Andrew Ambrosino28 June 2026

OpenAI Codex lead on the new shape of product work

6Frameworks

15Insights

Episode overview

Andrew Ambrosino explains how cheap AI-assisted implementation has inverted product development: building is abundant, while judgment, curation, coordination, and taste have become the scarce work. He describes OpenAI's heavily overlapping product, design, and engineering roles, while arguing that specialties and their accumulated best practices still matter. The conversation also traces Codex's evolution from a coding tool into a desktop work hub that can automate workflows and operate specialist software through connectors, browsers, computer use, and extensions.

Key ideas

AI makes implementation cheap, shifting product work toward choosing, curating, framing, and refining the right ideas.
Documents and prototypes remain useful, but teams must choose the medium that matches the question and clearly signal an artifact's maturity.
Product, design, and engineering increasingly overlap, yet eliminating disciplines entirely would discard valuable expertise and established best practices.
Strong contributors combine agency, disciplinary command, and taste, taking ideas from inception to a coherent finished outcome.
Long-range product plans should remain intentionally hazy because model progress can rapidly change which product ideas are viable.
Teams can build ambitious artifacts before models are capable enough, then retest them as intelligence improves rather than treating early failure as final.
Codex is dogfooded for coding, discovery, release coordination, Slack briefs, research, spreadsheets, browser work, and interaction with specialist desktop tools.
The envisioned desktop app is a home base for starting, tracking, automating, and completing work across both built-in experiences and external applications.

Transcript available · source text is retained privately and is not published

Frameworks in this episode

Innovation3 steps

Adversarial Dogfooding Loop

Force all your work through your own product even when it's the wrong tool, so it becomes the right tool

Read →

Innovation3 steps

Build-and-Bake: Ship the Same Feature Until the Model Catches Up

Prototype ambitious features now, let them sit, and re-release the same shape each time models leap

Read →

Strategy3 steps

Detune Precision by Time Horizon

The shorter the horizon, the more detail; keep long-range plans deliberately hazy to avoid false precision

Read →

Productivity3 steps

Label the Process Stage, Not the Polish

A production-looking prototype no longer means it's production-ready — say the stage out loud

Read →

Productivity3 steps

Match the Medium to the Point

When implementation is cheap, the skill is choosing document vs prototype for the point you're making

Read →

Leadership3 steps

Zone Defense for Product Work

Spread taste-makers out to cover the whole field instead of clustering on the same problem

Read →

People & resources mentioned

Attributed to the moment in the episode. Timestamps are approximate.

People · 7

Lenny RachitskyMentionstoday we've got another very special compilation episode something I've been pulling on more and more with the podcast and the newsletter
“today my guest is Andrew Ambercino, product and engineering lead for the Codex app at OpenAI.”
▶ Watch at ~1:15approx.
Andrew AmbrosinoMentionsproduct and engineering lead for the Codex app at OpenAI
“Andrew is a designer turned engineer turned product manager who is building the app that more and more of the world is using”
▶ Watch at ~2:00approx.
Paul GrahamMentionsPaul Graham talks about this too right just like live in the future and build it
“Paul Graham clearly has great taste and wears cargo shorts, right?”
▶ Watch at ~11:00approx.
JennyMentionshead of design for Claude Code and Cowork
“Jenny, who is the head of design for clock code and co-work and such”
▶ Watch at ~16:45approx.
Dan ShipperMentionsDan is the co-founder and CEO of Every which is a company that is at the very bleeding edge of what is possible with AI.
“Reminds me, I don't know if you watched uh when Dan Shipper was on the podcast”
▶ Watch at ~49:00approx.
BrentUsesOpenAI's in-house developer-experience videographer
“our in-house DX videographer Brent then was tasked with editing all these videos, right? And he edited all the videos with Codex”
▶ Watch at ~57:15approx.
Kate McKinnonMentionsmentioned
“Kate McKinnon plays the main Miss Frizzle.”
▶ Watch at ~1:04:00approx.

Resources · 47

CodexMentionssoftware · OpenAI
“Codeex is quickly becoming people's go-to app for building products and also for non-product work”
▶ Watch at ~1:30approx.
OpenAIMentionscompany
“Internally at OpenAI, nearly 100% of their employees use Codeex weekly.”
▶ Watch at ~1:45approx.
Lenny's NewsletterCoinednewsletter · Lenny Rachitsky
“available exclusively to Lenny's newsletter subscribers.”
▶ Watch at ~2:15approx.
OpenAIMentionscompany
“Everybody at OpenI, OpenAI is is very agentic, has great ideas, and so everybody's building everything.”
▶ Watch at ~3:30approx.
ClayMentionssoftware · Clay
“What do OpenAI, Anthropic, Cursor, Versell, Replet, Sierra, Clay, and hundreds of other winning companies all have in common?”
▶ Watch at ~5:15approx.
AnthropicMentionscompany
“What do OpenAI, Anthropic, Cursor, Versell, Replet, Sierra, Clay, and hundreds of other winning companies all have in common?”
▶ Watch at ~5:15approx.
ReplitMentionssoftware · Replit
“What do OpenAI, Anthropic, Cursor, Versell, Replet, Sierra, Clay, and hundreds of other winning companies all have in common?”
▶ Watch at ~5:15approx.
VercelMentionscompany · Guillermo Rauch
“What do OpenAI, Anthropic, Cursor, Versell, Replet, Sierra, Clay, and hundreds of other winning companies all have in common?”
▶ Watch at ~5:15approx.
CursorMentionssoftware · Anysphere
“What do OpenAI, Anthropic, Cursor, Versell, Replet, Sierra, Clay, and hundreds of other winning companies all have in common?”
▶ Watch at ~5:15approx.
SierraMentionscompany · Bret Taylor and Clay Bavor
“What do OpenAI, Anthropic, Cursor, Versell, Replet, Sierra, Clay, and hundreds of other winning companies all have in common?”
▶ Watch at ~5:15approx.
WorkOSRecommendscompany · WorkOS, Inc.
“Work OS allows you to build faster with delightful APIs, comprehensive docs, and a smooth developer experience.”
▶ Watch at ~6:00approx.
LinearMentionssoftware · Linear
“every new website that came out was just a copy of linear's website”
▶ Watch at ~14:00approx.
CodexUsessoftware · OpenAI
“now we use it for everything”
▶ Watch at ~16:00approx.
Claude CodeMentionssoftware · Anthropic
“Jenny, who is the head of design for clock code and co-work and such”
▶ Watch at ~16:45approx.
CoworkMentionssoftware · Anthropic
“Jenny, who is the head of design for clock code and co-work and such”
▶ Watch at ~16:45approx.
FigmaMentionssoftware · Figma
“kind of we saw with like you know Figma and Origami and all of these tools”
▶ Watch at ~18:30approx.
Origami StudioMentionssoftware · Meta
“kind of we saw with like you know Figma and Origami and all of these tools”
▶ Watch at ~18:30approx.
XeroxMentionscompany
“I believe that this this might have started with Xerox.”
▶ Watch at ~23:30approx.
UpthereMentionscompany
“First company I interned at, it was a company called Up There did the same thing.”
▶ Watch at ~23:30approx.
TypeScriptMentionssoftware · Microsoft
“I didn't care about like assembly language or memorizing TypeScript syntax”
▶ Watch at ~26:45approx.
MercuryUsescompany · Mercury
“I've been a customer of Mercury's for over 6 years. I have never once thought about leaving.”
▶ Watch at ~34:00approx.
CommandUsessoftware · Mercury
“I've been using Command to transfer money around to figure out what categories I've been spending the most money in”
▶ Watch at ~34:30approx.
ChatGPTMentionssoftware · OpenAI
“We had operator before that in chatbt, right?”
▶ Watch at ~36:00approx.
OperatorMentionssoftware · OpenAI
“We had operator before that in chatbt, right? That didn't work out. Very cool idea.”
▶ Watch at ~36:00approx.
AtlasMentionssoftware · Atlassian
“go back to Atlas, we had agent working inside of Atlas and, you know, that was pretty cool.”
▶ Watch at ~36:00approx.
Claude CodeMentionssoftware · Anthropic
“and then the cloud code comes out totally local like not hooked up to the cloud.”
▶ Watch at ~37:00approx.
NotionUsessoftware · Notion Labs
“I had a a you know notion doc somewhere with everything that needed to happen”
▶ Watch at ~43:45approx.
SlackUsessoftware · Slack Technologies
“I will see the daily brief that I have from like everything from the 3,000 Slack channels that I'm in”
▶ Watch at ~44:30approx.
OpenClawMentionssoftware · Peter Steinberger
“I don't think people realize that uh your app can act a lot like open claw.”
▶ Watch at ~46:00approx.
Google Cloud ConsoleUsessoftware · Google
“you have to go into like the Google cloud console and set up all these pups subhub API things and triggers.”
▶ Watch at ~47:00approx.
ObsidianMentionssoftware · Dynalist Inc.
“I set up an obsidian base or a notion area and I tell it how to basically build my mind palace”
▶ Watch at ~48:15approx.
NotionMentionssoftware · Notion Labs
“I set up an obsidian base or a notion area and I tell it how to basically build my mind palace”
▶ Watch at ~48:15approx.
SalesforceMentionscompany · Salesforce
“using notion and linear and Salesforce inside with your agent kind of helping you along”
▶ Watch at ~49:30approx.
Google ChromeMentionssoftware · Google
“We also have the the ability to install a Chrome extension where the app connects to Chrome.”
▶ Watch at ~49:45approx.
ElectronUsessoftware · OpenJS Foundation
“we originally launched the app. It's an Electron app.”
▶ Watch at ~50:00approx.
VS CodeMentionssoftware · Microsoft
“Are we trying to do key mapping to VS Code or to Chrome or to our own thing or to linear”
▶ Watch at ~51:00approx.
Microsoft ExcelUsessoftware · Microsoft
“the app talks directly to the addin in Microsoft Excel on your desktop.”
▶ Watch at ~56:45approx.
Adobe Premiere ProUsessoftware · Adobe
“It was able to understand that he used Premiere Pro.”
▶ Watch at ~57:45approx.
ChatGPTMentionssoftware · OpenAI
“how can we seamlessly interact with these tools that you're already using”
▶ Watch at ~58:30approx.
The GruffaloRecommendsbook · Julia Donaldson
“There's one called The Gruff to my kids.”
▶ Watch at ~1:02:00approx.
The Big Orange SplotRecommendsbook · Daniel Manus Pinkwater
“My favorite children's book ever is a very old one and it's called The Big Orange Spot or some something along those lines.”
▶ Watch at ~1:02:45approx.
NetflixMentionscompany · Netflix
“So, The Magic School Bus is back um on Netflix.”
▶ Watch at ~1:04:00approx.
The Magic School Bus Rides AgainRecommendstv show
“So, The Magic School Bus is back um on Netflix. It's It's a new animated.”
▶ Watch at ~1:04:00approx.
LinearRecommendssoftware · Linear
“I think linear linear does a great job. Like linear until until this linear was like my favorite at least software product.”
▶ Watch at ~1:04:45approx.
Lenny's PodcastCoinedpodcast · Lenny Rachitsky
“You can find all past episodes or learn more about the show at lennispodcast.com.”
▶ Watch at ~1:06:30approx.
Apple PodcastsMentionssoftware · Apple Inc.
“you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app.”
▶ Watch at ~1:06:30approx.
SpotifyMentionssoftware · Spotify
“you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app.”
▶ Watch at ~1:06:30approx.

Spot an error or want something removed? Request a correction or removal.

Insights & moments

The myth-busts, hot takes, explainers, and tools worth keeping.

Myth Buster· 2

Myth Buster06:30

PRDs Aren't Dead — You Just Have to Pick the Right Medium

Against the popular 'PRDs are dead, prototypes are in' claim, Andrew pushes back. When implementation is abundant, the skill is choosing the right format for the point you're making: a document for product clarity in a vague area, a prototype to stress-test an interaction.

Non-engineers are tempted to jump straight to a prototype to show what they mean
Engineers are tempted to write lots of documents that aren't worth reading
The format should match the point: docs for clarity, prototypes for interaction testing
Because building is cheap, choosing the medium is now the important decision

“you've seen many product leaders say PRDS are dead prototypes are in and I actually don't believe this at all.”
Andrew Ambrosino · 07:00

“if implementation is abundant, then it's really important to pick the right format for the point you're trying to make.”
Andrew Ambrosino · 07:30

#product#prd#prototyping#communication

Myth Buster16:30

Is the Design Process Dead? Both True and False

Andrew was never a fan of the formal design process even before AI — the diverge/converge, research-guaranteed-quality academic ritual. He agrees the day-to-day specifics are dead, but says the process as an overlay (knowing what stage you're at) matters more than ever now that speed of implementation has collapsed.

The old process assumed you could only afford to build once, so you exhaustively explored first
Prototyping got pulled in early via Figma/Origami; now full implementation gets pulled in too
Tied to exact tools and day-to-day specifics, the process is dead
As an overlay that marks where you are in the process, it's more important than ever

“So to say the design process is dead, I feel like it's both true and false, right?”
Andrew Ambrosino · 20:30

“I genuinely was not a fan of this process before AI”
Andrew Ambrosino · 17:00

#design#process#product#ai

Hot Take· 3

Hot Take03:00

Implementation Is Cheap Now — Taste Is the Real Bottleneck

Andrew argues the traditional product process has inverted: because anyone can now stand up any feature by talking to a model, implementation is no longer the expensive part. What's scarce is taste and curation — sifting the dozens of uncoordinated attempts at the same feature into something coherent.

Anyone can build almost any feature from scratch just by talking to the models
Old process derisked expensive implementation up front via docs, research and prototypes
That assumption is gone; the bottleneck moved from building to judging
One needed feature might have ~90 uncoordinated teams implementing it at once
The hard work is curation: what's good, what to fold together, how to frame it

“The implementation is actually not the expensive part anymore. It's dare I say taste.”
Andrew Ambrosino · 05:00

“right now I'm sure there are 90 different explorations for there's this feature that we desperately need to do”
Andrew Ambrosino · 04:30

#product#taste#ai#process#openai

Hot Take24:30

Getting Rid of the Product Role Is a Terrible Idea

Andrew warns against the extreme 'everyone's just a builder' bandwagon. Eliminating roles dangerously eliminates the idea that disciplines have knowable best practices — hard-won processes that get abandoned because someone wrote a bit of code. Every discipline has a real skill component.

Killing roles can kill the recognition that specialties have knowable best practices
Product as a discipline has real, tried-and-failed processes worth keeping
The 'this isn't your lane' gatekeeping can go away — but not everyone can do everything, in breadth or depth
You can use Excel and still not be able to work on the finance team

“I I've heard a lot of companies be like, we're getting rid of the product role, which I think is, by the way, a terrible…”
Andrew Ambrosino · 25:00

“part of the danger in eliminating the concept of roles is that it can dangerously eliminate the idea that things are specialties with knowable best…”
Andrew Ambrosino · 25:00

#roles#product#hiring#management

Hot Take40:30

A Plea to Research: Make Models Better at Deleting Code

Andrew calls out a core weakness blocking fully autonomous development: models almost always increase complexity. His public ask to research teams anywhere is to make models better at deleting code — because complexity creep becomes a real problem when you try to put development on autopilot.

All models currently tend to increase complexity
Complexity creep is a blocker for autonomous, unsupervised development
Andrew's explicit ask: make models better at deleting code
They're not yet at a 'set up a loop that improves the app' stage, but trying

“If research is listening at any company, please make the models better at deleting code.”
Andrew Ambrosino · 41:00

“One thing that I think all models suffer with right now is just they they usually increase complexity.”
Andrew Ambrosino · 40:30

#models#code#autonomy#research

Explainer· 3

Explainer10:00

What 'Good Taste' Actually Means (Beyond Aesthetics)

Andrew unpacks the buzzword 'taste.' People overemphasize the aesthetic part; taste is really systems thinking — how a thing fits the wider context, what theme it belongs to, and, most importantly, deciding what to build in the first place when you could build anything.

There's an aesthetic component (e.g. an animation that's too snappy for its meaning)
But the bigger part is systems thinking: how this fits the whole and where you're going
Much of taste is wider context and how to present information
The real taste question is 'if we can build anything, what's the goal and how do we get there?'

“there's also a a systems thinking part of it. Like how does this fit in the system?”
Andrew Ambrosino · 11:00

“how do we how do we get there that I think is like actually the real taste question here.”
Andrew Ambrosino · 12:00

#taste#design#product#judgment

Explainer12:00

Why Frontier Models Are Still Bad at Design

Andrew gives practical and deeper reasons AI lags at design. Design is harder to grade than code (there's no clean compile-or-not loop), labs prioritized coding because it accelerates AI research, and design demands novelty plus a codebase-abstraction layer that pure visual skill doesn't cover.

Design is harder to grade than code — the human taste feedback loop is tedious to build
Labs invested in coding first because correct code accelerates AI research; design doesn't feed that flywheel
Design needs novelty and randomness, whereas engineering wants to reuse known patterns
A rebrand isn't updating 263 components — it's the semantic abstractions between them, which models still miss

“I think design's a little bit harder to grade um than than software”
Andrew Ambrosino · 12:30

“if I have a model that outputs linear's website every time that's not the challenge here right”
Andrew Ambrosino · 14:00

#ai#design#models#research

Explainer28:30

'Zone Defense': How Product People Should Coordinate Now

Andrew describes running product like zone defense. If two product people work too closely, that's a bad signal — you want to spread out, find the gaps, and get full company coverage. With top-down year-long planning dead, taste-makers steer chaotic idea generation from inception to shipped product.

Two product people working too closely is often a bad signal
Do a force-directed exercise to find gaps and create space between people
Top-down, year-long planning no longer works amid the chaos of ideas
Taste-makers guide products from inception; you want full 'company coverage'

“if two product people are working too closely that's often not a good signal”
Andrew Ambrosino · 28:30

#product#management#coordination#planning

Story· 3

Story33:30

The Same Codex App Would Have Failed in November

Andrew is confident the Codex app they shipped in February would have flat-out failed if released in November — with the exact same shape. The only difference was the models between those months. It's the case for building ambitious features now and letting them 'bake' until a model leap makes them work.

Identical product shape, radically different outcome just months apart
The only variable that changed was model intelligence
Strategy: list features you want, prototype them, ship the ready ones, let others bake
Re-try baked features each time there's a leap in the models

“I am very confident that the Codex app that we released in February, if that had been ready in November, it would have absolutely failed…”
Andrew Ambrosino · 33:30

#codex#product#timing#models#openai

Story52:30

Codex Was 'Actively Hostile' to Non-Engineers — Who Refused to Leave

Once Codex hit internal PMF with engineers, people from marketing, comms, finance and legal started using it too — even though the app was actively hostile to them, showing code and asking to run terminal commands. OpenAI tried building friendlier surfaces for those personas, but nobody would leave Codex.

Codex hit clear internal PMF with engineering and research workflows first
Non-technical staff adopted it despite it being 'actively hostile' to them
OpenAI tried porting Codex lessons into ChatGPT and Atlas for other personas
The revealing result: nobody would leave Codex for the apps built for them

“we have people from marketing from comms from finance from legal from basically every discipline who are using this codeex app even though it is…”
Andrew Ambrosino · 53:00

“nobody would leave the Codex app for the apps that were allegedly for these other personas.”
Andrew Ambrosino · 54:00

#codex#adoption#pmf#openai

Story57:30

Codex Built Itself a Premiere Pro Extension to Edit Videos

Their in-house videographer Brent edited launch videos with Codex — not because it's a video editor, but out of curiosity. Codex understood he used Premiere Pro, edited the backing files, and when it couldn't do everything, built itself an extension it could install into Premiere Pro and talk to.

Codex isn't a video editor and has no video UI
It started because Brent was simply curious whether Codex could edit videos
It edited the files backing Premiere Pro's timeline
When that wasn't enough, it wrote and installed its own Premiere Pro extension to control the app

“So naturally, what Codex then did was built itself an extension that could be installed into Premiere Pro that it could then talk to”
Andrew Ambrosino · 58:00

“He started just because he was curious if Codex could edit videos.”
Andrew Ambrosino · 57:30

#codex#video#extensions#ambition

Takeaway· 4

Takeaway08:30

A Prototype That Looks Production-Ready Can Anchor You Wrong

The medium used to carry signal about where you were in the process — something that looked like production meant assumptions had been derisked. That link is now broken. A polished-looking exploration can trick a whole company into thinking it's ready to ship when it isn't.

Previously, 'looks like production' implied late-stage, derisked, design-reviewed work
Now polish and process-stage are divorced from each other
A too-polished exploration makes people say 'can we release this now?'
It may look ready for prod but not reflect the research or the business goal

“you do not want to over anchor on this thing that was meant to be an exploration, but now it looks so production ready”
Andrew Ambrosino · 09:30

#design#prototyping#product#process

Takeaway21:30

Your Role Is the Average of What You Spend Time On

In the Codex org, role collapse is real — designers speak engineer, PMs write code. Rather than being defined by the fences between disciplines, people are defined by the average of where their work actually lands. If most of your work is PM work, you're a PM for now.

The Codex org saw more role collapse than other teams because it's a technical product
Designers speak engineer; PMs write code and use technical language
People are defined less by discipline boundaries, more by the average of their work
The whole app is shaped by a dogfooding loop — they use the app even when it's not the best tool

“everybody's sort of defined less by the fence and the boundaries of where design stops and engineering starts, but more the average of where they're…”
Andrew Ambrosino · 22:00

#roles#teams#product#openai

Takeaway31:30

Nine-Month Plans Are False Precision

Andrew says planning isn't revolutionary at OpenAI — the shorter-term something is, the more detail it needs. They still plan nine months out, but it has to stay hazy: any precision added to a long-range plan right now is false precision because the models keep changing what's possible.

The shorter-term a thing is, the more detail its plan needs
Long-range plans must stay hazy on purpose
Precision on a nine-month plan is false precision and wastes time
On the applied product side, anything planned in November wasn't what actually happened

“any amount of precision that you add to a 9-month plan right now is false precision.”
Andrew Ambrosino · 32:00

“the shorter term something is, the more detail it needs.”
Andrew Ambrosino · 32:00

#planning#roadmap#product#ai

Takeaway1:07:30

Don't Get Married to Your Process — Marry Your Outcomes

Andrew's one piece of advice for succeeding with AI: don't get married to your exact process, get married to the outcomes you're uniquely able to deliver, and change your process freely to try things. Tying your identity to a specific tool or skill (like Figma auto layout) is a trap when AI will out-do that too.

Don't get married to your exact process
Marry the outcomes you are uniquely able to deliver
Change your process to try new things
Being 'the best at Figma auto layout' is a losing bet — AI will be better at that

“do not get married to your exact process. Get married to like the outcomes that you are uniquely able to deliver”
Andrew Ambrosino · 1:08:00

#career#ai#process#advice

Key ideas

Frameworks in this episode

Adversarial Dogfooding Loop

Build-and-Bake: Ship the Same Feature Until the Model Catches Up

Detune Precision by Time Horizon

Label the Process Stage, Not the Polish

Match the Medium to the Point

Zone Defense for Product Work

People & resources mentioned

People · 7

Resources · 47

Insights & moments

⚡Myth Buster· 2

PRDs Aren't Dead — You Just Have to Pick the Right Medium

Is the Design Process Dead? Both True and False

◆Hot Take· 3

Implementation Is Cheap Now — Taste Is the Real Bottleneck

Getting Rid of the Product Role Is a Terrible Idea

A Plea to Research: Make Models Better at Deleting Code

✶Explainer· 3

What 'Good Taste' Actually Means (Beyond Aesthetics)

Why Frontier Models Are Still Bad at Design

'Zone Defense': How Product People Should Coordinate Now

❝Story· 3

The Same Codex App Would Have Failed in November

Codex Was 'Actively Hostile' to Non-Engineers — Who Refused to Leave

Codex Built Itself a Premiere Pro Extension to Edit Videos

▲Takeaway· 4

A Prototype That Looks Production-Ready Can Anchor You Wrong

Your Role Is the Average of What You Spend Time On

Nine-Month Plans Are False Precision

Don't Get Married to Your Process — Marry Your Outcomes

Myth Buster· 2

Hot Take· 3

Explainer· 3

Story· 3

Takeaway· 4