In this episode of HackrlIfe I take as a critical look at Samsung's research on building "multimodal AI agents" using no-code platforms like Flowise.

While the paper sounds impressive with terms like "multimodal LLM-based Multi-Agent Systems," I dug into what these tools actually do versus the marketing hype.

What I Found It Really Is: API orchestration tools that connect existing AI services (OpenAI, Stable Diffusion, Luma AI) through visual drag-and-drop interfaces.

You're not building AI – you're chaining together existing APIs with better UX.

Where I Think It Actually Works:

• Routine content workflow automation (blog posts → social media variants)
• Customer research processing (audio transcription → analysis → reporting)
• Basic content generation pipelines
• Repetitive multimedia tasks that don't require complex business logic

The Real Value I See: Speed of implementation and iteration for non-technical teams. Instead of waiting weeks for developer resources, growth teams can prototype automation workflows in days.

• Not revolutionary AI development – just workflow automation with AI APIs
• Limited by underlying API capabilities – you can't create custom logic
• Costs scale with usage – multiple paid APIs add up quickly
• Quality still requires human oversight – automation ≠ autonomous operation

I believe tools like Flowise are useful for operational efficiency, not AI innovation. They're worth exploring if you have routine, rule-based content tasks that currently eat up team time. But I recommend approaching them as workflow automation tools, not magical AI solutions.

My advice: Start small, test one simple use case, measure time savings, then expand gradually if it proves valuable.

My main insight: The competitive advantage isn't in the AI capabilities – it's in reducing friction between having an automation idea and implementing it.

In this episode, I give growth professionals a realistic assessment of what these tools can actually do for their teams.