In the rapidly evolving landscape of artificial intelligence, we’re accustomed to AI assistants that seem to require a lot of effort. Constant hand-holding and a ton clarifying questions often make these tools more bothersome than helpful for a lot of more complex jobs. But what if AI could truly work for us, rather than the other way around? What if an AI could be an autonomous agent, understanding intricate requests and finding relevant information without much input from us?
Enter Manus AI, a game-changer in the world of digital assistants. Manus ushers in a new era of AI, one that operates with a high degree of independence and genuine understanding. It’s time we started expecting more from our AI tools.
Andd.. I recently got early access to it, let’s talk about it!
What Exactly is Agentic AI?
Before diving into Manus specifically, it’s worth understanding what sets agentic AI apart from conventional AI assistants. True AI agents should:
- Work independently without constant user guidance
- Plan and execute multi-step processes
- Access and integrate information from various sources
- Make reasonable decisions when faced with ambiguity
- Deliver complete solutions, not just partial answers
Most AI tools available today fail at one or more of these criteria (even Manus, somewhat.) They might provide information but require you to synthesize it, or they might need constant clarification and guidance.
Hands-On with Manus AI: A New Kind of Digital Assistant
Recently, I gained access to Manus AI and decided to test just how “agentic” it really is. Rather than starting with a simple request, I threw a complex, multi-faceted challenge at it:
“I need a 7-day Singapore (4 nights) Malaysia (3 nights) itinerary for June (we have flexibility) from New Delhi, India, for 3 adults and 1 kid. There isn’t a set budget but we don’t want to overspend. We love fun activities, good food, and good views without it being too tiring. We’re planning on getting an Airbnb because hotels would be too expensive. Please provide a detailed itinerary, proposed budgets, things to do, any events during the time, places to stay at, weather and everything else you can get hands on and a simple HTML with everything we’ve talked about we can reference throughout our journey.”
This request contains multiple constraints, preferences, and deliverables—exactly the kind of complex task that typically requires human expertise or, at minimum, several back-and-forth exchanges with an AI.
What Manus Actually Delivered
What happened next demonstrated why Manus represents a new generation of AI agent. Without any follow-up questions or clarifications, it produced:
- A complete day-by-day itinerary spanning two countries
- Budget estimates broken down by category (accommodation, food, activities, transportation)
- Location-specific recommendations considering the presence of a child
- Transportation logistics between countries
- Weather forecasts and seasonal considerations
- Neighborhood recommendations for Airbnb stays with price estimates
- Cultural and safety tips relevant to the destinations
- A complete, formatted HTML document for offline reference
(You can check out the website it generated here: https://kuberwastaken.github.io/Singapore-Plan/)
All of this was delivered in a single package with zero additional input from me. This level of autonomous execution is what separates true AI agents from simple AI assistants.
As @MattMickiewicz from Twitter said themselves too: “Manus AI lives up to the hype. It’s a genius at planning complex, multi-country, multi-stop itineraries including nailing down the optimal routing.”
and yeah! I totally agree!
Beyond Travel: Manus AI as a General-Purpose Agent
While my travel planning experience provides a concrete example of Manus’s capabilities, what’s particularly impressive is its versatility across domains. According to the company and user reports, Manus can autonomously handle tasks including:
- Data Analysis: Creating detailed stock performance dashboards with visualizations
- Education: Developing curriculum materials, interactive lessons, and study resources
- Financial Planning: Comparing complex insurance policies and investment options
- Web Development: Building functional web applications and interactive tools
- Content Creation: Producing comprehensive guides, presentations, and multimedia content
- Research: Gathering and synthesizing information from diverse sources
This versatility suggests we’re looking at a general-purpose AI agent rather than a domain-specific tool, representing a significant advancement in practical AI application.
The Technology Behind Manus AI’s Autonomy
Manus AI, developed by China-based company Butterfly Effect, has been in development for a bit over one year. The name “Manus” comes from the Latin word for “hand,” symbolizing its role in bridging idea generation and execution.
Manus achieved state-of-the-art performance on the GAIA benchmark, which evaluates AI agents on their ability to perform real-world tasks. This benchmark tests an AI’s capacity to plan, reason, and execute multi-step processes which are precisely the skills required for genuine autonomy.
What makes Manus particularly interesting is its transparency. Several users on X have highlighted that Manus shows its “work” behind the scenes, giving insight into how it makes decisions and gathers information.
For tasks like travel planning, Manus pulls data from sources like Tripadvisor and specialized travel sites, integrating this information into coherent outputs. This ability to independently access and synthesize information from multiple sources is a hallmark of truly agentic AI.
The Credit System: How Manus Quantifies Computational Work
Manus operates on a credit system that reflects the computational resources required for different tasks. Each request consumes credits based on complexity, duration, and resource utilization (including LLM tokens, virtual machines, and third-party API calls).
For example:
- My travel itinerary consumed over 570 credits
- An NBA player scoring efficiency chart: 200 credits (15 minutes)
- A wedding invitation webpage: 360 credits (25 minutes)
- A daily sky events app: 900 credits (80 minutes)
The current pricing structure starts at $39/month for 3,900 credits on the Starter plan. This credit system provides insight into how AI agent workloads are quantified, something we’ll likely see more of as AI agents become more sophisticated and resource-intensive (but which is also awfully expensive now, but hopefully not later like most other AI applications: check out AI Models Race to the Bottom if you want to learn more! )
The Frontier of Agentic AI: Comparing Manus to Other Systems
To understand Manus’s position in the emerging field of agentic AI, it’s helpful to compare it with other approaches:
Traditional AI Assistants (ChatGPT, Claude)
- Interaction model: Conversational, requiring multiple exchanges
- Information access: Limited to training data, may use plugins/tools
- Execution ability: Primarily informational, limited action capabilities
- Output quality: Variable, depends heavily on prompt quality
Task-Specific AI Tools (Wonderplan, Trip Planner AI)
- Interaction model: Guided interfaces with predefined options
- Information access: Domain-specific databases
- Execution ability: Limited to specific functions
- Output quality: Good within narrow parameters
Manus AI (New Generation Agent)
- Interaction model: One comprehensive request yields complete solution
- Information access: Multiple sources integrated autonomously
- Execution ability: Complex, multi-step planning and content creation
- Output quality: High, with minimal user guidance
AutoGPT and Similar Frameworks
- Interaction model: Set goal and watch execution
- Information access: Web and tool-based
- Execution ability: Multiple steps but often requires oversight
- Output quality: Variable, sometimes gets stuck in loops
Honestly, Manus is one of the best we have for “Agentic AI” and it actually does show
The Implications: What Truly Autonomous AI Means
The emergence of genuinely agentic AI like Manus has far-reaching implications:
1. Expertise Democratization
Tools like Manus democratize access to expertise. Not everyone can afford specialized consultants or has the time to become an expert in every domain, but agentic AI can provide specialized knowledge on demand. My travel planning experience demonstrated this—I received expert-level planning without needing to consult a travel agent or spend weeks researching.
2. Time Value Revolution
The real value proposition of agentic AI isn’t just convenience—it’s the reclamation of time. Complex tasks that might take hours or days of human effort can be compressed into minutes. This fundamentally changes the equation of what’s worth outsourcing versus doing yourself.
3. New Interaction Paradigms
As AI becomes truly agentic, our interaction patterns will shift from conversational exchanges to outcome-focused requests. Instead of breaking down tasks into small, manageable chunks for AI, we can present complex, holistic requests and expect complete solutions.
4. Skill Augmentation vs. Replacement
Agentic AI like Manus doesn’t simply replace human skills—it augments them by handling routine aspects of complex tasks while allowing humans to focus on higher-level decisions and creativity. The AI handles the “how” while humans focus on the “what” and “why.”
Room for Improvement in the Agentic AI Space
While Manus represents a significant advancement, there are several areas where agentic AI still needs to evolve:
1. Action Execution
Currently, Manus excels at planning and content creation but stops short of executing actions like making bookings or purchases. As Mario Gavira from Kiwi.com noted, it doesn’t yet navigate booking sites or complete transactions. True end-to-end agency would include these capabilities.
2. Real-Time Data Integration
While Manus accesses various information sources, integrating real-time data (like current prices, availability, or live conditions) would further enhance its utility.
3. Customization and Learning
Truly personalized agentic AI would learn from past interactions and user preferences, becoming increasingly tailored to individual needs over time.
4. Resource Optimization
At 570+ credits for a travel itinerary, there’s room for more efficient processing. As AI technology advances, we should expect higher efficiency from agentic systems.
5. Error Handling and Recovery
The ability to recognize when something isn’t working, adjust course, and recover from errors is essential for fully autonomous systems.
The Future Landscape of Autonomous AI Agents
As companies like OpenAI, Anthropic, and Google develop their own agentic systems, we’re entering a new phase of AI utility. The race is on to create AI that can truly act as an independent agent rather than just a responsive assistant.
Recent developments like:
- OpenAI’s potential “Agent Store”
- Google’s work on AI agents that can use tools
- Anthropic’s research into constitutional AI for safer autonomy
All point to a future where agentic AI becomes commonplace. Manus represents an early but impressive entry in this new category.
The Conclusion
Manus AI offers a glimpse into the future of human-AI interaction—one where we can delegate complex, multi-step tasks with natural language instructions and receive complete solutions. It represents a shift from AI as a tool we must actively wield to AI as an agent that works independently on our behalf.
While still in early preview and with room for improvement, Manus demonstrates what’s possible when AI moves beyond conversation toward genuine agency. For professionals, creatives, and anyone who values their time, this evolution represents perhaps the most significant advancement in practical AI application since the introduction of large language models.
The question is no longer whether AI can be truly agentic, but how quickly these capabilities will become the new standard for AI assistance… that, we’ll find out with time :)