A: Hey there!

That's a great question, especially if you've seen what Manus can do with its more autonomous research capabilities.

Here's how AgenticFlow compares and what's possible:

1. AgenticFlow & Manus-Style Research:
Current Capabilities (Level 4 Agents & Workflows):
Research Task: You can absolutely give an AgenticFlow Agent (or a workflow) instructions to "go online, conduct research on [topic], and compile the information for me."

How it Works:

The agent/workflow would use tools like our Google Search node, Perplexity Search MCP (https://agenticflow.ai/mcp/perplexity_search), or a Web Scraping node / Firecrawl MCP (https://agenticflow.ai/mcp/firecrawl) to access online information.

It would then use LLM nodes to process, analyze, extract key points, and compile/summarize that information into the format you request.

We even have a pre-built agent called "Eri - The Deep Research Agent" (https://agenticflow.ai/app/explore/agent/56bcbd55-d408-4e1a-9641-61950d884800) that does exactly this type of deep research (it's best used with your own OpenAI key due to the intensity of calls).

Clarifying Questions (Current Method):

Right now, an AgenticFlow agent doesn't proactively ask a series of clarifying questions before starting a research task in the same deeply interactive, conversational way a human or a very advanced autonomous agent like Manus might.

You typically provide all necessary context and clarification in your initial prompt or through the structured inputs of a workflow.

If the initial information is insufficient, the agent might complete the task based on its interpretation, or it might indicate it needs more specifics in its output, requiring you to refine the prompt and re-run.

Future Capabilities (Path to More Manus-Like Behavior):

Multi-Agent System Add-On: Our upcoming MAS add-on (https://agenticflow.ai/mas-pre-order) is a step towards more complex task handling. A "Manager Agent" could potentially be designed to have an initial "clarification loop" with you or another agent before dispatching research sub-tasks.

More Autonomous Agents (Level 6 Vision): We do have a Proof of Concept for "Manus-level" autonomous agents that can perform more complex reasoning, plan multi-step actions, and potentially engage in more dynamic clarification dialogues. This is part of our longer-term vision. As I mentioned in a previous note, "We really love experimenting with different things from DeepResearch to a Manus prototype... eventually these shall be added as new building blocks in AF."

Key Difference from Manus (Currently):

Level of Autonomy in Clarification: Manus excels at that highly autonomous, interactive clarification before deep execution. AgenticFlow currently relies more on you providing clear initial instructions, with agents executing based on that. The "back-and-forth" for clarification is more of a human-in-the-loop refinement process with AgenticFlow at present.

Cost & Practicality: As you might know from Manus, that level of autonomy and deep reasoning can be very resource-intensive (both in terms of time and cost per task). AgenticFlow aims to provide powerful, practical, and cost-effective automation for a wider range of use cases today, with a clear path towards increasing autonomy.

In Short:
AgenticFlow can definitely conduct online research and compile information based on your instructions. It can be very effective. However, it doesn't currently have the same level of proactive, multi-turn clarifying dialogue before execution that a specialized autonomous research agent like Manus might demonstrate. That deeper conversational planning is more aligned with our Level 5/6 vision.

You can achieve very powerful research outcomes now, and we're building towards even greater agent autonomy!
— Sean