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This week on How I AI: Which AI model is the best designer? and ChatGPT agent mode, the “little helper” that transformed recruiting

2025-12-09 00:03:21

Here’s a weekly recap of new podcast episodes across Lenny’s Podcast Network:

Every Monday, host Claire Vo shares a 30- to 45-minute episode with a new guest demoing a practical, impactful way they’ve learned to use AI in their work or life. No pontificating—just specific and actionable advice.

ChatGPT agent mode: The “little helper” that transformed recruiting, crafted user personas, and solved parking nightmares at HoneyBook | Michal Peled

Brought to you by:

Brex—The intelligent finance platform built for founders

Google Gemini—Your everyday AI assistant

In this episode, Michal Peled walks through three real examples from her work at HoneyBook—using ChatGPT’s agent mode to automate LinkedIn recruiting (and surface candidates humans missed), turning static customer research into interactive AI personas, and even building a parking-avoidance calendar app for Giants games. Along the way, Michal breaks down how to structure great agent workflows, why interviewing humans is the key to good automation, and how tools like NotebookLM can turn messy research into reliable, citation-backed prompts.

Biggest takeaways:

ChatGPT agent mode is your “little helper” that can perform real-world tasks. Unlike regular ChatGPT, agent mode can navigate websites, perform searches, and execute complex workflows—all while narrating its thought process. This transforms it from a text generator into a true digital assistant that can replicate human workflows.
The best AI automation starts with interviewing humans about their process. Michal’s recruiting automation succeeded because she asked the hiring team exactly what criteria they use: “Candidates must be from Israel or working at an Israeli company, active on LinkedIn within 3 months, and employed at their current job for over a year.” By codifying these specific requirements, she created an agent that found candidates the team had missed.
The best prompt improvement technique: ask AI to fix your prompt. When AI isn’t giving you the results you want, Michal’s approach is to say: “This is the prompt I’m using. This is what’s wrong with the output. This is how I want it to be. Take away everything that doesn’t work well.”

▶️ Listen now on YouTube | Spotify | Apple Podcasts

Gemini 3 vs. Claude Opus 4.5 vs. GPT-5.1 Codex: Which AI model is the best designer?

Brought to you by: Lovable—Build apps by simply chatting with AI

In this episode, Claire runs a simple but revealing experiment: give the exact same prompt to three leading AI models—Gemini 3, Claude Opus 4.5, and GPT-5.1 Codex—and see which is actually good at design. One model produces a polished, thoughtful, near-production-ready redesign. One delivers something usable but uninspired. And one . . . reminds us that strong coding ability doesn’t always translate to front-end taste. If you’ve ever wondered which AI you should trust with real design work, this episode gives you the clearest answer yet.

Biggest takeaways:

Anthropic’s Opus 4.5 is the clear design winner. It delivered the most visually appealing and functionally complete redesign, with thoughtful details like hover effects with call-to-action arrows, placeholder images for missing content, and elegant background imagery instead of generic gradients.
Codex 5.1 struggles with front-end design. Despite its strong coding capabilities, OpenAI’s model delivered the weakest design, falling back on “AI slop purple gradients” and creating non-functional elements. The lesson: don’t use it as your design resource.
Gemini 3 is serviceable but lacks refinement. While it created a functional redesign with hero sections and card layouts, it missed opportunities for visual polish and didn’t handle edge cases (like missing images) as elegantly as Opus 4.5.

▶️ Listen now on YouTube | Spotify | Apple Podcasts

More shows coming soon. . . 👀
If you’re enjoying these episodes, reply and let me know what you’d love to learn more about: AI workflows, hiring, growth, product strategy—anything.

Catch you next week,
Lenny

P.S. Want every new episode delivered the moment it drops? Hit “Follow” on your favorite podcast app.

ChatGPT agent mode: The “little helper” that transformed recruiting, crafted user personas, and solved parking nightmares | Michal Peled (Honeybook)

2025-12-08 21:03:55

Michal Peled is a Technical Operations Engineer at HoneyBook who specializes in building internal tools and automations that eliminate friction for teams. In this episode, Michal demonstrates three practical AI use cases: using ChatGPT’s agent mode to automate LinkedIn recruiting, transforming customer research into interactive AI personas, and creating a custom calendar solution for a very San Francisco–specific problem—avoiding expensive parking during Giants games.

Listen or watch on YouTube, Spotify, or Apple Podcasts

What you’ll learn:

How to use ChatGPT agent mode to automate LinkedIn recruiting and find high-quality candidates that manual searches missed
The step-by-step process for turning static customer research into interactive AI personas that product and marketing teams can actually use
Why NotebookLM excels at creating prompts from source material with proper citations
How to structure agent-mode prompts to create effective “little helpers” that follow your exact workflow
A practical framework for improving your prompts when AI tools aren’t giving you the results you want
How internal tools teams can drive massive impact by focusing on eliminating friction in everyday workflows

Brought to you by:

Brex—The intelligent finance platform built for founders

Google Gemini—Your everyday AI assistant

In this episode, we cover:

(00:00) Introduction to Michal and ChatGPT agent mode

(02:10) Using agent mode for LinkedIn recruiting automation

(05:14) Creating effective prompts for agent mode

(10:50) Demo of agent mode searching LinkedIn profiles

(16:29) Results and team reception of the recruiting automation

(19:53) The outcome of implementing on Michal’s team

(23:50) Creating custom GPT personas from customer research

(28:43) Using NotebookLM to transform research into persona prompts

(35:00) Adding guardrails to custom GPT personas

(37:20) Demo of interacting with custom-persona GPTs

(41:02) Creating a calendar automation for parking during baseball games

(48:15) Lightning round and final thoughts

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

The 100-person AI lab that became Anthropic and Google's secret weapon | Edwin Chen (Surge AI)

2025-12-07 21:31:23

Edwin Chen is the founder and CEO of Surge AI, the company that teaches AI what’s good and bad, powering frontier labs with elite data, environments, and evaluations. Surge surpassed $1 billion in revenue with under 100 employees last year, completely bootstrapped—the fastest company in history to reach this milestone. Before founding Surge, Edwin was a research scientist at Google, Facebook, and Twitter and studied mathematics, computer science, and linguistics at MIT.

Listen on YouTube, Spotify and Apple Podcasts

We discuss:

How Surge reached over $1 billion in revenue with fewer than 100 people by obsessing over quality
The story behind how Claude Code got so good at coding and writing
The problems with AI benchmarks and why they’re pushing AI in the wrong direction
How RL environments are the next frontier in AI training
Why Edwin believes we’re still a decade away from AGI
Why taste and human judgment shape which AI models become industry leaders
His contrarian approach to company building that rejects Silicon Valley’s “pivot and blitzscale” playbook
How AI models will become increasingly differentiated based on the values of the companies building them

Brought to you by:

Vanta—Automate compliance. Simplify security.

WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs

Coda—The all-in-one collaborative workspace

Where to find Edwin Chen:

• X: https://x.com/echen

• LinkedIn: https://www.linkedin.com/in/edwinzchen

• Surge’s blog: https://surgehq.ai/blog

Referenced:

• Surge: https://surgehq.ai

• Surge’s product page: https://surgehq.ai/products

• Claude Code: https://www.claude.com/product/claude-code

• Gemini 3: https://aistudio.google.com/models/gemini-3

• Sora: https://openai.com/sora

• Terrence Rohan on LinkedIn: https://www.linkedin.com/in/terrencerohan

• Richard Sutton—Father of RL thinks LLMs are a dead end: https://www.dwarkesh.com/p/richard-sutton

• The Bitter Lesson: http://www.incompleteideas.net/IncIdeas/BitterLesson.html

• Reinforcement learning: https://en.wikipedia.org/wiki/Reinforcement_learning

• Grok: https://grok.com

• Warren Buffett on X: https://x.com/WarrenBuffett

• OpenAI’s CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai

• Anthropic’s CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next

• Brian Armstrong on LinkedIn: https://www.linkedin.com/in/barmstrong

• Interstellar on Prime Video: https://www.amazon.com/Interstellar-Matthew-McConaughey/dp/B00TU9UFTS

• Arrival on Prime Video: https://www.amazon.com/Arrival-Amy-Adams/dp/B01M2C4NP8

• Travelers on Netflix: https://www.netflix.com/title/80105699

• Waymo: https://waymo.com

• Soda versus pop: https://flowingdata.com/2012/07/09/soda-versus-pop-on-twitter

Recommended books:

• Stories of Your Life and Others: https://www.amazon.com/Stories-Your-Life-Others-Chiang/dp/1101972122

• The Myth of Sisyphus: https://www.amazon.com/Myth-Sisyphus-Vintage-International/dp/0525564454

• Le Ton Beau de Marot: In Praise of the Music of Language: https://www.amazon.com/dp/0465086454

• Gödel, Escher, Bach: An Eternal Golden Braid: https://www.amazon.com/G%C3%B6del-Escher-Bach-Eternal-Golden/dp/0465026567

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

Lenny may be an investor in the companies discussed.

My biggest takeaways from this conversation:

🧠 Community Wisdom: Combating ageism, facilitating roadmap discussions, 90-day onboarding plan, staying stealth pre-launch, and more

2025-12-07 01:01:25

👋 Hello and welcome to this week’s edition of ✨ Community Wisdom ✨ a subscriber-only email, delivered every Saturday, highlighting the most helpful conversations in our members-only Slack community.

Why LinkedIn is turning PMs into AI-powered "full stack builders” | Tomer Cohen (LinkedIn CPO)

2025-12-04 21:32:07

Tomer Cohen is the longtime chief product officer at LinkedIn, where he’s pioneering the Full Stack Builder program, a radical new approach to product development that fully embraces what AI makes possible. Under his leadership, LinkedIn has scrapped its traditional Associate Product Manager program and replaced it with an Associate Product Builder program that teaches coding, design, and PM skills together. He’s also introduced a formal “Full Stack Builder” title and career ladder, enabling anyone from any function to take products from idea to launch. In this conversation, Tomer explains why product development has become too complex at most companies and how LinkedIn is building an AI-powered product team that can move faster, adapt more quickly, and do more with less.

Listen on YouTube, Spotify and Apple Podcasts

We discuss:

How 70% of the skills needed for jobs will change by 2030
The broken traditional model: organizational bloat slows features to a six-month cycle
The Full Stack Builder model
Three pillars of making FSB work: platform, agents, and culture (culture matters most)
Building specialized agents that critique ideas and find vulnerabilities
Why off-the-shelf AI tools never work on enterprise code without customization
Top performers adopt AI tools fastest, contrary to expectations about leveling effects
Change management tactics: celebrating wins, making tools exclusive, updating performance reviews

Brought to you by:

Vanta—Automate compliance. Simplify security.

Figma Make—A prompt-to-code tool for making ideas real

Miro—The AI Innovation Workspace where teams discover, plan, and ship breakthrough products

Where to find Tomer Cohen:

• LinkedIn: https://www.linkedin.com/in/tomercohen

• Podcast: https://podcasts.apple.com/us/podcast/building-one-with-tomer-cohen/id1726672498

Referenced:

• How LinkedIn became interesting: The inside story | Tomer Cohen (CPO at LinkedIn): https://www.lennysnewsletter.com/p/how-linkedin-became-interesting-tomer-cohen

• LinkedIn: https://www.linkedin.com

• Cursor: https://cursor.com

• The rise of Cursor: The $300M ARR AI tool that engineers can’t stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell

• Devin: https://devin.ai

• Figma: https://www.figma.com

• Microsoft Copilot: https://copilot.microsoft.com

• Windsurf: https://windsurf.com

• Building a magical AI code editor used by over 1 million developers in four months: The untold story of Windsurf | Varun Mohan (co-founder and CEO): https://www.lennysnewsletter.com/p/the-untold-story-of-windsurf-varun-mohan

• Lovable: https://lovable.dev

• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (co-founder and CEO): https://www.lennysnewsletter.com/p/building-lovable-anton-osika

• APB program at LinkedIn: https://careers.linkedin.com/pathways-programs/entry-level/apb

• Naval Ravikant on X: https://x.com/naval

• One Song podcast: https://podcasts.apple.com/us/podcast/%D7%A9%D7%99%D7%A8-%D7%90%D7%97%D7%93-one-song/id1201883177

• Song Exploder podcast: https://songexploder.net

• Grok on Tesla: https://www.tesla.com/support/grok

• Reid Hoffman on X: https://x.com/reidhoffman

Recommended books:

• Why Nations Fail: The Origins of Power, Prosperity, and Poverty: https://www.amazon.com/Why-Nations-Fail-Origins-Prosperity/dp/0307719227

• Outlive: The Science and Art of Longevity: https://www.amazon.com/Outlive-Longevity-Peter-Attia-MD/dp/0593236599

• The Beginning of Infinity: Explanations That Transform the World: https://www.amazon.com/Beginning-Infinity-Explanations-Transform-World/dp/0143121359

Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

Lenny may be an investor in the companies discussed.

My takeaways from this conversation:

Gemini 3 vs. Claude Opus 4.5 vs. GPT-5.1 Codex: Which AI model is the best designer?

2025-12-03 20:03:30

I put three cutting-edge AI models to the test in a head-to-head design competition. Using the exact same prompt, I challenged Google’s Gemini 3, Anthropic’s Opus 4.5, and OpenAI’s Codex 5.1 to redesign my blog page, evaluating them on visual design quality, user experience improvements, and SEO optimization capabilities. One model produced a beautiful, polished, production-ready redesign. One was fine. And one completely whiffed. If you’re trying to figure out where each model fits in your workflow—design, planning, back-end, or something else—this episode will save you a lot of trial and error.

What you’ll learn:

How each AI model approaches the same design challenge differently
Why planning capabilities dramatically impact design quality
The specific visual and functional improvements each model made
Which model excels at front-end design versus back-end functionality
How to strategically choose the right AI model for different parts of your workflow
The importance of model-switching based on specific use cases

Blog design: https://www.chatprd.ai/blog

Listen or watch on YouTube, Spotify, or Apple Podcasts