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AI and Software Development: What Engineers Need to Know with Mayank Jindal

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Manage episode 458331178 series 2922369
Content provided by Kashif Manzoor. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Kashif Manzoor 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.

Welcome to Open Tech Talks.

In this episode, we’re speaking with Mayank Jindal, a Software Development Engineer, about AI's evolving landscape and its impact on software engineering. From AI use cases to challenges in model development, we cover strategies for aligning AI solutions with business needs, tips for staying updated in this fast-paced field, and career advice for aspiring developers.

Whether new to AI or looking to refine your skills, this episode delivers insights you can apply immediately.

Large language models (LLMs) are transforming software engineering by automating code generation, debugging, and testing. They enable developers to accelerate workflows but require engineers to upskill and adapt. While AI reduces repetitive tasks, developers need to focus on designing architectures, validating outputs, and ensuring AI-generated code meets quality standards.

This episode has covered AI's evolving role, its impact on software engineering, and strategies for addressing challenges in AI development.

Episode # 153

Today’s Guest: Mayank Jindal, Software Development Engineer, Amazon

He is a Software Engineer passionate about leveraging Artificial Intelligence to enhance the digital world.

What Listeners Will Learn:

  • Understand how large language models (LLMs) influence software engineers' role and reshape development workflows.
  • Explore common challenges faced in AI development, including data quality, scalability, and performance optimization.
  • Discover strategies for keeping up with the rapid advancements in AI and machine learning technologies.
  • Gain practical tips for newcomers looking to start or grow their AI and software development careers.
  • Learn methods for translating business requirements into effective AI and machine learning models and tips for overcoming common obstacles.
  • Learn about real-world AI applications that are transforming industries and solving complex problems with AI
Resources:

  continue reading

158 episodes

Artwork
iconShare
 
Manage episode 458331178 series 2922369
Content provided by Kashif Manzoor. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Kashif Manzoor 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.

Welcome to Open Tech Talks.

In this episode, we’re speaking with Mayank Jindal, a Software Development Engineer, about AI's evolving landscape and its impact on software engineering. From AI use cases to challenges in model development, we cover strategies for aligning AI solutions with business needs, tips for staying updated in this fast-paced field, and career advice for aspiring developers.

Whether new to AI or looking to refine your skills, this episode delivers insights you can apply immediately.

Large language models (LLMs) are transforming software engineering by automating code generation, debugging, and testing. They enable developers to accelerate workflows but require engineers to upskill and adapt. While AI reduces repetitive tasks, developers need to focus on designing architectures, validating outputs, and ensuring AI-generated code meets quality standards.

This episode has covered AI's evolving role, its impact on software engineering, and strategies for addressing challenges in AI development.

Episode # 153

Today’s Guest: Mayank Jindal, Software Development Engineer, Amazon

He is a Software Engineer passionate about leveraging Artificial Intelligence to enhance the digital world.

What Listeners Will Learn:

  • Understand how large language models (LLMs) influence software engineers' role and reshape development workflows.
  • Explore common challenges faced in AI development, including data quality, scalability, and performance optimization.
  • Discover strategies for keeping up with the rapid advancements in AI and machine learning technologies.
  • Gain practical tips for newcomers looking to start or grow their AI and software development careers.
  • Learn methods for translating business requirements into effective AI and machine learning models and tips for overcoming common obstacles.
  • Learn about real-world AI applications that are transforming industries and solving complex problems with AI
Resources:

  continue reading

158 episodes

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