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EP 524: Agentic AI Done Right - How to avoid missing out or messing up.

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Manage episode 482532025 series 3470198
Content provided by Everyday AI. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Everyday AI 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://ppacc.player.fm/legal.

Agentic AI is equally as daunting as it is dynamic. So…… how do you not screw it up?
After all, the more robust and complex agentic AI becomes, the more room there is for error.
Luckily, we’ve got Dr. Maryam Ashoori to guide our agentic ways.
Maryam is the Senior Director of Product Management of watsonx at IBM. She joined us at IBM Think 2025 to break down agentic AI done right.
Newsletter: Sign up for our free daily newsletter
More on this Episode: Episode Page
Join the discussion: Have a question? Join the convo here.
Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: [email protected]
Connect with Jordan on LinkedIn
Topics Covered in This Episode:

  1. Agentic AI Benefits for Enterprises
  2. Watson X's New Features & Announcements
  3. AI-Powered Enterprise Solutions at IBM
  4. Responsible Implementation of Agentic AI
  5. LLMs in Enterprise Cost Optimization
  6. Deployment and Scalability Enhancements
  7. AI's Impact on Developer Productivity
  8. Problem-Solving with Agentic AI

Timestamps:
00:00 AI Agents: A Business Imperative

06:14 "Optimizing Enterprise Agent Strategy"

09:15 Enterprise Leaders' AI Mindset Shift

09:58 Focus on Problem-Solving with Technology

13:34 "Boost Business with LLMs"

16:48 "Understanding and Managing AI Risks"

Keywords:
Agentic AI, AI agents, Agent lifecycle, LLMs taking actions, WatsonX.ai, Product management, IBM Think conference, Business leaders, Enterprise productivity, WatsonX platform, Custom AI solutions, Environmental Intelligence Suite, Granite Code models, AI-powered code assistant, Customer challenges, Responsible AI implementation, Transparency and traceability, Observability, Optimization, Larger compute, Cost performance optimization, Chain of thought reasoning, Inference time scaling, Deployment service, Scalability of enterprise, Access control, Security requirements, Non-technical users, AI-assisted coding, Developer time-saving, Function calling, Tool calling, Enterprise data integration, Solving enterprise problems, Responsible implementation, Human in the loop, Automation, IBM savings, Risk assessment, Empowering workforce.

Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

  continue reading

525 episodes

Artwork
iconShare
 
Manage episode 482532025 series 3470198
Content provided by Everyday AI. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Everyday AI 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://ppacc.player.fm/legal.

Agentic AI is equally as daunting as it is dynamic. So…… how do you not screw it up?
After all, the more robust and complex agentic AI becomes, the more room there is for error.
Luckily, we’ve got Dr. Maryam Ashoori to guide our agentic ways.
Maryam is the Senior Director of Product Management of watsonx at IBM. She joined us at IBM Think 2025 to break down agentic AI done right.
Newsletter: Sign up for our free daily newsletter
More on this Episode: Episode Page
Join the discussion: Have a question? Join the convo here.
Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
Website: YourEverydayAI.com
Email The Show: [email protected]
Connect with Jordan on LinkedIn
Topics Covered in This Episode:

  1. Agentic AI Benefits for Enterprises
  2. Watson X's New Features & Announcements
  3. AI-Powered Enterprise Solutions at IBM
  4. Responsible Implementation of Agentic AI
  5. LLMs in Enterprise Cost Optimization
  6. Deployment and Scalability Enhancements
  7. AI's Impact on Developer Productivity
  8. Problem-Solving with Agentic AI

Timestamps:
00:00 AI Agents: A Business Imperative

06:14 "Optimizing Enterprise Agent Strategy"

09:15 Enterprise Leaders' AI Mindset Shift

09:58 Focus on Problem-Solving with Technology

13:34 "Boost Business with LLMs"

16:48 "Understanding and Managing AI Risks"

Keywords:
Agentic AI, AI agents, Agent lifecycle, LLMs taking actions, WatsonX.ai, Product management, IBM Think conference, Business leaders, Enterprise productivity, WatsonX platform, Custom AI solutions, Environmental Intelligence Suite, Granite Code models, AI-powered code assistant, Customer challenges, Responsible AI implementation, Transparency and traceability, Observability, Optimization, Larger compute, Cost performance optimization, Chain of thought reasoning, Inference time scaling, Deployment service, Scalability of enterprise, Access control, Security requirements, Non-technical users, AI-assisted coding, Developer time-saving, Function calling, Tool calling, Enterprise data integration, Solving enterprise problems, Responsible implementation, Human in the loop, Automation, IBM savings, Risk assessment, Empowering workforce.

Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

  continue reading

525 episodes

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