Build a team of AI agents that can collaborate with each other to solve a complicated task. ✅ Content repurposing, ✅ Market research, ✅ Literature review, you name it. Focus on what matters, let MindPal agents take care of the rest.
Hi Product Hunt,
Ever wonder how you can build AI workflows that involve multiple steps such as creating a high-quality and well-researched blog post, doing market research and analysis, writing a literature review, or crafting a business plan? With AI Assembly by MindPal, you can build such intricate workflows with ease!
🤔 But first, why AI Assembly?
After working with various AI models and integrating AI into our workflows, we have come to recognize a few limitations. Generative AI models like ChatGPT or Claude excel at producing results within a certain length, but struggle with long-form content such as writing research papers or performing complex analyses involving multiple tasks. Furthermore, these models are not well-suited for reasoning tasks, often producing generic results when forced to tackle a large task at once.
To overcome these limitations, we have adopted a best practice of breaking down tasks and having AI agents focus on one specific task at a time. This allows for customization and ensures the AI agent is best suited to solve that particular task.
However, up until now, our AI agents have only been able to work individually. There are instances where connecting multiple AI agents to collaborate on solving a larger task becomes necessary. Examples of such tasks include performing complicated research, writing comprehensive papers, or conducting complex reasoning for marketing campaigns or social media content pipelines.
That's when MindPal's AI Assembly feature comes into place.
✅ What is an AI Assembly?
AI assemblies are workflows that chain different AI agents together into an automated sequence. This sequence can be triggered with an input, and based on pre-configured steps, each step is carried out one by one to produce the final result. The chained agents can also pass input or data among each other, making the process collaborative and powerful.
❤️ Why we love the concept of AI Assembly
There are several reasons why we love the AI assembly feature on MindPal:
It is a natural development of our agent-first design. After optimizing our MindPal to view AI agents as the primary focus, allowing them to work together feels like a natural progression.
AI assemblies are intuitive. Just as you can think of an agent as an employee, an assembly can be seen as a team or a process commonly performed at work. By defining processes and tasks into specific steps, you can automate them with an AI assembly.
AI assembly unlocks numerous possibilities on MindPal, enabling AI agents to maximize their potential and abilities. It allows us to automate highly specialized or complicated tasks involving multiple steps, while still ensuring the quality you require.
With AI assembly, we can now help you automate a wide range of tasks, no matter how specialized or complex they may be. Take a look and explore the possibilities that AI assembly offers on MindPal.
@sylviangth The multi-agent assembly function is now step by step, would there be a flow process map-like visual format down the road for, orchestrating & prototyping a more complex agents' workflow?
Hi Sylvia,
I'm thoroughly impressed by the concept of AI Assembly by MindPal. Breaking down tasks for better AI performance is a smart move, and the ability to chain these agents together for complex workflows sounds incredibly powerful. I can already envision the benefits for content creators and researchers alike. Looking forward to seeing the creative ways people will use your platform. Great job on this innovative approach!
I love it ❣️ Imagine all of the insights to be had by chatting with your stuff. Even better, imagine what this could bring to the table in a business environment. Create bespoke agents, sync them together, and your good to go 🚀
I tested the assembly line yesterday and love it. I started with a simple idea of building an email course.
The assembly line had a
-research agent for the topic
-instructional design agent for the course -objectives and outline
-copywriter to write each of the emails.
Looking good so far!
Next I’m gonna try applying the six thinking hats to an idea 💡
Congrats on the launch of AI Assembly! The idea of stringing together different AI agents for complex tasks is intriguing. Can't wait to see how it streamlines workflows!
Hi team, I'm really intrigued by the concept of AI Assembly. How does the coordination between different AI agents work? Is there a central control system?
Hi Product Hunt Community,
I wanted to introduce you to a game-changing feature on MindPal called Assembly. As the creator of MindPal, I couldn't be more excited to share this with you.
Assembly is a powerful feature that allows you to create a multi-agent system, enabling you to tackle big tasks by seamlessly chaining together a team of agents.
Check it out and experience the potential of Assembly for yourself. It's time to take your productivity to new heights.
After having utilized Mindpals for several months, I must say that the idea it has provided for enhancing agents' workflow is truly mind-blowing. The responsive customer service they offer has been exceptional, and I strongly recommend grabbing this opportunity now to avoid any potential regrets in the future.
This sounds like a really interesting tool! I'm curious to know how Assembly by MindPal ensures effective collaboration between the AI agents. Do they have a specific communication protocol or a way to distribute tasks efficiently? Looking forward to learning more about it!
@moon10 Thanks for your interest and support, Moon! For now, you can define the data that is passed along to the workflow, whether it is from the original trigger input or from the output of other steps. We make sure that one step is run when and only when all the input specified is available. We are refining this feature every day to allow more complicated logic and collaboration among the agents.
MindPal