Why MultiAgentic Systems Struggle to Turn Data into Actions
What’s missing between data, agents and decisions
Why MultiAgentic Systems Struggle to Turn Data into Actions launched on January 17, 2026 with 16 votes, #777 of 14,584 launches that month and more than 90% of that year's launches.
In plain words
This is a Substack newsletter that examines the challenges multiagent AI systems face when attempting to convert data into actionable outcomes. Published in January 2026, it explores the practical limitations and technical difficulties that arise when multiple AI agents work together on data-driven tasks. The newsletter is aimed at readers interested in AI systems, their real-world applications, and the gaps between theoretical capabilities and actual performance.
written from the facts on this page · September 2026
From the sources
Funnelling AI Towards Enterprise Success Subscribe Sign in Part 2: Why MultiAgentic Systems Still Struggle to Turn Data into Actionable Insights What’s missing between data, agents and decisions Sruthi Poddutur Jan 16, 2026 4 Share Before You Continue If you haven’t read Part 1 , it is strongly recommend starting there first. Part 1 walks through a concrete failure mode in modern agentic systems: How GenAI pipelines that look correct, modular, and well-designed still fail to produce decisions because context collapses at every handoff . It shows why adding more agents, better prompts, or richer tools doesn’t fix the problem. It focuses on what changes when decision-making context is treated…from sruthipoddutur.substack.com
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