86.5% on the Gaia scoring system, just a few points shy of the average human performance.
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@ Y Combinator
Despite its strong performance, Manus has sparked a broader discussion about the nature of AI startups and the role of application layer wrappers.
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@ Y Combinator
Some critics dismiss Manus as merely a wrapper for existing foundational models and tools, but this perspective overlooks the reality that many successful AI products also fit this description.
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Successful AI products like Cursor and Windsurf integrate existing large language models with external APIs and developer-focused tools, demonstrating the viability of the wrapper model.
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Manus co-founder Yichchow Peak G emphasized that from the beginning, they aimed to work orthogonally to model development, seeking excitement rather than feeling threatened by new model releases.
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@ Y Combinator
What sets successful wrappers apart is their intuitive user interface, proprietary evaluations, careful fine-tuning of foundational models, and well-designed multi-agent architectures.
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@ Y Combinator
Manus exemplifies these trade-offs well, as its multi-agent orchestration significantly reduces per-task costs to around $2, compared to competitors like OpenAI's Deep Research.
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@ Y Combinator
Manus provides greater transparency and user control, allowing users to inspect, customize, or replace individual sub-agents and tool integrations, which centralized platforms often lack.
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One innovative feature of Manus is its ability to expose the file system, enabling users to see exactly what the agents are doing, unlike ChatGPT, which requires reprompting and lacks transparency.
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Manus offers a glimpse into the future of AI, potentially allowing users to run a desktop operating system directly on their computers, providing more control than browser-based solutions.
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However, Manus faces challenges with coordination among specialized agents as tasks scale in complexity, which can hinder its effectiveness.
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The advantages of Manus, such as UX refinements and thoughtful integrations, are vulnerable to competitors who can replicate these features, posing a risk to its market position.
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The key challenge for AI startups isn't whether wrappers are viable, but how to achieve sustainable differentiation in their products.
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@ Y Combinator
For founders, this may involve investing in proprietary evaluations that are costly or time-consuming to replicate, embedding workflows deeply into user routines, or forming integrations with unique platforms or datasets.
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04/08/25
@ Y Combinator
Ultimately, success in AI relies on the ability to effectively stitch together existing models into products that users genuinely love, rather than reinventing the wheel.