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Why humans are AI’s biggest bottleneck (and what’s coming in 2026) | Alexander Embiricos (OpenAI Codex Product Lead)

Overview

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Why humans are AI’s biggest bottleneck (and what’s coming in 2026) | Alexander Embiricos (OpenAI Codex Product Lead)

Lenny's Podcast: Product | Career | Growth

4 DAYS AGO
Lenny's Podcast: Product | Career | Growth

Lenny's Podcast: Product | Career | Growth

4 DAYS AGO
OverviewShownoteHighlightsTranscriptChaptersPins

Shownote

Alexander Embiricos leads product on Codex, OpenAI’s powerful coding agent, which has grown 20x since August and now serves trillions of tokens weekly. Before joining OpenAI, Alexander spent five years building a pair programming product for engineers. He ...

Highlights

AI is rapidly reshaping the landscape of software development, not by replacing engineers, but by evolving into an intelligent collaborator that augments human capability. At OpenAI, this transformation is being led by Codex, a coding agent designed to function less like a tool and more like a teammate embedded in the development workflow. Under Alexander Embiricos’ leadership, Codex is pushing the boundaries of how AI can participate in the full lifecycle of engineering work.
07:29
It's better to adopt a 'ready fire aim' approach as in many AI companies, getting products out early to see how people use them.
13:52
The average user prompts AI only tens of times a day but could benefit thousands of times.
20:20
Codex Max is 30% faster and smarter than previous versions
27:13
The best way for AI models to use a computer is by writing code.
42:32
The real bottleneck in AI-assisted development is validating code and reviewing PRs, not writing it.
44:08
Codex allows PMs to answer technical questions more easily and prototype quickly.
45:41
Designers can build working prototypes instantly with Codex and turn them into PRs
47:18
The Sora Android app was built in 18 days using Codex
49:02
One engineer 完成了一周内完成的任务，以前需要两到三名工程师花费数周时间
53:35
Vertical AI startups can solve particular customer problems better than general solutions
55:36
Reddit provides better user feedback signals than Twitter due to upvoting mechanics
1:00:24
An AI browser provides deeper context for agents to act appropriately without flooding users with notifications.
1:10:15
Codex evaluates chart movement over time for more efficient training and represents the future of AI agents.
1:13:03
The final validation of AI output is the key bottleneck
1:18:35
Tesla's self-driving software is a masterclass in mixed-initiative design.

Chapters

Introduction to Alexander Embiricos
00:00
The speed and ambition at OpenAI
05:13
Codex: OpenAI’s coding agent
11:34
Codex’s explosive growth
15:43
The future of AI and coding agents
24:59
The impact of AI on engineering
33:11
How Codex has impacted the way PMs operate
44:08
Throwaway code and ubiquitous coding
45:40
Shipping the Sora Android app
47:10
Building the Atlas browser
49:01
Codex’s impact on productivity
53:34
Measuring progress on Codex
55:35
Why they are building a web browser
58:09
Non-engineering use cases for Codex
1:01:58
Codex’s capabilities
1:02:53
Tips for getting started with Codex
1:04:49
Skills to lean into in the AI age
1:05:37
How far are we from a human version of AI?
1:10:36
Hiring and team growth at Codex
1:13:31
Lightning round and final thoughts
1:15:47

Transcript

Lenny Rachitsky: Do lead work on Codex. Alexander Embiricos: Codex is OpenAI's coding agent. We think of Codex as just the beginning of a software engineering teammate. It's a bit like this really smart intern that refuses to read Slack, doesn't check Dat...