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Hosts: Srini Annamaraju & David Royle.
Guest: Ravi Ramchandran.
Welcome to episode 8.
AI agents are getting easier to build. That’s the exciting bit. The risky bit is that organisations can now create weak, badly governed automations before leadership has worked out what “good” actually looks like.
In this episode, Ravi joins Srini and David to pull the conversation out of buzzword-land and into real work. He walks through a practical example of building an agent that turns meeting transcripts into status reports, then digs into what matters underneath: prompt discipline, guardrails, safe experimentation, risk metrics, and why handing people tools without changing operating practice is asking for trouble.
The conversation moves from macro AI noise to enterprise reality. How should leaders think about the 70-20-10 split of routine, experimental, and visionary work? Where does human friction still belong? And how do you encourage innovation without creating a quiet flood of low-quality AI output across the firm?
What we cover
Chapters
Top-5 Takeaways
Who it’s for
Enterprise Leaders in all functions inerested in AI adoption.
Help Spread the Word
Enjoyed the episode? Follow us!
Template Takeaways
Ravi has kindly shared these two templates he walked us through for general open access. Please feel free to download them from this Google Drive folder.
https://drive.google.com/drive/folders/1yKGryaEQ4lM8hLSf1il3jrqbZj4XgHrt?usp=sharing
By Srini and DavidHosts: Srini Annamaraju & David Royle.
Guest: Ravi Ramchandran.
Welcome to episode 8.
AI agents are getting easier to build. That’s the exciting bit. The risky bit is that organisations can now create weak, badly governed automations before leadership has worked out what “good” actually looks like.
In this episode, Ravi joins Srini and David to pull the conversation out of buzzword-land and into real work. He walks through a practical example of building an agent that turns meeting transcripts into status reports, then digs into what matters underneath: prompt discipline, guardrails, safe experimentation, risk metrics, and why handing people tools without changing operating practice is asking for trouble.
The conversation moves from macro AI noise to enterprise reality. How should leaders think about the 70-20-10 split of routine, experimental, and visionary work? Where does human friction still belong? And how do you encourage innovation without creating a quiet flood of low-quality AI output across the firm?
What we cover
Chapters
Top-5 Takeaways
Who it’s for
Enterprise Leaders in all functions inerested in AI adoption.
Help Spread the Word
Enjoyed the episode? Follow us!
Template Takeaways
Ravi has kindly shared these two templates he walked us through for general open access. Please feel free to download them from this Google Drive folder.
https://drive.google.com/drive/folders/1yKGryaEQ4lM8hLSf1il3jrqbZj4XgHrt?usp=sharing