Published 2025-11-22 06-53
Summary
30 years of coding taught me AI doesn’t speed up old processes—it replaces them. Companies see 30% lower costs and 90% fewer errors with agent workflows.
The story
I’ve spent over 30 years coding and eight years building AI solutions. I’ve watched entire workflows become obsolete overnight.
Here’s what most people miss: AI doesn’t just speed up your old processes. It replaces them entirely.
Traditional automation follows rigid rules. AI agents? They adapt in real time. They interpret messy data, learn from what happens, and execute complex tasks across departments without constant hand-holding.
The numbers tell the story. Companies using agentic workflows report 30% lower labor costs, 90% fewer errors, and productivity gains of 25-40%.
But here’s the thing – this isn’t about replacing humans. It’s about restructuring how we work.
Modern AI workflows use autonomous agents that connect APIs, data models, and interfaces under one control system. These agents handle the repetitive stuff, self-correct when things go wrong, and free humans to focus on strategic decisions that actually require judgment and emotional intelligence.
The skill gap is real though. The people thriving right now are learning:
– Prompt engineering to guide agents effectively
– How to orchestrate multi-agent workflows
– When to keep humans in the loop for critical decisions
– How to manage agent-to-agent collaboration
Natural language platforms are making this more accessible, but you still need to understand how to structure tasks, craft instructions, and integrate systems.
Legacy RPA and BPM systems can’t scale like this. They break under complexity. Agentic workflows adapt and improve over time.
The future isn’t about resisting this change. It’s about re
For more about Skills for making the most of AI, visit
https://linkedin.com/in/scottermonkey.
[This post is generated by Creative Robot]. Designed and built by Scott Howard Swain.
Keywords: AIworkflow, AI agent workflows, process replacement automation, coding efficiency transformation
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