Search a title or topic

Over 20 million podcasts, powered by 

Player FM logo
Artwork

Content provided by TWIML and Sam Charrington. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by TWIML and Sam Charrington or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Player FM - Podcast App
Go offline with the Player FM app!

Context Engineering for Productive AI Agents with Filip Kozera - #741

46:01
 
Share
 

Manage episode 497256248 series 2355587
Content provided by TWIML and Sam Charrington. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by TWIML and Sam Charrington or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this episode, Filip Kozera, founder and CEO of Wordware, explains his approach to building agentic workflows where natural language serves as the new programming interface. Filip breaks down the architecture of these "background agents," explaining how they use a reflection loop and tool-calling to execute complex tasks. He discusses the current limitations of agent protocols like MCPs and how developers can extend them to handle the required context and authority. The conversation challenges the idea that more powerful models lead to more autonomous agents, arguing instead for "graceful recovery" systems that proactively bring humans into the loop when the agent "knows what it doesn't know." We also get into the "application layer" fight, exploring how SaaS platforms are creating data silos and what this means for the future of interoperable AI agents. Filip also shares his vision for the "word artisan"—the non-technical user who can now build and manage a fleet of AI agents, fundamentally changing the nature of knowledge work.

The complete show notes for this episode can be found at https://twimlai.com/go/741.

  continue reading

761 episodes

Artwork
iconShare
 
Manage episode 497256248 series 2355587
Content provided by TWIML and Sam Charrington. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by TWIML and Sam Charrington or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this episode, Filip Kozera, founder and CEO of Wordware, explains his approach to building agentic workflows where natural language serves as the new programming interface. Filip breaks down the architecture of these "background agents," explaining how they use a reflection loop and tool-calling to execute complex tasks. He discusses the current limitations of agent protocols like MCPs and how developers can extend them to handle the required context and authority. The conversation challenges the idea that more powerful models lead to more autonomous agents, arguing instead for "graceful recovery" systems that proactively bring humans into the loop when the agent "knows what it doesn't know." We also get into the "application layer" fight, exploring how SaaS platforms are creating data silos and what this means for the future of interoperable AI agents. Filip also shares his vision for the "word artisan"—the non-technical user who can now build and manage a fleet of AI agents, fundamentally changing the nature of knowledge work.

The complete show notes for this episode can be found at https://twimlai.com/go/741.

  continue reading

761 episodes

All episodes

×
 
Loading …

Welcome to Player FM!

Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.

 

Copyright 2025 | Privacy Policy | Terms of Service | | Copyright
Listen to this show while you explore
Play