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What Holds Devs Back From Multi-Agent Thinking | Guy Podjarny

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Manage episode 521307193 series 3585084
Content provided by Tessl. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Tessl 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.

LLMs don’t get smarter when you dump everything into context, they get distracted.
At AI-Native DevCon, Guy Podjarny unpacks the evolution of AI augmented development, and how devs can get the most from current tools.
On the docket:
• how to help agents close the capability-reliability gap
• why 'context engineering is basically the same as specs.'
• why statistical measurement is the only meaningful way to judge agent reliability.
• how ‘tiles’ level inconsistent documentation across old and new libraries.
AI Native Dev, powered by Tessl and our global dev community, is your go-to podcast for solutions in software development in the age of AI. Tune in as we engage with engineers, founders, and open-source innovators to talk all things AI, security, and development.
Connect with us here:
1. Guy Podjarny- https://www.linkedin.com/in/guypo/
2. Simon Maple- https://www.linkedin.com/in/simonmaple/
3. Tessl- https://www.linkedin.com/company/tesslio/
4. AI Native Dev- https://www.linkedin.com/showcase/ai-native-dev/
Join our AI Native Dev Community: https://discord.com/invite/jbb2vHnHZQ?utm_source=footer&utm_medium=tessl+website&utm_campaign=community

Join the AI Native Dev Community on Discord: https://tessl.co/4ghikjh
Ask us questions: [email protected]

  continue reading

Chapters

1. Trailer (00:00:00)

2. Introduction (00:01:07)

3. Keynote Speaker Introduction (00:02:05)

4. The Evolution of AI in Software Development (00:03:40)

5. Challenges and Solutions in AI Agent Reliability (00:04:44)

6. Context Engineering in Practice (00:11:52)

7. Conclusion: The Future of AI and Context Engineering (00:25:23)

83 episodes

Artwork
iconShare
 
Manage episode 521307193 series 3585084
Content provided by Tessl. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Tessl 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.

LLMs don’t get smarter when you dump everything into context, they get distracted.
At AI-Native DevCon, Guy Podjarny unpacks the evolution of AI augmented development, and how devs can get the most from current tools.
On the docket:
• how to help agents close the capability-reliability gap
• why 'context engineering is basically the same as specs.'
• why statistical measurement is the only meaningful way to judge agent reliability.
• how ‘tiles’ level inconsistent documentation across old and new libraries.
AI Native Dev, powered by Tessl and our global dev community, is your go-to podcast for solutions in software development in the age of AI. Tune in as we engage with engineers, founders, and open-source innovators to talk all things AI, security, and development.
Connect with us here:
1. Guy Podjarny- https://www.linkedin.com/in/guypo/
2. Simon Maple- https://www.linkedin.com/in/simonmaple/
3. Tessl- https://www.linkedin.com/company/tesslio/
4. AI Native Dev- https://www.linkedin.com/showcase/ai-native-dev/
Join our AI Native Dev Community: https://discord.com/invite/jbb2vHnHZQ?utm_source=footer&utm_medium=tessl+website&utm_campaign=community

Join the AI Native Dev Community on Discord: https://tessl.co/4ghikjh
Ask us questions: [email protected]

  continue reading

Chapters

1. Trailer (00:00:00)

2. Introduction (00:01:07)

3. Keynote Speaker Introduction (00:02:05)

4. The Evolution of AI in Software Development (00:03:40)

5. Challenges and Solutions in AI Agent Reliability (00:04:44)

6. Context Engineering in Practice (00:11:52)

7. Conclusion: The Future of AI and Context Engineering (00:25:23)

83 episodes

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