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Claude Code + Obsidian: My family’s AI brain | Scott Farrar

2026-11-11 21:04:09

Scott Farrar is a math educator and parent who got tired of AI chats that drift and forget. So he built a household brain in Claude Code: a folder of Markdown files, viewed in Obsidian, that knows his appliances, warranties, insurance documents, and everything on his family’s to-do list. In this episode, Scott shows how he uses it to shop for car insurance, plan repairs, share the system with his wife, and put priority tasks and recent wins on a wall display. We also talk about AI and math learning, and why he wants AI to keep kids doing the thinking.

Listen or watch on YouTube, Spotify, or Apple Podcasts

What you’ll learn:

  1. Why he moved his home life from AI chat to Claude Code

  2. What Claude told him to photograph first

  3. How AI made him a sharper insurance shopper

  4. The to-do file he keeps coming back to

  5. How he and his wife share one household brain

  6. Why his wall display has a “recent wins” section

  7. How a flipped tutor gets kids to teach the AI


Brought to you by:

WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more

Jira Product Discovery—Prioritize with insights, build with confidence

In this episode, we cover:

(00:00) Teaser

(02:41) The problem (and solution)

(06:05) Demo: shopping for car insurance

(08:05) Building a household brain

(12:37) Type A vs. type B AI organization

(14:40) His shared household to-do list

(19:07) Household DAKboard wall display

(21:36) Does it actually change behavior?

(22:40) Household tasks to hand to AI

(26:00) AI, kids, and student agency

(31:16) When AI gets out of sync

(32:49) Where to find Scott

Tools referenced:

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

• Obsidian: https://obsidian.md/

• GitHub: https://github.com/

• DAKboard: https://dakboard.com/

Other references:

• I Built My Home’s AI Assistant (Scott’s write-up): https://sfxmath.com/work/homeai-household-knowledge-base/

• Algebuds: Student Tutors Chatbot: https://sfxmath.com/work/algebuds/

Where to find Scott Farrar:

Website: https://sfxmath.com/

LinkedIn: https://www.linkedin.com/in/farrarscott

Where to find Claire Vo:

ChatPRD: https://www.chatprd.ai/

Website: https://clairevo.com/

LinkedIn: https://www.linkedin.com/in/clairevo/

X: https://x.com/clairevo

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

State of the tech job market: late 2026

2026-11-10 23:04:03

👋 Hey there, I’m Lenny. Each week, I share deeply researched product, growth, and career advice. For more: Lenny’s Jobs | Lenny’s Podcast | Lennybot | How I AI | Become an AI-Native Builder and my other favorite AI/PM courses.

Subscribe now

P.S. Get a full free year of Cursor, Notion, Replit, Lovable, Wispr Flow, Linear, ElevenLabs, PostHog, Granola, Brain.fm, Waking Up, and more, by becoming an Insider subscriber (while supplies last). Learn more.


Welcome to my latest job market report, my second of 2026. Of the five reports I’ve done over the past few years, this one is the most surprising and interesting.

Here’s what we’re seeing right now:

  1. PMs seem to be winning in the AI era

  2. Engineering demand has stalled

  3. Design is at a record low

  4. Everybody now needs to AI

  5. Tech jobs are concentrating in the Bay Area

  6. Remote is at a record low

  7. The tech job market is growing fast, but mostly outside of software (gasp!)

This analysis is based on two proprietary datasets that I love working with: TrueUp, which powers Lenny’s Jobs and tracks global job openings at tech companies (over 9,000 companies). The second dataset comes from Live Data Technologies, which tracks job changes (hires, departures, and promotions) for 124 million professionals, and their hiring numbers below are specifically for the U.S. Looking at these together, we can triangulate common trends, and the differences between the datasets are themselves revealing. Thank you, Amit Taylor and Alex Hamilton, for sharing this amazing data with us. 🙏

Let’s get into it.

P.S. If you’re looking for a job, check out Lenny’s Jobs!


Takeaway 1: Product managers seem to be benefiting most in the AI era

There’s been a lot of talk about AI replacing product managers (“who needs ’em!”). But so far, the data is showing the exact opposite. There are more open PM roles than at any point in nearly four years, up 75% from the March 2023 low, and PM openings have grown faster than any other core tech role since the start of 2023 (+56%, compared with +43% for engineering).

When we look at hiring numbers vs. just job openings, the story gets more interesting. Even though open roles are growing, actual hiring for every core product role has been flat or in decline over the past few years (see takeaway 7 for which roles are now growing fastest). But PM hiring has held up the best (by far). And PM is the only one of the five core roles whose share of hiring grew (from 16% in 2021 to 21% today).

The fact that we’re seeing growth in PM openings (first set of charts) but a flat line and even a decline in hiring (second set of charts) tells me that there’s growing demand for PMs, but that landing great PMs is getting harder.

Takeaway 2: Demand for engineers is plateauing

For the first time in the history of this report, engineering job openings have stalled. Open engineering roles grew 29% through 2024, 15% through 2025, and just 2.5% this past year. There are fewer open eng roles at tech companies today than there were even this past March.

The hiring data shows the same slowdown. Companies in the U.S. hired about 113,000 software engineers over the past 12 months (May 2025 to April 2026)—less than half the 2022 peak (239,000). And the number has dropped every year since 2022.

Just like with PMs, engineering job openings are up while actual hiring is down (+44% vs. −17% since January 2024), so even as demand slows, landing great engineers is getting harder too.

Two bright spots for engineers: One, demand for tech recruiters is on an absolute tear. We’re hitting record highs: open recruiter roles are up nearly 300% since mid-2023. This may be a leading indicator of a reacceleration of eng hiring, which we’ll be watching closely.

Another bright spot is that in terms of absolute numbers, engineering is still the largest category of tech hiring, by far. Over 120,000 engineers were hired just in the U.S. in 2025. And there are still plenty of great engineering jobs out there. Over 65,000 to be exact.

One additional new trend to watch within the engineering function is the rise of the forward deployed engineer (FDE). FDE openings are exploding. Historically, there have been only a few dozen open FDE roles globally (mostly at Palantir), but openings started climbing in 2025 and are up 4.6x in the past year alone! There are currently around 1,500 open FDE roles. Note that this growth is likely a combination of increased demand for this job along with other job categories, like “sales engineer,” being rebranded as “FDE.” Either way, FDE is so hot right now.

Also, a telling trend: security engineering is one of the fastest-growing specialties, right behind FDEs. On the flip side, demand for mobile and front-end engineers has been nearly halved in the past year. That’s wild. I think the story here is the collapse of specialized/siloed engineering disciplines, with smaller eng teams having broader ownership (thanks to AI).

Takeaway 3: Demand for designers continues to hit record lows

Unfortunately for my designer friends, design roles continue to decline. There are only about 1,900 open product design roles1 at tech companies globally right now. Not that much higher than just open FDE roles. It’s the lowest we’ve seen since we started tracking, and down 28% from a year ago. 😥

Actual hiring data from Live Data Technologies tells the same story. U.S. companies hired about 12,600 product designers over the past 12 months, less than half as many as in 2022 (27,600), and the number has fallen every year since.

Even more telling, the ratio of open PM roles to open design roles is trending further and further toward PM. There are now 3.8 open PM roles for every open design role. This is up from 2.6 earlier this year and 1.9 in early 2023.

Hiring data from LDT shows the same trend, with slightly different numbers: U.S. employers hired about 2.9 PMs for every designer over the past 12 months, up from 1.9 in 2022.

I’m hopeful this turns around, as companies recognize that great design can be a huge differentiator and help their product stand out in an increasingly noisy (and AI-slop-y) market. Katie Dill’s talk about AI and design recently became my most-watched video of all time, so there’s hope.

Sadly, user research has been hit even harder than design. Only about 1,800 user researchers were hired in the U.S. over the past year, down 66% from 5,300 in 2022, the steepest drop of any role we looked at, and hiring fell another 22% from the year before. What hiring remains is concentrated at a few big companies. In 2025, Meta and Google alone made about one in eight of all U.S. user research hires, and so far in 2026, Google is the only company to have hired 50 or more. And there are currently only 108 open UXR jobs at tech companies globally.

My theory is that the increasing pace of product development is responsible. Just as there’s less time for the traditional design process, there’s also less time for (and interest in) the traditional user research process. For better or worse, teams are becoming more comfortable releasing products earlier to avoid falling behind, and learning and iterating post-launch vs. through user research. Also, better UXR tooling (e.g. Listen Labs, Simile) is allowing non-UXR people to do user research themselves. I wonder if UXR as a dedicated function is going extinct . . . 🫣

Takeaway 4: Everybody now needs to AI

When we did this report two years ago, the most mentioned skills in PM job descriptions were SQL, Jira, AWS, and Python. Today, “LLM” is the most mentioned skill in product manager job descriptions.

What’s more, many other AI terms are now some of the most frequently mentioned skills in PM job descriptions. “Claude” is the third most mentioned term, and Cursor, OpenAI, and MCP are in the top eight. SQL, meanwhile, is still holding strong, but as recent podcast guest Emmanuel Ameisen pointed out, we’ll never be better at SQL than AI ever again. So we’ll see how long that lasts. Also, “evals” is gaining momentum (in the top 10)—and I expect this number to grow.

For engineers, “Python” has been the most mentioned skill for years, and it’s still growing! Look at that inflection in early 2025. Three other trends stand out for engineers: (1) “LLM” just passed Java in eng job postings, (2) the general decline of Java over the past year, and (3) the durability of Kubernetes.

Essentially, Python and AI 📈, Java 📉.

For designers, Figma has been mogging every other skill for years. And narrative violation: demand for experience with Figma has actually grown over the past three years.

But as with every other role, AI is ascendant. “Claude” became the second most mentioned skill in designer JDs this spring (crossing CSS!). It’s notable that it’s Claude specifically, vs. “LLM” or ChatGPT. Anthropic seems to be winning the hearts and minds of designers. And Cursor has also edged past CSS. The times, they are a-changin’.

This suggests an answer to the question: If demand for Figma is growing, why has Figma’s stock fallen? Designers may not be dropping Figma, but for the first time in a long time, designers are increasingly reaching for other tools too. And design as a function isn’t growing.

Takeaway 5: Top tech jobs continue to concentrate in the Bay Area

Today, we’re at a record percentage of open tech roles being based in the Bay Area. That’s huge. 15% of all open roles at tech companies are now based in the Bay Area (about one in seven), and the number of open jobs in the Bay Area is up 43% from just a year ago!

The trend is even more pronounced for core product roles. One in four open PM and design roles is now in the Bay Area, and one in five engineering roles. All three are at record highs, and each has nearly doubled its share since 2022.

Takeaway 6: Remote roles continue to decline

The flip side of tech jobs concentrating in the Bay Area is that the number of remote roles continues to decline. Just 14% of open tech roles now offer a remote option, the lowest on record, down from 21% in late 2022.

Remote engineering roles are also at record lows, currently at 14%, and down from the 25% we saw in late 2022. Design is on the same path: 19% of open design roles are remote, down from 34%. PM, however, is the exception, holding steady at about one in five (21%) for the past two years, but still near record lows.

Put all this together, and sometime last year, we crossed a milestone where there are now more open PM/eng/design roles based in the Bay Area than remote roles globally. Remote led almost 2 to 1 in the other direction four years ago.

Takeaway 7: Overall, the tech job market is growing—but outside of software roles (gasp!)

I saved what might be the most interesting takeaway for last.

Read more

Claude Fable 5.2 review: fast, creative, and finally not annoying

2026-11-10 04:37:49

Anthropic just released Fable 5.2, their new frontier model, and I spent two days actually building things with it before recording this. I made an animated marketing video from a single tweet, assembled a pile of unboxed furniture using only blurry floor photos, and extended our CXO brand sprites into a full bug-defense game complete with a trailer. In this episode I walk through what impressed me, what fell short, and how I’m thinking about routing tasks between Fable 5.2 and Opus 5.5 going forward.

Listen or watch on YouTube, Spotify, or Apple Podcasts

What you’ll learn:

  1. What Anthropic launched with Fable 5.2 and Mythos 5.2, and when to reach for Fable instead of Opus 5.5

  2. My pros and cons after a couple of days of hands-on testing

  3. How Fable 5.2 turned a tweet and a brand book into an animated video that doesn’t look like slides

  4. The geometry test every other model failed: assembly instructions for flat-pack furniture with no manual

  5. How it handled a real re-architecture of ChatPRD’s product intelligence pipeline

  6. Why I still wouldn’t let it design a website on its own

  7. The 3D typewriter it built me, and how you can get access to the model


In this episode, we cover:

(00:00) Confessions of a Claude hater

(02:54) What Anthropic launched: Fable 5.2 and Mythos 5.2

(03:16) When to use Fable 5.2 vs. Opus 5.5

(03:30) Black holes, coding claims, and benchmarks

(04:40) Guardrails and anti-distillation safeguards

(05:12) My high-level pros and cons

(07:23) Video generation: turning a tweet into an animated film

(09:47) Animating the invader bots

(11:29) Flat-pack furniture with no instructions

(13:09) The bug factory game and its trailer

(15:16) Real engineering: re-architecting ChatPRD’s product intelligence pipeline

(16:57) Where it falls down: web design

(18:08) Claire’s typewriter

(23:02) How I AI bench preview

(23:34) How to get it: availability, fast mode, and Fable resets

(24:13) Final take

Tools referenced:

• Claude Fable 5.2: https://www.anthropic.com/claude-fable-and-mythos-5-2

• Claude Opus 5.5: https://www.anthropic.com/claude-opus-5-5

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

• HyperFrames: https://hyperframes.heygen.com/

• typed.page: https://typed.page/

Other references:

• Guillermo Rauch’s 3D record player: https://vinyl-gl.vercel.app/

• The bug factory game: https://www.cxo.dev/games/bug-factory

Where to find Claire Vo:

ChatPRD: https://www.chatprd.ai/

Website: https://clairevo.com/

LinkedIn: https://www.linkedin.com/in/clairevo/

X: https://x.com/clairevo

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

🎙️ How I AI: How this founder built a better Duolingo with Codex

2026-11-10 00:01:20

How this founder built a better Duolingo with Codex | William Imoh

Listen now on YouTube • Spotify • Apple Podcasts

Brought to you by:

  • WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more

  • Vanta—Automate compliance and simplify security

William Imoh is the founder of Hackmamba and the creator of Mural, an AI language tutor he built after a 1,000-day Duolingo streak still left him unable to hold a conversation in Norwegian. In this episode, he shows how he used Codex and GPT-Live to build native iOS and Android apps despite having no Swift or Kotlin experience, and explains how he designed Mural to teach through complete immersion. He also walks through the Lord of the Rings–themed team of Grok Bots that helps him run a 25-person company, from Gandalf as chief of staff to Legolas in marketing and Aragorn in sales.

Biggest takeaways:

  1. When agents write the code, the programming languages you know matter far less. William had never written Swift, but he wanted Mural to feel truly native, so Codex built it in Swift for iOS and Kotlin for Android. The technical stack followed the product vision, not the skills of the founder.

  2. Taste is often just design judgment expressed clearly. William told Codex to create a minimal, Apple-quality app that felt like autumn. When the first version came back in dark mode, he redirected it toward warm colors, gradients, and a lighter visual style.

  3. Product management experience translates directly into better prompting. William structures his requests as epics and user stories tied to specific user problems. That discipline gives the agent clearer goals and consistently produces stronger results.

  4. Real-time voice is finally good enough to build around, but it remains expensive. William says Mural would not have been possible without GPT-Live-1. A 30-minute session costs roughly $3 to $5, which is expensive for software but still cheaper than an on-demand human tutor.

  5. Agents feel more like colleagues when they have clear identities and jobs. William’s Grok Bot team includes Gandalf as chief of staff, Legolas in marketing, Elrond in engineering, and other Lord of the Rings characters across the business. The personas make each agent’s responsibilities easier to understand and delegate to.

  6. Useful context comes from access, not longer prompts. William connected his agents to Google Workspace, Linear, Notion, Pipedrive, QuickBooks, his calendar, and browser tools. He grants broad access by default, while keeping banking and customer data protected.

  7. The future may be custom systems of record with AI on top. William built Three Pipes, an internal HR tool that combines email, calendar, and meeting notes to track and rank candidates. Instead of adapting his workflow to generic software, he created the database his company actually needed.

  8. Better models reduce the need for elaborate skill libraries. Most of William’s skills became unnecessary as the underlying models improved. The few that survived encode durable expertise, including growth strategy, content strategy, and removing AI-style writing.

  9. When an agent stalls, restart with clearer instructions and add a reviewer. William begins a fresh session, breaks the task into steps, and asks the agent to inspect its own work. He also uses Grok Bot to review Cursor’s output.

Blog and detailed workflow walkthroughs from this episode:

William Imoh Built a Norwegian Tutor That Refuses to Speak English: https://www.chatprd.ai/how-i-ai/william-imoh-built-a-norwegian-tutor-that-refuses-to-speak-english
↳ Create an Immersive AI Language Tutor: https://www.chatprd.ai/how-i-ai/workflows/create-an-immersive-ai-language-tutor
↳ How to Manage Business Operations with Role-Based AI Agents: https://www.chatprd.ai/how-i-ai/workflows/how-to-manage-business-operations-with-role-based-ai-agents
↳ Build a Native Mobile App with AI and Clear Product Direction: https://www.chatprd.ai/how-i-ai/workflows/build-native-mobile-app-ai-product-direction


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.

How this founder built a better Duolingo with Codex | William Imoh

2026-11-09 21:04:17

William Imoh is the founder of Hackmamba, a developer marketing company, and the creator of Mural, a real-time voice app he built to learn Norwegian after moving from Dubai to Norway. He has a chemical engineering degree, taught himself to code, and spent four years as a product manager, but he had never written a line of Swift. In this episode, William shows how he used Codex and GPT-Live to build Mural natively for iOS and Android, then walks through the Lord of the Rings–themed Grok Bot “fellowship” that helps him run a team of about 25 as a solo founder.

Listen or watch on YouTube, Spotify, or Apple Podcasts

What you’ll learn:

  1. The design prompt that made Mural look nothing like any other language app

  2. Why 1,000 days of Duolingo left him unable to hold a conversation in Norwegian

  3. What GPT-Live-1 costs per session and the latency threshold that makes or breaks a voice tutor

  4. How he assigned every solo founder role to a Lord of the Rings character in Grok

  5. Why he gave his agents access to everything across 15 open tabs, except one thing

  6. What he still has to do himself after the models improved

  7. Why the fear that keeps him up isn’t replacement—it’s dependency


Brought to you by:

WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more

Vanta—Automate compliance and simplify security

In this episode, we cover:

(00:00) Teaser

(02:52) Introduction to William and his language learning app

(05:58) William’s tech background and how he started building

(08:07) The first prompt

(11:09) The importance of design language and articulation

(14:38) Live demo: a Norwegian conversation

(21:11) Having a growth mindset

(22:48) Why GPT Live works for this

(23:34) What it costs to run

(24:50) Running Hackmamba with agents

(26:58) Codex projects for organization

(28:47) His Lord of the Rings Grok Bot fellowship

(34:05) Recap

(34:54) Prompting strategies

(37:21) Where to find William

References:

• Mural on GitHub: https://github.com/Chuloo/mural

• Codex: https://chatgpt.com/codex

• GPT-Live: https://openai.com/index/introducing-gpt-live/

• Grok Bot: https://grokbot.com/

• Cursor: https://cursor.com/

• Boki: https://boki.io/

• Notion: https://www.notion.com/

Where to find William Imoh:

X: https://x.com/iChuloo

LinkedIn: https://www.linkedin.com/in/william-imoh

Hackmamba: https://hackmamba.io/

Hackmamba Podcast: https://hackmamba.io/eoc-podcast/

Mural: https://mural.chat/

Where to find Claire Vo:

ChatPRD: https://www.chatprd.ai/

Website: https://clairevo.com/

LinkedIn: https://www.linkedin.com/in/clairevo/

X: https://x.com/clairevo

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

Why PMs are suddenly valuable again | Tulsee Doshi (Head of Product, Gemini)

2026-11-08 21:31:32

Tulsee Doshi is head of product for Google’s frontier AI models, including Gemini and other multimodal models, such as Nano Banana, Genie, Veo, and Lyria.

We discuss:

  1. Why model development is not just engineering, but also like Snape’s potions class

  2. Google’s full-stack frontier AI strategy

  3. What PMs do inside a frontier AI lab

  4. Tulsee’s 60-20-20 framework for balancing what works now and what’s almost working

  5. How to write your first eval

  6. The rising value of great PMs


Brought to you by:

WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more

DX—Engineering intelligence for the AI era

Where to find Tulsee Doshi:

• X: https://x.com/tulseedoshi

• LinkedIn: linkedin.com/in/tulsee-doshi

Referenced:

• Nano Banana: https://aistudio.google.com/models/nano-banana

• Lyria: https://deepmind.google/models/lyria

• Gemma: https://deepmind.google/models/gemma

• Gemini Audio: https://deepmind.google/models/gemini-audio

• Severus Snape: https://en.wikipedia.org/wiki/Severus_Snape

• Emmanuel Ameisen on LinkedIn: https://www.linkedin.com/in/ameisen

• Gemini 4 Argon: our next era of frontier intelligence: https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon

• Inside OpenAI | Logan Kilpatrick (head of developer relations): https://www.lennysnewsletter.com/p/inside-openai-logan-kilpatrick-head

• Madhavi Sewak on LinkedIn: https://www.linkedin.com/in/madhavisewak

• Wiz: https://www.wiz.io

• Scan for Good: Using AI to discover and fix high-priority exposures across public services and critical infrastructure: https://www.wiz.io/blog/scan-for-good-critical-ai-exposures

• All-In: Trump’s Super Intelligence Summit, AI Safety Accord, GDP Beats, Midterm Predictions: https://www.youtube.com/v/ZJKs08oU1zg

• Google AI Studio: https://aistudio.google.com/onboarding

• Dots: https://chatgpt.com/features/dots

• Genie: https://deepmind.google/models/genie

• Veo: https://aistudio.google.com/models/veo

• Omni: https://gemini.google/overview/video-generation

• Flow: https://flow.google.com

• NotebookLM: https://notebook.google.com

• Antigravity: https://antigravity.google/

• Eli Collins on LinkedIn: linkedin.com/in/elidcollins

• Developing the Monk Skin Tone Scale: https://skintone.google/the-scale

• Michael Bernstein on LinkedIn: https://www.linkedin.com/in/mibernstein

• Expert Crowdsourcing with Flash Teams: https://hci.stanford.edu/publications/2014/flashteams/flashteams-uist2014.pdf

• The Hugging Face incident and the road ahead: https://openai.com/index/hugging-face-incident-and-the-road-ahead

• Head of Claude Code: What happens after coding is solved | Boris Cherny: https://www.lennysnewsletter.com/p/head-of-claude-code-what-happens

• Grok Bot: https://x.ai/bot

• Josh Woodward on LinkedIn: linkedin.com/in/joshwoodward

• Muse: https://ai.meta.com/muse

• Instinct: https://instinct.co

• Spark: https://gemini.google/overview/agent/spark

• How tech workers actually feel about AI in 2026 | Annual AI sentiment survey (Noam Segal): https://www.lennysnewsletter.com/p/how-tech-workers-actually-feel-about

• OpenAI’s Head of ChatGPT: We’re entering a new era of AI (again) | Tibo Sottiaux: https://www.lennysnewsletter.com/p/openais-head-of-chatgpt-were-entering

• Severance on Apple TV: https://tv.apple.com/us/show/severance/umc.cmc.1srk2goyh2q2zdxcx605w8vtx

• Wispr Flow: https://wisprflow.ai

• TEDxConcordia: Lenny Rachitsky—Losing Serendipity: https://www.youtube.com/watch?v=5p0VK_-BoJI

• Serendipity: https://www.imdb.com/title/tt0240890

• India Festival: https://www.icaportland.org

• Rambler voice input on Gboard: https://support.google.com/gboard/answer/17468539

Recommended books:

• Exhalation: https://www.amazon.com/Exhalation/dp/1529014492

• Creativity, Inc.: Overcoming the Unseen Forces That Stand in the Way of True Inspiration: https://www.amazon.com/Creativity-Inc-Expanded-Overcoming-Inspiration/dp/0593594649

• Throne of Glass: https://www.amazon.com/Throne-Glass-1/dp/1639730958

• A Court of Thorns and Roses: https://www.amazon.com/Court-Thorns-Roses-Sarah-Maas/dp/1635575567


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:

Read more