Uploaded July 2026 | Updated September 2026, 2 weeks ago
What happens when engineering is no longer the bottleneck?
In this episode of Advanced Insights, AMD CTO and EVP Mark Papermaster sits down with Boris Cherny, creator and head of Claude Code at Anthropic, to explore how agentic AI is transforming software development and the broader engineering organization.
They discuss the rapid evolution from autocomplete to autonomous, multi-agent workflows; how engineers are becoming orchestrators of increasingly capable agents; and why curiosity, adaptability and the ability to generate strong ideas are becoming even more valuable. The conversation also examines the leadership and culture changes needed to unlock productivity, the importance of trust and verification, and the compute required to support agents that can operate for days or even weeks.
From “one-person armies” to AI-native organizations, learn how agentic workflows are reshaping the way products are imagined, built, tested and brought to market.
00:00 Introduction
00:34 Meet Boris Cherny
01:01 From Startups and Meta to Claude Code
02:16 Why Better Developer Tools Matter
03:10 Building Tools Around Anthropic’s Safety Mission
04:14 Why Non-Traditional Backgrounds Matter
05:09 From Code Assist to Agentic Software Development
06:01 How Claude Code Evolved
07:18 From Autocomplete to Entire Projects
08:07 Designing for a Purely Agentic Future
09:02 Rethinking Workflows Around Multiple Agents
09:50 From Deterministic Workflows to Model-Led Orchestration
10:36 Giving Agents Goals, Context and Tools
11:24 How Anthropic Uses Claude Every Day
12:35 Claude at the Center of the Engineering Lifecycle
13:16 Why AI Has to Sit at the Center of the Process
14:11 Anthropic’s 8x Increase in Code Output per Engineer
14:37 Removing Bottlenecks One at a Time
15:41 How the Role of Engineers Is Changing
16:20 Moving Up the Abstraction Stack
16:49 The Skills That Matter in an Agentic Era
17:14 When Engineering Is No Longer the Bottleneck
18:37 The Role of Leaders in Driving AI Adoption
19:27 From One Agent to Thousands of Agents
20:42 How Anthropic Engineers Work with Dozens of Agents
21:01 Sub-Agents and Nested Agent Workflows
21:26 Running Agents in the Cloud and from Mobile
21:51 Dynamic Workflows for Large-Scale Engineering Tasks
22:33 Culture Change and the Power of Multi-Agent Systems
23:27 Why Scaling Laws Still Matter
24:02 Test-Time Compute and Getting Better Results
24:48 Finding the Performance Roofline
24:59 Rethinking ROI for AI
25:37 Why Experimentation Drives the Biggest Returns
26:33 Democratizing Who Can Solve Hard Problems
27:42 Learning to Trust the Model
28:44 From Micromanaging AI to Setting Guardrails
29:09 Measuring and Choosing Between AI Approaches
29:51 Evals Versus “Vibes”
31:00 Trust, Verification and Governance
31:58 Building Safety and Reliability into the Model
32:39 Truthfulness, Alignment and Avoiding Sycophancy
33:20 Security and Prompt-Injection Resistance
34:26 Running Long-Lived Agents Safely
35:00 Why Anthropic Uses Automated Safety Classifiers
35:32 Scaling AI Systems and Products
36:28 How AMD Thinks About Scaling
36:40 Innovating Beyond Traditional Moore’s Law
37:26 Why Agentic Workflows Matter to Chip Design
37:58 The Role of Partnership in Scaling
38:32 What’s Coming Next for AI Agents
39:04 More Autonomy, Longer-Running Agents
39:37 From Features to Entire Products and Startups
40:08 Mark’s Key Takeaways
40:55 Closing and Where to Watch or Listen
***
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What happens when engineering is no longer the bottleneck?
In this episode of Advanced Insights, AMD CTO and EVP Mark Papermaster sits down with Boris Cherny, creator and head of Claude Code at Anthropic, to explore how agentic AI is transforming software development and the broader engineering organization.
They discuss the rapid evolution from autocomplete to autonomous, multi-agent workflows; how engineers are becoming orchestrators of increasingly capable agents; and why curiosity, adaptability and the ability to generate strong ideas are becoming even more valuable. The conversation also examines the leadership and culture changes needed to unlock productivity, the importance of trust and verification, and the compute required to support agents that can operate for days or even weeks.
From “one-person armies” to AI-native organizations, learn how agentic workflows are reshaping the way products are imagined, built, tested and brought to market.
00:00 Introduction
00:34 Meet Boris Cherny
01:01 From Startups and Meta to Claude Code
02:16 Why Better Developer Tools Matter
03:10 Building Tools Around Anthropic’s Safety Mission
04:14 Why Non-Traditional Backgrounds Matter
05:09 From Code Assist to Agentic Software Development
06:01 How Claude Code Evolved
07:18 From Autocomplete to Entire Projects
08:07 Designing for a Purely Agentic Future
09:02 Rethinking Workflows Around Multiple Agents
09:50 From Deterministic Workflows to Model-Led Orchestration
10:36 Giving Agents Goals, Context and Tools
11:24 How Anthropic Uses Claude Every Day
12:35 Claude at the Center of the Engineering Lifecycle
13:16 Why AI Has to Sit at the Center of the Process
14:11 Anthropic’s 8x Increase in Code Output per Engineer
14:37 Removing Bottlenecks One at a Time
15:41 How the Role of Engineers Is Changing
16:20 Moving Up the Abstraction Stack
16:49 The Skills That Matter in an Agentic Era
17:14 When Engineering Is No Longer the Bottleneck
18:37 The Role of Leaders in Driving AI Adoption
19:27 From One Agent to Thousands of Agents
20:42 How Anthropic Engineers Work with Dozens of Agents
21:01 Sub-Agents and Nested Agent Workflows
21:26 Running Agents in the Cloud and from Mobile
21:51 Dynamic Workflows for Large-Scale Engineering Tasks
22:33 Culture Change and the Power of Multi-Agent Systems
23:27 Why Scaling Laws Still Matter
24:02 Test-Time Compute and Getting Better Results
24:48 Finding the Performance Roofline
24:59 Rethinking ROI for AI
25:37 Why Experimentation Drives the Biggest Returns
26:33 Democratizing Who Can Solve Hard Problems
27:42 Learning to Trust the Model
28:44 From Micromanaging AI to Setting Guardrails
29:09 Measuring and Choosing Between AI Approaches
29:51 Evals Versus “Vibes”
31:00 Trust, Verification and Governance
31:58 Building Safety and Reliability into the Model
32:39 Truthfulness, Alignment and Avoiding Sycophancy
33:20 Security and Prompt-Injection Resistance
34:26 Running Long-Lived Agents Safely
35:00 Why Anthropic Uses Automated Safety Classifiers
35:32 Scaling AI Systems and Products
36:28 How AMD Thinks About Scaling
36:40 Innovating Beyond Traditional Moore’s Law
37:26 Why Agentic Workflows Matter to Chip Design
37:58 The Role of Partnership in Scaling
38:32 What’s Coming Next for AI Agents
39:04 More Autonomy, Longer-Running Agents
39:37 From Features to Entire Products and Startups
40:08 Mark’s Key Takeaways
40:55 Closing and Where to Watch or Listen
***
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©2026 Advanced Micro Devices, Inc. AMD, the AMD Arrow Logo, and combinations thereof are trademarks of Advanced Micro Devices, Inc. in the United States and other jurisdictions. Other names are for informational purposes only and may be trademarks of their respective owners.
