Context Engineering for Productive AI Agents with Filip Kozera - #741
2025-07-29 · 46 min · episode 741 · 16 entities
Asserted relationships
-
→ appeared on The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence podcast0.68
evidence rules-v4
Context Engineering for Productive AI Agents with Filip Kozera - #741
-
0.55
evidence rules-v4
Feed author/publisher: Sam Charrington
-
0.50
evidence rules-v4
CEO of Wordware
-
0.50
evidence rules-v4
CEO of Wordware
-
0.40
evidence rules-v4
Feed category: Science
-
0.40
evidence rules-v4
Feed category: Technology
-
0.40
evidence rules-v4
Feed category: News
-
0.40
evidence rules-v4
Feed category: Tech News
-
0.40
evidence rules-v4
Feed author/publisher: TWIML
Entities found in this episode
companys 7
-
0.70
evidence rules-v4
Feed author/publisher: TWIML
-
0.62
evidence rules-v4
CEO of Wordware
-
0.50
evidence rules-v4
Feed category: Technology
-
0.50
evidence rules-v4
CEO of Wordware
-
0.50
evidence rules-v4
CEO of Wordware
-
0.40
evidence rules-v4
Feed category: Technology
-
0.40
evidence rules-v4
Feed author/publisher: TWIML
concepts 5
-
0.50
evidence rules-v4
Feed category: Science
-
0.50
evidence rules-v4
Feed category: Tech News
-
0.40
evidence rules-v4
Feed category: Science
-
0.40
evidence rules-v4
Feed category: News
-
0.40
evidence rules-v4
Feed category: Tech News
persons 3
-
0.72
evidence rules-v4
Context Engineering for Productive AI Agents with Filip Kozera - #741
-
0.70
evidence rules-v4
Feed author/publisher: Sam Charrington
-
0.55
evidence rules-v4
Feed author/publisher: Sam Charrington
podcasts 1
-
appeared on The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence podcast0.68
evidence rules-v4
Context Engineering for Productive AI Agents with Filip Kozera - #741
Episode description as stored
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.