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The evolving role of DevProd teams in the AI era

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Manage episode 508558544 series 3338504
Content provided by Brook Perry. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Brook Perry 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.

CEO Abi Noda is joined by DX CTO Laura Tacho to discuss the evolving role of Platform and DevProd teams in the AI era. Together, they unpack how AI is reshaping platform responsibilities, from evaluation and rollout to measurement, tool standardization, and guardrails. They explore why fundamentals like documentation and feedback loops matter more than ever for both developers and AI agents. They also share insights on reducing tool sprawl, hardening systems for higher throughput, and leveraging AI to tackle tech debt, modernize legacy code, and improve workflows across the SDLC.

Where to find Abi Noda:

• LinkedIn: https://www.linkedin.com/in/abinoda

• Substack: ​​https://substack.com/@abinoda

Where to find Laura Tacho:

• LinkedIn: https://www.linkedin.com/in/lauratacho/

• X: https://x.com/rhein_wein

• Website: https://lauratacho.com/

• Laura’s course (Measuring Engineering Performance and AI Impact) https://lauratacho.com/developer-productivity-metrics-course

In this episode, we cover:

(00:00) Intro: Why platform teams need to evolve

(02:34) The challenge of defining platform teams and how AI is changing expectations

(04:44) Why evaluating and rolling out AI tools is becoming a core platform responsibility

(07:14) Why platform teams need solid measurement frameworks to evaluate AI tools

(08:56) Why platform leaders should champion education and advocacy on measurement

(11:20) How AI code stresses pipelines and why platform teams must harden systems

(12:24) Why platform teams must go beyond training to standardize tools and create workflows

(14:31) How platform teams control tool sprawl

(16:22) Why platform teams need strong guardrails and safety checks

(18:41) The importance of standardizing tools and knowledge

(19:44) The opportunity for platform teams to apply AI at scale across the organization

(23:40) Quick recap of the key points so far

(24:33) How AI helps modernize legacy code and handle migrations

(25:45) Why focusing on fundamentals benefits both developers and AI agents

(27:42) Identifying SDLC bottlenecks beyond AI code generation

(30:08) Techniques for optimizing legacy code bases

(32:47) How AI helps tackle tech debt and large-scale code migrations

(35:40) Tools across the SDLC

Referenced:

  continue reading

87 episodes

Artwork
iconShare
 
Manage episode 508558544 series 3338504
Content provided by Brook Perry. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Brook Perry 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.

CEO Abi Noda is joined by DX CTO Laura Tacho to discuss the evolving role of Platform and DevProd teams in the AI era. Together, they unpack how AI is reshaping platform responsibilities, from evaluation and rollout to measurement, tool standardization, and guardrails. They explore why fundamentals like documentation and feedback loops matter more than ever for both developers and AI agents. They also share insights on reducing tool sprawl, hardening systems for higher throughput, and leveraging AI to tackle tech debt, modernize legacy code, and improve workflows across the SDLC.

Where to find Abi Noda:

• LinkedIn: https://www.linkedin.com/in/abinoda

• Substack: ​​https://substack.com/@abinoda

Where to find Laura Tacho:

• LinkedIn: https://www.linkedin.com/in/lauratacho/

• X: https://x.com/rhein_wein

• Website: https://lauratacho.com/

• Laura’s course (Measuring Engineering Performance and AI Impact) https://lauratacho.com/developer-productivity-metrics-course

In this episode, we cover:

(00:00) Intro: Why platform teams need to evolve

(02:34) The challenge of defining platform teams and how AI is changing expectations

(04:44) Why evaluating and rolling out AI tools is becoming a core platform responsibility

(07:14) Why platform teams need solid measurement frameworks to evaluate AI tools

(08:56) Why platform leaders should champion education and advocacy on measurement

(11:20) How AI code stresses pipelines and why platform teams must harden systems

(12:24) Why platform teams must go beyond training to standardize tools and create workflows

(14:31) How platform teams control tool sprawl

(16:22) Why platform teams need strong guardrails and safety checks

(18:41) The importance of standardizing tools and knowledge

(19:44) The opportunity for platform teams to apply AI at scale across the organization

(23:40) Quick recap of the key points so far

(24:33) How AI helps modernize legacy code and handle migrations

(25:45) Why focusing on fundamentals benefits both developers and AI agents

(27:42) Identifying SDLC bottlenecks beyond AI code generation

(30:08) Techniques for optimizing legacy code bases

(32:47) How AI helps tackle tech debt and large-scale code migrations

(35:40) Tools across the SDLC

Referenced:

  continue reading

87 episodes

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