Summary
In this episode of AI at Work, Elijah and Kevin dive into the shifting terrain of automation and AI-powered agents. They highlight how traditional “if this, then that” workflows are giving way to dynamic systems driven by large language models, platforms like n8n enable you to describe what you want done, not just how. They share two real-world use cases, one clutter-clearing example (categorizing home-repair receipts) and one high-value business trigger (automated meeting-prep briefs). The conversation underlines the big leap: moving from rule-based automations to agent architectures that can decide, adapt, and act.
Takeaways
• Automation still matters, but the magic happens when an LLM steps into the workflow and makes decisions.
• Platforms like n8n now bridge no-code visual workflows with AI agentic functionality. n8n+1
• Start small: find one tedious, repetitive task you do and automate it today. Build confidence before scaling.
• Be aware of guardrails: data access, security, and scope still matter when your agent can act autonomously.
• The shift is real: business value lies not just in moving data, but in orchestrating flows where parts of the system think.
Chapters
00:00 Hectic mornings, Google Docs & teleoperated Sora robots
02:30 Playing with Sora & falling into the AI video rabbit hole
04:40 Bengal cat chaos & the dark side of AI gen videos
07:10 AI-native kids & shifting expectations about tech
09:30 Smart speakers, home automation hell & the orchestration gap
13:45 The Midwit meme & the $16 wired earbud breakthrough
17:20 Agents vs automations: what’s the actual difference?
24:30 Picking a platform, connectors, APIs & pricing models
45:20 Real-world agents: sales prep & everyday automations
01:01:45 Agentic browsers & letting AI work inside your apps
Show Notes & Links: https://www.spark6.com/podcast
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Check out Kevin’s stuff:
Ascend Labs: https://ascendlabs.ai/
Follow Kevin on LinkedIn: https://www.linkedin.com/in/kevinguywilliams/
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SPARK6 Agency: https://www.spark6.com/
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