2026-04-06 23:03:07
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Al Chen is a field engineer at Galileo who works directly with enterprise customers asking highly technical questions. In this episode, Claire talks with Al about how he uses Claude Code to query Galileo’s entire codebase across 15 repositories, combine it with Confluence and Slack, and deliver accurate, real-time answers without relying on documentation or constantly pinging engineering. They cover why code is often a better source of truth than docs, how to turn customer questions into scalable knowledge, and how AI is changing what customer-facing teams can do.
Write a script to pull the latest code from all repos daily—and let Claude Code write it. Al uses a 16-line script (written entirely by Claude Code) that pulls the latest main branch from all 15 repositories every morning. This ensures that he’s always querying current code instead of outdated information, solving the “docs are stale” problem that plagues most technical support teams.
Maintain a “customer quirks” page to make AI answers customer-specific. Al keeps a Confluence page listing each enterprise customer’s unique deployment requirements: how they handle secrets, namespaces, encryption, air-gapped environments. His Claude Code custom commands reference this page first, generating highly tailored deployment instructions instead of generic answers anyone could Google.
Combine code repositories with Confluence MCP for maximum context. Al’s custom Claude Code commands first check Confluence for deployment documentation, then query the code repositories if needed. This multi-source approach means Claude Code pulls from official docs, tribal knowledge, and actual implementation—delivering answers no single source could provide.
Your code is better documentation than your docs. Al realized public documentation couldn’t answer his enterprise customers’ detailed technical questions. By pulling all 15 of Galileo’s repositories into VS Code and querying them with Claude Code, he can now answer questions about how services cascade together, how features actually work, and deployment specifics that aren’t captured anywhere else.
Turn Slack support threads into knowledge base articles automatically. Using Pylon, Al converts detailed customer conversations into abstracted help articles with one click. These articles are more in-depth and current than official docs because they’re based on real customer questions and don’t require the overhead of PR reviews and approval processes.
Reduce engineering interruptions to near-zero by self-serving answers. Before this system, Al constantly pinged engineering with customer questions, creating frustration on both sides. Now he queries the code directly, only reaching out to validate answers or when Claude Code can’t find information (usually because it exists only in meeting notes or hallway conversations).
The human value-add is making AI answers sound human, and knowing when to validate. Al doesn’t blindly copy-paste Claude Code responses. He proofreads everything, removes telltale AI phrases like “in summary,” condenses verbose answers to what customers actually need, and validates complex technical answers with engineering when he doesn’t fully understand the implementation.
Compete on customer experience, not just product velocity. Everyone uses AI to ship faster products. Al uses AI to show up differently in customer relationships—delivering custom deployment documentation that accounts for each customer’s specific security requirements and infrastructure constraints. This differentiation in service quality is harder to replicate than product features.
How Al Chen Uses Claude Code and 15 Repos to Answer Any Customer Question: https://www.chatprd.ai/how-i-ai/claude-code-and-repos-to-answer-any-customer-question
Automatically Create a Knowledge Base from Slack Support Threads: https://www.chatprd.ai/how-i-ai/workflows/automatically-create-a-knowledge-base-from-slack-support-threads
How to Use AI to Answer Customer Questions from Your Entire Codebase: https://www.chatprd.ai/how-i-ai/workflows/how-to-use-ai-to-answer-customer-questions-from-your-entire-codebase
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
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2026-04-06 20:03:35
Al Chen is a field engineer at Galileo, an observability platform for AI applications, where he works on the front lines with enterprise customers asking highly technical questions. Despite never having held an engineering role, Al has built a system using Claude Code to query Galileo’s 15 separate repositories, combine that with Confluence documentation and customer-specific quirks, and deliver hyper-personalized answers that would otherwise require constant engineering support.
Listen or watch on YouTube, Spotify, or Apple Podcasts
How to use Claude Code to query multiple repositories simultaneously for customer support
Why code is often a better source of truth than documentation
How to combine repository context with Confluence and Slack using MCPs
The “customer quirks” system that creates hyper-personalized deployment guides
How to build virtuous loops that turn single customer questions into scalable knowledge
Why information organization matters less in the AI era
A simple 16-line script (written by Claude Code) that pulls the latest main branch across all your repositories to keep your context current
How to reduce engineering interruptions to near-zero by empowering customer-facing teams to query the codebase directly
Orkes—The enterprise platform for reliable applications and agentic workflows
Tines—Start building intelligent workflows today
(00:00) Introduction to Al Chen
(02:50) The problem: documentation wasn’t enough
(04:23) Pulling 15 repos into VS Code
(06:03) How Claude Code queries the entire codebase
(08:00) Why current code beats documentation
(08:31) The pull script that keeps everything updated
(09:54) Opening projects at the multi-repo level
(11:40) Live demo: answering deployment questions
(13:25) The customer quirks system
(15:00) Living in chaos: why organization matters less now
(17:03) Competing on customer experience, not just product
(18:20) Should customers be able to query the code directly?
(20:05) Where humans still add value
(25:46) Using AI for reactive Slack support
(29:16) The “and then” workflow discovery
(32:07) Scaling processes across the team
(34:07) Lightning round and final thoughts
• Claude Code: https://claude.ai/code
• VS Code: https://code.visualstudio.com/
• Pylon: https://usepylon.com/
• Confluence: https://www.atlassian.com/software/confluence
• Slack: https://slack.com/
• Kubernetes: https://kubernetes.io/
• Stack Overflow: https://stackoverflow.com/
• Intercom: https://www.intercom.com/
LinkedIn: https://www.linkedin.com/in/thealchen/
Company: https://www.rungalileo.io
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].
2026-04-05 20:31:45
Amol Avasare is Head of Growth at Anthropic, which is going through the most unprecedented growth trajectory in history—scaling from $1 billion to over $19 billion in ARR in just 14 months. Previously, Amol worked on the growth teams at Mercury and MasterClass. Before that he was a founder, and he cold emailed his way into the Anthropic role when no job listing existed. Most remarkably, he overcame a traumatic brain injury from a Muay Thai match that meant he couldn't work for nearly a year.
Listen on YouTube, Spotify, and Apple Podcasts
How Amol landed his role by cold emailing Anthropic’s CPO Mike Krieger
How Anthropic is automating growth experiments with Claude (their internal tool called “CASH”)
Why the ratio of PMs to engineers might need to flip (more PMs than engineers) as AI makes engineers exponentially more productive
Why activation is the single highest-leverage growth problem in AI
Why Anthropic indexes 70/30 toward big bets (the opposite of most growth teams)
How he uses Cowork to detect team misalignment in Slack
How the company’s focus on AI coding created a research flywheel that accelerated their models
WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs
Vanta—Automate compliance, manage risk, and accelerate trust with AI
• X: https://x.com/TheAmolAvasare
• LinkedIn: https://www.linkedin.com/in/amolavasare
• How a traumatic brain injury made me a better PM—and person: https://www.lennysnewsletter.com/p/how-a-traumatic-brain-injury-made
• Anthropic: https://www.anthropic.com
• Snowflake: https://www.snowflake.com
• Canva: https://www.canva.com
• Palantir: https://www.palantir.com
• Atlassian: https://www.atlassian.com
• Anthropic’s CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next
• Claude Code: https://code.claude.com
• Dario Amodei on X: https://x.com/DarioAmodei
• Facebook: https://www.facebook.com
• Uber: https://www.uber.com
• DoorDash: https://www.doordash.com
• Anthropic co-founder on quitting OpenAI, AGI predictions, $100M talent wars, 20% unemployment, and the nightmare scenarios keeping him up at night | Ben Mann: https://www.lennysnewsletter.com/p/anthropic-co-founder-benjamin-mann
• Mercury: https://mercury.com
• MasterClass: https://www.masterclass.com
• Calm: https://www.calm.com
• Alexey Komissarouk’s website: https://alexeymk.com
• Alexey’s “Mastering Growth Engineering” course: https://www.reforge.com/courses/mastering-growth-engineering
• Claude Cowork: https://www.anthropic.com/product/claude-cowork
• Making an impact through authenticity and curiosity | Ami Vora (CPO at Faire, ex-WhatsApp, FB, IG): https://www.lennysnewsletter.com/p/authenticity-and-curiosity-ami-vora
• Ami Vora’s Substack: https://amivora.substack.com
• Benepass: https://getbenepass.com
• Brex: https://www.brex.com
• Granola: https://www.granola.ai
• The design process is dead. Here’s what’s replacing it. | Jenny Wen (head of design at Claude): https://www.lennysnewsletter.com/p/the-design-process-is-dead
• Marc Andreessen: The real AI boom hasn’t even started yet: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom
• John Egan’s website: https://jwegan.com
• Workday: https://www.workday.com
• Figma: https://www.figma.com
• Spirit Rock: https://www.spiritrock.org
• This will make you a better decision-maker | Annie Duke (author of “Thinking in Bets” and “Quit,” former pro poker player): https://www.lennysnewsletter.com/p/making-better-decisions-annie-duke
• Marty Supreme: https://www.imdb.com/title/tt32916440
• Maruhachi Shinsui Maruhachi Pro: https://www.amazon.co.jp/-/en/Maruhachi-Shinsui-Feather-Pillow-Blissful/dp/B081DNVD3K
• The Joy of Living: Unlocking the Secret and Science of Happiness: https://www.amazon.com/Joy-Living-Unlocking-Science-Happiness/dp/0307347311
• Awareness: Conversations with the Masters: https://www.amazon.com/Awareness-Opportunities-Reality-Anthony-Mello/dp/0385249373
• Thinking in Bets: Making Smarter Decisions When You Don’t Have All the Facts: https://www.amazon.com/Thinking-Bets-Making-Smarter-Decisions/dp/0735216371
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.
2026-04-05 06:02:36
👋 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.
2026-04-02 20:32:28
Simon Willison is a prolific independent software developer, a blogger, and one of the most visible and trusted voices on the impact AI is having on builders. He co-created Django, the web framework that powers Instagram, Pinterest, and tens of thousands of other websites. He coined the term “prompt injection,” popularized the terms “AI slop” and “agentic engineering,” and has built over 100 open source projects, including Datasette, a data analysis tool used by investigative journalists worldwide. What makes Simon unique is that he’s made the leap from traditional software engineering to AI-native development more fully and visibly than almost anyone—and he’s been documenting everything he learns in real time on his blog, SimonWillison.net.
Listen on YouTube, Spotify, and Apple Podcasts
Why November 2025 was the inflection point when AI coding agents crossed from “mostly works” to “actually works”
How Simon writes 95% of his code from his phone now and why he’s mentally exhausted by 11 a.m.
Why mid-career engineers (not juniors) are most at risk right now
The three agentic engineering patterns Simon uses daily (red/green TDD, templates, hoarding)
The next leap: the “dark factory” pattern where nobody writes or reviews code and AI does its own QA
Why prompt injection is an unsolved security problem and the “lethal trifecta” that will likely lead to an AI Challenger disaster
Why the pelican riding a bicycle became the unofficial benchmark for AI model quality
WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs
Vanta—automate compliance, manage risk, and accelerate trust with AI
• X: https://x.com/simonw
• LinkedIn: https://www.linkedin.com/in/simonwillison
• Website: https://simonwillison.net
• Agentic Engineering Patterns: https://simonwillison.net/guides/agentic-engineering-patterns
• It genuinely feels to me like GPT-5.2 and Opus 4.5 in November represent an inflection point: https://x.com/simonw/status/2007904766756880848
• Claude Code: https://code.claude.com
• Codex: https://chatgpt.com/codex
• Head of Claude Code: What happens after coding is solved | Boris Cherny: https://www.lennysnewsletter.com/p/head-of-claude-code-what-happens
• There’s a new kind of coding I call “vibe coding”: https://x.com/karpathy/status/1886192184808149383
• Firefox: https://www.firefox.com
• Naming expert shares the process behind creating billion-dollar brand names like Azure, Vercel, Windsurf, Sonos, Blackberry, and Impossible Burger | David Placek (Lexicon Branding): https://www.lennysnewsletter.com/p/naming-expert-david-placek
• Windsurf: https://windsurf.com
• Thoughtworks: https://www.thoughtworks.com
• Cloudflare: https://www.cloudflare.com
• Shopify: https://www.shopify.com
• Jensen Huang: Nvidia’s Future, Physical AI, Rise of the Agent, Inference Explosion, AI PR Crisis: https://www.youtube.com/watch?v=gwW8GKwHB3I
• Inside Linear: Building with taste, craft, and focus | Karri Saarinen (co-founder, designer, CEO): https://www.lennysnewsletter.com/p/inside-linear-building-with-taste
• Hacker News: https://news.ycombinator.com
• Dario Amodei on X: https://x.com/DarioAmodei
• Lenny’s post on the job market in tech: https://www.lennysnewsletter.com/p/state-of-the-product-job-market-in-ee9
• Claude app: https://apps.apple.com/us/app/claude-by-anthropic/id6473753684
• Gemini: https://gemini.google.com/app
• Import and export your memory from Claude: https://support.claude.com/en/articles/12123587-import-and-export-your-memory-from-claude
• Wispr Flow: https://wisprflow.ai
• The last six months in LLMs, illustrated by pelicans on bicycles: https://simonwillison.net/2025/Jun/6/six-months-in-llms
• Gemini 3.1 Pro: https://simonwillison.net/2026/Feb/19/gemini-31-pro
• Redis: https://redis.io
• Node.js: https://nodejs.org
• Simon’s tools repository: https://github.com/simonw/tools
• Simon’s research repository: https://github.com/simonw/research
• Tesseract: https://github.com/tesseract-ocr/tesseract
• TDD: https://martinfowler.com/bliki/TestDrivenDevelopment.html
• Red/green TDD: https://simonwillison.net/guides/agentic-engineering-patterns/red-green-tdd
• The lethal trifecta for AI agents: private data, untrusted content, and external communication: https://simonwillison.net/2025/Jun/16/the-lethal-trifecta
• Prompt injection: https://simonwillison.net/series/prompt-injection
• The coming AI security crisis (and what to do about it) | Sander Schulhoff: https://www.lennysnewsletter.com/p/the-coming-ai-security-crisis
• AI prompt engineering in 2025: What works and what doesn’t | Sander Schulhoff (Learn Prompting, HackAPrompt): https://www.lennysnewsletter.com/p/ai-prompt-engineering-in-2025-sander-schulhoff
• The Challenger Disaster: Normalisation of Deviance: https://psychsafety.com/normalisation-of-deviance
• Thanksgiving Day Chart—Behind The Net: https://www.blackswanreport.com/blog/2009/11/thanksgiving-day%C2%A0chart-behind-the-net
• CaMeL offers a promising new direction for mitigating prompt injection attacks: https://simonwillison.net/2025/Apr/11/camel
• OpenClaw: https://openclaw.ai
• Introducing ai.com—Your Private, Personal AI Agent: https://www.youtube.com/watch?v=n7I-D4YXbzg
• Tamagotchi: https://en.wikipedia.org/wiki/Tamagotchi
• NanoClaw: https://nanoclaw.dev
• Spider-Man 2: https://www.imdb.com/title/tt0316654
• Alfred Molina: https://en.wikipedia.org/wiki/Alfred_Molina
• AI for Data Journalism: demonstrating what we can do with this stuff right now: https://simonwillison.net/2024/Apr/17/ai-for-data-journalism
• Kākāpō: https://en.wikipedia.org/wiki/K%C4%81k%C4%81p%C5%8D
• Kākāpō Cam: Rakiura the kākāpō—2026 nest: https://www.youtube.com/live/BfGL7A2YgUY
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.
2026-04-01 22:11:12
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Claire Vo went from public OpenClaw skeptic to running nine dedicated AI agents that manage her businesses, write code, close sales deals, and make sure she gets to her kids' basketball games on time. In this episode, she shares her complete power-user's guide to OpenClaw—covering everything from setup and key concepts to practical workflows and building your own team of agents.
In this episode, you’ll learn:
What OpenClaw is and why it’s more autonomous and powerful than other AI tools
How to choose the right setup: Mac Mini, VPS, or a hosted option
Six ready-to-copy workflows you can start using immediately
How to run multiple agents with specific roles (Claire’s full 9-agent setup)
The best tools and integrations to connect your agents to the real world
Key security considerations and how to think about risk
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