Apr 6, 2026 · 29m · a16z

OpenClaw, Claude Code, and the Future of Software | Peter Yang on The a16z Show

Anish Acharya · 14m spoken Peter Yang · 11m spoken
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Host Anish Acharya interviews Roblox Product Lead Peter Yang on The a16z Show to explore personal AI agent setups, developer tooling shifts, and the future of work. Together, they discuss the OpenClaw ecosystem, vibe coding with Claude Code, corporate restructuring, and the broader economic impacts of AI automation.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. How this is scored →

The host as informed peer 6.2 Guest teaching 2.1 Guest disagreement 1.7 The host pushing back 2.8
05100:0010:0020:000:42–3:31 · The host as informed peer 3/10 The a16z Show Title Sequence The host opens with friendly banter about their shared background at Credit Karma before probing into Peter's experience with OpenClaw. The host gently challenges Peter on whether OpenClaw offers anything genuinely distinct from standard LLMs beyond interface polish.3:31–6:10 · The host as informed peer 5/10 Conversational Interfaces vs. Agent Self-Modification The host demonstrates technical understanding of agent architectures, asking specifically about file-based memory files and skill directories. Peter shares practical observations about OpenClaw's memory limitations and how he patched them with secondary retrieval tools.6:10–8:35 · The host as informed peer 6/10 Will Agents Replace Task-Based Mobile Apps? When Peter suggests mobile apps will die as agents take over tasks, the host offers a counter-framework centered on emotional intent behind app usage. The host pushes back on the idea of a single agent replacing specialized interfaces that fulfill distinct psychological needs.8:35–11:05 · The host as informed peer 6/10 Agent Permissions and Churning to Claude The host shows strong familiarity with developer workflows, contrasting Claude Code's conversational flow against OpenAI Codex's deliberate reasoning latency. Peter shares his frustration with ChatGPT's defensive conversational prompts.11:05–13:39 · The host as informed peer 6/10 Harness Quality-of-Life Features in AI Tooling The host highlights specific UX harness features in AI tools while actively pushing back on the claim that companies will build custom agentic tools to churn off cheap SaaS like Calendly. The host highlights the maintenance burden and low return on effort of replacing low-cost software.13:39–16:59 · The host as informed peer 7/10 AI's Impact on Figma and Design Workflows The host introduces a nuanced conceptual model dividing software into 'thinking tools' and 'making tools' to explain Figma's enduring moat. The host also draws parallels to historical programming paradigms like Microsoft Excel.16:59–19:47 · The host as informed peer 6/10 Rethinking Corporate Structure and Agentic Teams Peter criticizes corporate bureaucracy and OKRs, advocating for smaller team sizes powered by agents. The host agrees and builds on this premise, explaining how agents eliminate emotional friction in cross-functional alignment.19:47–22:40 · The host as informed peer 7/10 Unemployed Builders vs. Corporate Planning Cycles Peter offers a hot take that unemployed builders hold an advantage over corporate PMs due to uninterrupted time to experiment. The host contextualizes high-velocity iteration using an optimization model of rapid local hill climbing versus deliberate global search.22:40–26:15 · The host as informed peer 8/10 Micro-TAM Businesses and the Next Generation Peter poses a strategic question regarding consumer retention when agents bypass UI layers. The host responds with a comprehensive breakdown of consumer monetization trends, contrasting ad-supported models with direct subscription and token consumption models.26:15–29:29 · The host as informed peer 8/10 The Emerging Agent Stack and Job Automation Realities When Peter brings up fears of AI-driven job displacement, the host pushes back using proprietary startup data from venture deal flow. The host categorizes AI products into partial efficiency boosters versus rare full-job automators to argue against doom scenarios.0:42–3:31 · Guest teaching 3/10 The a16z Show Title Sequence The host opens with friendly banter about their shared background at Credit Karma before probing into Peter's experience with OpenClaw. The host gently challenges Peter on whether OpenClaw offers anything genuinely distinct from standard LLMs beyond interface polish.3:31–6:10 · Guest teaching 3/10 Conversational Interfaces vs. Agent Self-Modification The host demonstrates technical understanding of agent architectures, asking specifically about file-based memory files and skill directories. Peter shares practical observations about OpenClaw's memory limitations and how he patched them with secondary retrieval tools.6:10–8:35 · Guest teaching 2/10 Will Agents Replace Task-Based Mobile Apps? When Peter suggests mobile apps will die as agents take over tasks, the host offers a counter-framework centered on emotional intent behind app usage. The host pushes back on the idea of a single agent replacing specialized interfaces that fulfill distinct psychological needs.8:35–11:05 · Guest teaching 2/10 Agent Permissions and Churning to Claude The host shows strong familiarity with developer workflows, contrasting Claude Code's conversational flow against OpenAI Codex's deliberate reasoning latency. Peter shares his frustration with ChatGPT's defensive conversational prompts.11:05–13:39 · Guest teaching 2/10 Harness Quality-of-Life Features in AI Tooling The host highlights specific UX harness features in AI tools while actively pushing back on the claim that companies will build custom agentic tools to churn off cheap SaaS like Calendly. The host highlights the maintenance burden and low return on effort of replacing low-cost software.13:39–16:59 · Guest teaching 2/10 AI's Impact on Figma and Design Workflows The host introduces a nuanced conceptual model dividing software into 'thinking tools' and 'making tools' to explain Figma's enduring moat. The host also draws parallels to historical programming paradigms like Microsoft Excel.16:59–19:47 · Guest teaching 1/10 Rethinking Corporate Structure and Agentic Teams Peter criticizes corporate bureaucracy and OKRs, advocating for smaller team sizes powered by agents. The host agrees and builds on this premise, explaining how agents eliminate emotional friction in cross-functional alignment.19:47–22:40 · Guest teaching 2/10 Unemployed Builders vs. Corporate Planning Cycles Peter offers a hot take that unemployed builders hold an advantage over corporate PMs due to uninterrupted time to experiment. The host contextualizes high-velocity iteration using an optimization model of rapid local hill climbing versus deliberate global search.22:40–26:15 · Guest teaching 3/10 Micro-TAM Businesses and the Next Generation Peter poses a strategic question regarding consumer retention when agents bypass UI layers. The host responds with a comprehensive breakdown of consumer monetization trends, contrasting ad-supported models with direct subscription and token consumption models.26:15–29:29 · Guest teaching 1/10 The Emerging Agent Stack and Job Automation Realities When Peter brings up fears of AI-driven job displacement, the host pushes back using proprietary startup data from venture deal flow. The host categorizes AI products into partial efficiency boosters versus rare full-job automators to argue against doom scenarios.0:42–3:31 · Guest disagreement 1/10 The a16z Show Title Sequence The host opens with friendly banter about their shared background at Credit Karma before probing into Peter's experience with OpenClaw. The host gently challenges Peter on whether OpenClaw offers anything genuinely distinct from standard LLMs beyond interface polish.3:31–6:10 · Guest disagreement 1/10 Conversational Interfaces vs. Agent Self-Modification The host demonstrates technical understanding of agent architectures, asking specifically about file-based memory files and skill directories. Peter shares practical observations about OpenClaw's memory limitations and how he patched them with secondary retrieval tools.6:10–8:35 · Guest disagreement 2/10 Will Agents Replace Task-Based Mobile Apps? When Peter suggests mobile apps will die as agents take over tasks, the host offers a counter-framework centered on emotional intent behind app usage. The host pushes back on the idea of a single agent replacing specialized interfaces that fulfill distinct psychological needs.8:35–11:05 · Guest disagreement 2/10 Agent Permissions and Churning to Claude The host shows strong familiarity with developer workflows, contrasting Claude Code's conversational flow against OpenAI Codex's deliberate reasoning latency. Peter shares his frustration with ChatGPT's defensive conversational prompts.11:05–13:39 · Guest disagreement 2/10 Harness Quality-of-Life Features in AI Tooling The host highlights specific UX harness features in AI tools while actively pushing back on the claim that companies will build custom agentic tools to churn off cheap SaaS like Calendly. The host highlights the maintenance burden and low return on effort of replacing low-cost software.13:39–16:59 · Guest disagreement 1/10 AI's Impact on Figma and Design Workflows The host introduces a nuanced conceptual model dividing software into 'thinking tools' and 'making tools' to explain Figma's enduring moat. The host also draws parallels to historical programming paradigms like Microsoft Excel.16:59–19:47 · Guest disagreement 2/10 Rethinking Corporate Structure and Agentic Teams Peter criticizes corporate bureaucracy and OKRs, advocating for smaller team sizes powered by agents. The host agrees and builds on this premise, explaining how agents eliminate emotional friction in cross-functional alignment.19:47–22:40 · Guest disagreement 3/10 Unemployed Builders vs. Corporate Planning Cycles Peter offers a hot take that unemployed builders hold an advantage over corporate PMs due to uninterrupted time to experiment. The host contextualizes high-velocity iteration using an optimization model of rapid local hill climbing versus deliberate global search.22:40–26:15 · Guest disagreement 1/10 Micro-TAM Businesses and the Next Generation Peter poses a strategic question regarding consumer retention when agents bypass UI layers. The host responds with a comprehensive breakdown of consumer monetization trends, contrasting ad-supported models with direct subscription and token consumption models.26:15–29:29 · Guest disagreement 2/10 The Emerging Agent Stack and Job Automation Realities When Peter brings up fears of AI-driven job displacement, the host pushes back using proprietary startup data from venture deal flow. The host categorizes AI products into partial efficiency boosters versus rare full-job automators to argue against doom scenarios.0:42–3:31 · The host pushing back 2/10 The a16z Show Title Sequence The host opens with friendly banter about their shared background at Credit Karma before probing into Peter's experience with OpenClaw. The host gently challenges Peter on whether OpenClaw offers anything genuinely distinct from standard LLMs beyond interface polish.3:31–6:10 · The host pushing back 2/10 Conversational Interfaces vs. Agent Self-Modification The host demonstrates technical understanding of agent architectures, asking specifically about file-based memory files and skill directories. Peter shares practical observations about OpenClaw's memory limitations and how he patched them with secondary retrieval tools.6:10–8:35 · The host pushing back 4/10 Will Agents Replace Task-Based Mobile Apps? When Peter suggests mobile apps will die as agents take over tasks, the host offers a counter-framework centered on emotional intent behind app usage. The host pushes back on the idea of a single agent replacing specialized interfaces that fulfill distinct psychological needs.8:35–11:05 · The host pushing back 1/10 Agent Permissions and Churning to Claude The host shows strong familiarity with developer workflows, contrasting Claude Code's conversational flow against OpenAI Codex's deliberate reasoning latency. Peter shares his frustration with ChatGPT's defensive conversational prompts.11:05–13:39 · The host pushing back 5/10 Harness Quality-of-Life Features in AI Tooling The host highlights specific UX harness features in AI tools while actively pushing back on the claim that companies will build custom agentic tools to churn off cheap SaaS like Calendly. The host highlights the maintenance burden and low return on effort of replacing low-cost software.13:39–16:59 · The host pushing back 4/10 AI's Impact on Figma and Design Workflows The host introduces a nuanced conceptual model dividing software into 'thinking tools' and 'making tools' to explain Figma's enduring moat. The host also draws parallels to historical programming paradigms like Microsoft Excel.16:59–19:47 · The host pushing back 1/10 Rethinking Corporate Structure and Agentic Teams Peter criticizes corporate bureaucracy and OKRs, advocating for smaller team sizes powered by agents. The host agrees and builds on this premise, explaining how agents eliminate emotional friction in cross-functional alignment.19:47–22:40 · The host pushing back 3/10 Unemployed Builders vs. Corporate Planning Cycles Peter offers a hot take that unemployed builders hold an advantage over corporate PMs due to uninterrupted time to experiment. The host contextualizes high-velocity iteration using an optimization model of rapid local hill climbing versus deliberate global search.22:40–26:15 · The host pushing back 2/10 Micro-TAM Businesses and the Next Generation Peter poses a strategic question regarding consumer retention when agents bypass UI layers. The host responds with a comprehensive breakdown of consumer monetization trends, contrasting ad-supported models with direct subscription and token consumption models.26:15–29:29 · The host pushing back 4/10 The Emerging Agent Stack and Job Automation Realities When Peter brings up fears of AI-driven job displacement, the host pushes back using proprietary startup data from venture deal flow. The host categorizes AI products into partial efficiency boosters versus rare full-job automators to argue against doom scenarios.

speaking balance: gold is the host, purple is the guest (3 minute bins)

0:00 · the host 0% · guest 100%0:00 · the host 0% · guest 100%3:00 · the host 0% · guest 100%3:00 · the host 0% · guest 100%6:00 · the host 0% · guest 100%6:00 · the host 0% · guest 100%9:00 · the host 0% · guest 100%9:00 · the host 0% · guest 100%12:00 · the host 0% · guest 100%12:00 · the host 0% · guest 100%15:00 · the host 0% · guest 100%15:00 · the host 0% · guest 100%18:00 · the host 0% · guest 100%18:00 · the host 0% · guest 100%21:00 · the host 0% · guest 100%21:00 · the host 0% · guest 100%24:00 · the host 0% · guest 100%24:00 · the host 0% · guest 100%27:00 · the host 0% · guest 100%27:00 · the host 0% · guest 100%
Sharpest disagreement ▶ 17:10 Peter criticizes corporate growth and wasteful OKR culture

Peter forcefully argues that corporate expansion turns companies into terrible workplaces filled with pointless three-hour meetings.

Hardest push from the host ▶ 13:14 Host rejects premise of replacing simple SaaS like Calendly

The host directly challenges Peter's premise about building internal tools to churn off SaaS, pointing out that paying $20/month for software like Calendly is far more efficient than maintaining custom agentic builds.

Biggest teaching moment ▶ 5:25 Peter explains OpenClaw's memory limitations and multi-layer fix

Peter educates the host on why basic file-based memory fails in practice and explains his setup using Toby's QMD search tool to improve context retrieval.

The host holds their own ▶ 27:05 Host uses venture data to counter AI job loss narrative

The host draws on extensive deal flow observation to demonstrate that very few AI startups achieve 100% task automation, reframing AI as a productivity multiplier rather than a driver of net job destruction.

the scores for every segment, with the reasoning behind each
ChapterTopicThe host as informed peerGuest teachingGuest disagreementThe host pushing backWhy
The a16z Show Title Sequence 3312 The host opens with friendly banter about their shared background at Credit Karma before probing into Peter's experience with OpenClaw. The host gently challenges Peter on whether OpenClaw offers anything genuinely distinct from standard LLMs beyond interface polish.
Conversational Interfaces vs. Agent Self-Modification 5312 The host demonstrates technical understanding of agent architectures, asking specifically about file-based memory files and skill directories. Peter shares practical observations about OpenClaw's memory limitations and how he patched them with secondary retrieval tools.
Will Agents Replace Task-Based Mobile Apps? 6224 When Peter suggests mobile apps will die as agents take over tasks, the host offers a counter-framework centered on emotional intent behind app usage. The host pushes back on the idea of a single agent replacing specialized interfaces that fulfill distinct psychological needs.
Agent Permissions and Churning to Claude 6221 The host shows strong familiarity with developer workflows, contrasting Claude Code's conversational flow against OpenAI Codex's deliberate reasoning latency. Peter shares his frustration with ChatGPT's defensive conversational prompts.
Harness Quality-of-Life Features in AI Tooling 6225 The host highlights specific UX harness features in AI tools while actively pushing back on the claim that companies will build custom agentic tools to churn off cheap SaaS like Calendly. The host highlights the maintenance burden and low return on effort of replacing low-cost software.
AI's Impact on Figma and Design Workflows 7214 The host introduces a nuanced conceptual model dividing software into 'thinking tools' and 'making tools' to explain Figma's enduring moat. The host also draws parallels to historical programming paradigms like Microsoft Excel.
Rethinking Corporate Structure and Agentic Teams 6121 Peter criticizes corporate bureaucracy and OKRs, advocating for smaller team sizes powered by agents. The host agrees and builds on this premise, explaining how agents eliminate emotional friction in cross-functional alignment.
Unemployed Builders vs. Corporate Planning Cycles 7233 Peter offers a hot take that unemployed builders hold an advantage over corporate PMs due to uninterrupted time to experiment. The host contextualizes high-velocity iteration using an optimization model of rapid local hill climbing versus deliberate global search.
Micro-TAM Businesses and the Next Generation 8312 Peter poses a strategic question regarding consumer retention when agents bypass UI layers. The host responds with a comprehensive breakdown of consumer monetization trends, contrasting ad-supported models with direct subscription and token consumption models.
The Emerging Agent Stack and Job Automation Realities 8124 When Peter brings up fears of AI-driven job displacement, the host pushes back using proprietary startup data from venture deal flow. The host categorizes AI products into partial efficiency boosters versus rare full-job automators to argue against doom scenarios.

Statements from this episode (29)

Prediction Not checkable as stated
Yang: AI Agents Will Shrink Product Teams to Two or Three People
“And instead of having like a ten-person product team, you have like a two or three-person product team and you have a bunch of agents to help Help you.”
Peter Yang Apr 6, 2026 ▶ 0:25
Disclosure
Peter Yang uses OpenClaw for analytics, banking, docs, and websites
“It, like, pulls analytics for me across YouTube and, like, my Mercury banking account. It can update Google documents for me. It can build a website for me.”
Peter Yang Apr 6, 2026 ▶ 2:17
Opinion
Yang: OpenClaw via Telegram feels more personal than Claude or ChatGPT
“Because I've installed on Telegram, it just feels like more personal than using like Cloud or ChatGPT.”
Peter Yang Apr 6, 2026 ▶ 3:13
Opinion
Yang: 70–80% of OpenClaw's value is its conversational interface
“I think it's probably like, 70, 80%, just like the per, per, per personable part of it, because I mostly just talk to it and like, you know, through voice.”
Peter Yang Apr 6, 2026 ▶ 3:50
Disclosure
Peter Yang uses complex prompts for Claude but simple texting for OpenClaw
“With cloud, I have like very fancy prompts like very long prompts, but with open cloud, I just kind of text it.”
Peter Yang Apr 6, 2026 ▶ 4:56
Opinion
Peter Yang: OpenClaw's default memory system is weak and forgets context
“I think the default memory system is actually not that great.”
Peter Yang Apr 6, 2026 ▶ 5:25
Disclosure
Peter Yang uses a custom three-layer memory system for OpenClaw
“So, so I actually installed this, like, three-layer memory system that, to be honest, I don't fully understand, but it has, like, it has, like, Toby's QMD search tool.”
Peter Yang Apr 6, 2026 ▶ 5:36
Disclosure
Yang: OpenClaw Integrations Drastically Reduced His Utility App Usage
“Ever since I set up all these apps, like Mercury, MCP, and all this kind of crap on my open call, like, I don't actually open those apps much anymore, you know.”
Peter Yang Apr 6, 2026 ▶ 6:28
Prediction Not checkable as stated
Yang: Task-Oriented Apps Will Decline Before Entertainment Apps
“I think the ones that are gonna dive first or, like, maybe get less usage first is, like, apps that you're just opening to try to complete a task. Like, you actually are trying to do something, you know. Like, apps that you're opening to, like, get entertainme…”
Peter Yang Apr 6, 2026 ▶ 6:40
Insight
Acharya: People open smartphone apps to satisfy specific emotional states
“I've always had this theory that people open apps on their phone because they want to feel a feeling. You know, and I think, of course, there's some like functional set of needs, which is why you open calendar or something. But I also think that, you know, Wha…”
Anish Acharya Apr 6, 2026 ▶ 7:28
Disclosure
Yang manages AI agent context switching via distinct Telegram channels
“I do have multiple channels set up with Zoe in Telegram. Like, one is just to random voice replies, and the other one is we're actually working on our project together. And the other one, I have, like, a public channel where, like, I'm giving demos.”
Peter Yang Apr 6, 2026 ▶ 8:00
Disclosure
Yang Set Up Dedicated Hardware and Account Permissions for His AI
“Well, I did buy the Mac Mini and set up his own email. And, but I gave it, like, read access to my email and, like, calendar, and I also gave it, like, write access to some docs.”
Peter Yang Apr 6, 2026 ▶ 8:38
Prediction Held up
Yang: OpenAI Will Integrate Personal Agent Capabilities Directly Into ChatGPT
“I mean, I think that's what Peter Steinberg is working out at OpenAI, right? Yeah. He's probably going to build something to ChatGPT, which everybody uses so that ChatGPT can actually get stuff done for you and, like, maybe feels more human.”
Peter Yang Apr 6, 2026 ▶ 9:00
Disclosure
Yang Churned From ChatGPT Over Annoying Repetitive Conversational Prompts
“And dude, I got so annoyed about it that I kind of churned from ChatGPT.”
Peter Yang Apr 6, 2026 ▶ 9:23
Disclosure
Peter Yang uses Codex for real coding and Claude Code for vibing
“Codex is when I want to try to do something real, and Cloud Code is when I'm just like vibing.”
Peter Yang Apr 6, 2026 ▶ 9:41
Assertion Not checkable as stated
Yang: Startups Use Vibe Coders to Build Internal Tools Replacing SaaS
“I was talking to some folks the other day and like an AI native startup, and they're basically trying to, they have a bunch of vibe coders and all the vibe coders are just trying to build internal tools that replace their SaaS. That they're paying for.”
Peter Yang Apr 6, 2026 ▶ 12:04
Prediction Not checkable as stated
Yang: Slack will remain durable as a control plane for AI agents
“I don't think, I feel like Slack has a lot of legs, because Slack can also be the place where you talk to the agents themselves.”
Peter Yang Apr 6, 2026 ▶ 12:55
Prediction Not checkable as stated
Yang: Designers Who Ignore Vibe Coding Will Soon Be Obsolete
“As a designer, you kind of need to learn how to vibe code. Otherwise, you're going to, like, if you want to know how to do Figma, like, you're probably going to be, like, out of date in a couple of years.”
Peter Yang Apr 6, 2026 ▶ 13:56
Prediction Not checkable as stated
Yang: Coding Will Eat All Knowledge Work
“I feel like coding will eat all knowledge work.”
Peter Yang Apr 6, 2026 ▶ 15:22
Disclosure
Peter Yang gets 80% of his work drafted by AI
“I never start from zero. Like I always get the first 80% from AI.”
Peter Yang Apr 6, 2026 ▶ 16:07
Insight
Yang: Aligning cross-functional AI agents is easier than aligning humans
“I think it's way easier to cross-function the line of the agents than with humans.”
Peter Yang Apr 6, 2026 ▶ 17:50
Prediction Not checkable as stated
Acharya: AI will handle emotional office communications and negotiations
“Maybe the future of this is that a lot of that emotional subjective work gets handled. And we're sort of guiding the process, but not in the middle of it in a way that just doesn't suit us as humans.”
Anish Acharya Apr 6, 2026 ▶ 18:57
Opinion
Acharya: Most PMs do not know how to innovate products
“I think the black pill is I don't think most PMs know how to do that. In fact, many companies have zero people that know how to do that at all in any function.”
Anish Acharya Apr 6, 2026 ▶ 19:30
Opinion
Yang: Unemployed builders have more time to innovate than employed PMs
“My hot take is that like, I feel like if you're actually unemployed, like you probably have more time to be a builder and like to be innovative. Because you can actually, like, play all this stuff and, like, learn all this stuff while the PMs are trying to.”
Peter Yang Apr 6, 2026 ▶ 19:48
Opinion
Yang: Traditional corporate annual planning no longer works
“The traditional process where, like, do annual planning and, like, do all this bullshit, like, I just feel like that doesn't really work anymore, you know?”
Peter Yang Apr 6, 2026 ▶ 21:01
Prediction Not checkable as stated
Yang Wants His Kids to Build Businesses and Skip College
“That, that, that's my plan for my kids, dude. Like, I want them to just build, like bootstrap businesses in high, high school. And they can skip the whole college and, like corporate life.”
Peter Yang Apr 6, 2026 ▶ 23:16
Assertion Not checkable as stated
Acharya: AI Software Enables Consumption Revenue and High Direct Consumer Prices
“Consumers are now excited to try new things. They're willing to pay. They're willing to pay a really high price point. There's also consumption revenue in consumer for the first time.”
Anish Acharya Apr 6, 2026 ▶ 25:00
Prediction Not checkable as stated
Acharya: Consumer Software Will Feature Dual Interfaces for AI Agents and Humans
“Two, I think that a lot of the products will have a sort of, you know, it'll have an API interface for your agents to interact with or for, you know, for transactional sort of rote things. And then it'll have like a consumption based interface as well. So you …”
Anish Acharya Apr 6, 2026 ▶ 25:30
Prediction Not checkable as stated
Yang: Workforce will transition from mega-corporations to solopreneurs and smaller firms
“I feel like there's gonna be a transition from, like, these, like, 10,000 plus people companies. Laying a lot of people off to hopefully, like, more smaller companies like solopreneurs and stuff like that.”
Peter Yang Apr 6, 2026 ▶ 28:28
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