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Codex from 0 to 10M Users: Building ChatGPT Work — Akshay Nathan, OpenAI

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Codex from 0 to 10M Users: Building ChatGPT Work — Akshay Nathan, OpenAI

Latent Space: The AI Engineer Podcast

1 DAYS AGO
Latent Space: The AI Engineer Podcast

Latent Space: The AI Engineer Podcast

1 DAYS AGO
OverviewShownoteHighlightsTranscriptChaptersPins

Shownote

There are roughly 100x more people who use code than who can write code. As code that “just works” becomes easier to generate, this group may be the biggest prize of all — if you can get the agentic interface right. A key trend we have been tracking over ...

Highlights

Akshay Nathan, who leads Core Product Engineering at OpenAI, discusses the launch of ChatGPT Work and the evolution of AI agents from coding tools to knowledge work platforms. He explains how the same agent harness that powers Codex now enables non-developers to accomplish complex tasks, from financial planning to performance reviews, and shares insights on product design, team dynamics, and measuring productivity in an AI-driven world.
00:03
Bringing the power of code to everyone through prompts.
01:33
The mission of building AGI has stayed consistent
02:40
No one-size-fits-all solution.
05:28
Non-developers using Codex with pride revealed its power beyond developers.
07:19
Codex and ChatGPT Work share the same underlying harness
12:08
AI blurs job roles
19:05
Slider simplifies model selection to speed vs. quality
22:38
Users act as intermediaries, querying the AI and relaying responses
29:30
Sites are replacing decks as canonical artifacts
30:10
New model capabilities reduce the need for manual input
34:33
Show not tell principle
38:23
AI should only gather context, not write reviews
40:41
The model's improved humor and ability to make surprising connections.
47:01
Natural language queries can replace traditional UX
50:26
Balancing power and abstraction in sub-agents
57:04
Chronicle learns from computer usage to build deeper memory.
1:02:30
Everyone becomes T-shaped generalists with AI
1:03:20
Valuable ideas come from user feedback and friction
1:07:09
Don't conflate motion with progress.

Chapters

Introduction and Bringing the Power of Code to Everyone
00:00
Joining OpenAI and Preserving a Startup Culture
01:33
What OpenAI Learned from Enterprise AI Adoption
02:40
Why OpenAI Built ChatGPT Work
05:28
Codex vs. ChatGPT Work and the Shared Agent Harness
07:17
Why OpenAI Merged Its Agent Experiences
12:07
Models, Reasoning Levels, and Choosing the Right Default
16:24
Artifacts, Agentic Spreadsheets, and Model–Product Collaboration
20:26
Why Sites Could Replace Decks and Spreadsheets
24:22
Designing an Agent That Can Build Almost Anything
30:08
From Developer Agents to Knowledge Work—and Everyone
34:28
Power-User Advice and AI-Assisted Performance Reviews
36:07
OpenAI’s Internal AI Memes and the Ten-Million-User Launch
40:41
OpenClaw, Personal Agents, and ChatGPT as an Operating System
44:39
Sub-Agents, Ultra Mode, and How Much Control Users Need
50:24
ChatGPT Memory, Personalization, and Chronicle
54:39
How AI Is Reshaping Product Development and Tech Roles
1:00:19
Ideas, Taste, and Why LLMs Struggle to Generate New Ideas
1:03:15
Measuring Productivity, Quality At-Bats, and Motion vs. Progress
1:04:42

Transcript

swyx: Okay, we're here in the studio with Akshay from OpenAI, Welcome, Thank you. And with our trustee co-host, Vibhu. So you recently launched ChatGPT Work. You lead core product engineering. It's been a long journey into all this. I find it very interest...