"When I started integrating AI into my workflows, I was seduced by the promise of "one tool to rule them all." One login. One workflow. One platform that would manage research, writing, operations and communications - all in one neat package. In theory, it was elegant. But what I found, in the end, was a trap. What broke first were nonnegotiables: depth, nuance and reliability."
"What followed was a shift in mindset: I swapped "one-platform thinking" for "stack thinking." I started curating a bench of specialized tools - each assigned to a distinct job - and built workflows that were resilient, adaptable and far more effective in the real world. At first, using a single AI platform felt efficient. Everything was under one roof. No juggling accounts, no format drift. Just "AI, here I come." It was neat. It felt modern."
Relying on a single AI platform produced shallow research, homogenized writing, and brittle operational workflows. Depth, nuance, and reliability collapsed when one system was forced to handle deep research, outreach copy, and automation orchestration. Broad outputs obscured edge-case detail, made writing generic and unbranded, and required significant time debugging platform limits. Switching to a curated stack of specialized tools assigned to distinct tasks restored resilience, adaptability, and effectiveness. Specialized tools preserved research depth, supported branded writing, and produced stable operational automations. The stack approach prioritized tool fit for function over convenience of consolidation.
Read at InfoWorld
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