Forward Deployed, Episode 2: Claude Code Skills and the Progressive Disclosure Problem

Forward Deployed, Episode 5: Aligning Agents

Welcome to episode five of Forward Deployed. Noah sits down with Taylor Pearson [https://taylorpearson.me/] to continue the conversation about how we align agents, and why the best models may come from outside traditional software engineering. Taylor brings a background that cuts across history, internet businesses, The End of Jobs [https://www.amazon.com/End-Jobs-Meaning-9-5-ebook/dp/B010L8SYRG], risk parity investing, complexity science, and recent deep work with Claude Code [https://www.alephic.com/writing/the-magic-of-claude-code]. The conversation moves from firms and transaction costs to Toyota, military doctrine, memory, skills, and the problem of getting agents to work toward the right goal. Key Topics Covered * Aligning agents: Why the episode starts with the question of how to align agents and what engineering can borrow from organization design, markets, and systems theory * Taylor’s path: From history, SEO, ecommerce, and The End of Jobs to finance, risk parity, complexity science, and AI work * Claude Code as a turning point: Why agentic command-line systems felt more transformative for Taylor than chatbot workflows * Historical analogies for AI: Electricity, factory design, Toyota, and the need for a new pattern language for agentic work * Companies as agentic systems: Why firms may be a more useful model than deterministic software systems for coordinating agents * Junior employees and agents: The familiar failure mode where the work is done well but aimed at the wrong problem * Bottlenecks and specs: Why fixing pull requests is not the whole game, and why the bottleneck may move upstream into briefs, specs, and coordination * Pace layers and skills: Best practices, project architecture, plans, code, and how different layers of a system move at different speeds * Memory and context: How skills, files, and externalized memory help agents carry useful context between sessions and systems * Jobs and firm boundaries: How AI changes the calculus around what belongs inside a company, what gets outsourced, and which roles collapse together * Writing, investing, and complex systems: Why some domains resist fixed best practices because everyone adapts to the same patterns Timestamps Note: timestamps are approximate * 00:00 - Introduction: Taylor Pearson, complexity theory, organizations, and aligning agents * 01:15 - Taylor’s path from history to SEO, ecommerce, The End of Jobs, finance, and AI * 03:30 - The GFC, The Black Swan, markets, systems thinking, and transaction costs * 07:00 - Claude Code, Codex, and the agentic workflow shift * 13:45 - Historical analogies for AI, electricity, factories, and pattern languages * 18:00 - Why companies may be the better model for agentic systems than software systems * 20:45 - Organization metaphors, the Toyota Production System, and agents as junior employees * 24:00 - Bottlenecks, specs, briefs, and the coordination work before code * 27:05 - Mission alignment, pace layers, skills, best practices, and architecture * 32:20 - Cynefin, best practices, good practices, and emergent practices * 34:50 - Boyd’s OODA loop, Schwerpunkt, and shared objectives * 39:05 - Memory, role boundaries, and what changes inside and outside the firm * 43:25 - Externalized memory, skills, and context across systems * 46:25 - Generalization, AI writing, de-slopping, and verifiable rewards * 49:15 - Writing, investing, complex systems, and the Maginot Line problem * 51:20 - Closing thoughts Links & References Core References * Taylor Pearson [https://taylorpearson.me/] - Guest on this episode * The End of Jobs [https://www.amazon.com/End-Jobs-Meaning-9-5/dp/1619613352] - Taylor’s book on work, technology, and entrepreneurship * The Black Swan [https://www.penguinrandomhouse.com/books/541852/the-black-swan-second-edition-by-nassim-nicholas-taleb/] by Nassim Nicholas Taleb [https://www.penguinrandomhouse.com/books/541852/the-black-swan-second-edition-by-nassim-nicholas-taleb/] - The GFC-era entry point Taylor mentions * Thinking in Systems [https://www.amazon.com/Thinking-Systems-Donella-H-Meadows/dp/1603580557] by Donella Meadows [https://www.amazon.com/Thinking-Systems-Donella-H-Meadows/dp/1603580557] - The systems thinking reference in the conversation * Images of Organization [https://www.amazon.com/Images-Organization-Gareth-Morgan/dp/1412939798] by Gareth Morgan [https://www.amazon.com/Images-Organization-Gareth-Morgan/dp/1412939798] - The organization metaphor book Taylor recommends * The Goal [https://www.amazon.com/Goal-Process-Ongoing-Improvement/dp/0884271951] by Eliyahu Goldratt [https://www.amazon.com/Goal-Process-Ongoing-Improvement/dp/0884271951] - The bottleneck and theory-of-constraints reference Noah returns to * The Phoenix Project [https://itrevolution.com/product/the-phoenix-project/] - The IT follow-up to The Goal Concepts & Frameworks * Ronald Coase [https://en.wikipedia.org/wiki/Ronald_Coase] and transaction cost economics [https://en.wikipedia.org/wiki/Transaction_cost] - Why work happens inside or outside firms * Toyota Production System [https://en.wikipedia.org/wiki/Toyota_Production_System] - The people-and-machines operating system discussed in the episode * A Pattern Language [https://en.wikipedia.org/wiki/A_Pattern_Language] - Christopher Alexander’s pattern-language idea applied to agentic work * Stuart Brand’s pace layers [https://jods.mitpress.mit.edu/pub/issue3-brand/release/2] - The model Noah uses for best practices, architecture, plans, and code * Cynefin framework [https://thecynefin.co/about-us/about-cynefin-framework/] - Simple, complicated, complex, and chaotic work domains * John Boyd’s OODA loop [https://en.wikipedia.org/wiki/OODA_loop] - Decision-making and shared objective reference * Schwerpunkt [https://en.wikipedia.org/wiki/Schwerpunkt] - The point-of-effort concept Taylor connects to agent alignment * Systemantics [https://en.wikipedia.org/wiki/Systemantics] by John Gall [https://en.wikipedia.org/wiki/Systemantics] - The Maginot Line and previous-war problem discussed near the end Tools & Platforms * Claudesidian [https://github.com/heyitsnoah/claudesidian] - Noah’s Obsidian/Claude framework * OpenAI Codex [https://openai.com/codex/] - The competing agentic coding interface discussed in the episode * Obsidian [https://obsidian.md/] - Note-taking and memory system context for agent workflows * Alephic [https://www.alephic.com/] - Noah’s AI consulting company Previous Episodes * Episode 1: The Bitter Lesson [https://www.forwarddeployed.com/p/forward-deployed-episode-1-the-bitter] * Episode 2: Claude Code Skills and the Progressive Disclosure Problem [https://www.forwarddeployed.com/p/forward-deployed-episode-2-claude] * Episode 3: Context Engineering [https://www.forwarddeployed.com/p/forward-deployed-episode-3-context] * Episode 4: The Special Forces Model [https://www.forwarddeployed.com/p/forward-deployed-episode-4-the-special] About the Hosts Noah Brier is co-founder of Alephic [https://www.alephic.com/], an AI consulting company helping brands and enterprises build custom AI systems. Taylor Pearson is an author and investor whose work spans entrepreneurship, markets, complexity theory, and AI. He is the author of The End of Jobs [https://www.amazon.com/End-Jobs-Meaning-9-5-ebook/dp/B010L8SYRG]. Connect with the Hosts * Noah Brier: LinkedIn [https://www.linkedin.com/in/noahbrier/] | X/Twitter [https://twitter.com/heyitsnoah] * Taylor Pearson: Website [https://taylorpearson.me/] | X/Twitter [http://twitter.com/TaylorPearsonMe] * Alephic: alephic.com [https://www.alephic.com/] Subscribe for weekly episodes exploring how AI is actually being deployed in the real world. Newsletter: Sign up for updates at forwarddeployed.com [https://forwarddeployed.com/] This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.forwarddeployed.com [https://www.forwarddeployed.com?utm_medium=podcast&utm_campaign=CTA_1]

Forward Deployed, Episode 4: The Special Forces Model

Welcome to episode four of Forward Deployed. Noah sits down with Chris Papasadero to explore the deep parallels between Special Forces operations, enterprise software deployment, and creative direction—and what all of it means for building AI agents that actually work in the real world. Key Topics Covered * The Forward Deployed Engineer (FDE) model: How Palantir’s approach to embedding technical experts mirrors Special Forces doctrine * Force multiplication: Why Green Berets are designed to produce outsized output from minimal input — and what that means for AI agents * Comfort with ambiguity: The Special Forces selection pipeline, the Star Course, and why a 2% selection rate tests for the right traits * Cultural embedding: Why Palantir contractors in Afghanistan succeeded by understanding the operational environment, not just the software * Organizational structure and bureaucracy: NCO-led detachments, pushing planning to the lowest level, and the OSS Simple Sabotage Field Manual * Three layers of alignment: Shared cultural values, doctrine, and experience — Chris’s framework for aligning both teams and AI agents * Second and third-order effects: Why software engineering (like warfare) is a creative pursuit, not a six sigma factory process * Showrunners and creative direction: The role of holding both operational and creative vision across a large, autonomous team * Warhol Factory vs. Ford Factory: Why creative production is a better analogy for agentic systems than industrial automation Timestamps Note: timestamps are approximate * 00:00 - Introduction and the origin of “Forward Deployed” * 01:30 - Chris’s background: Special Forces and Palantir * 05:00 - The Forward Deployed Engineer (FDE) model at Palantir * 08:30 - Cultural embedding: Why Palantir worked in Afghanistan * 12:00 - Special Forces as force multipliers * 15:00 - The selection pipeline and comfort with ambiguity * 18:30 - The Star Course: Navigating alone without external guidance * 21:00 - Maintaining the big picture in the fog of war * 25:00 - Organizational structure: NCO-led detachments and decentralized planning * 29:00 - Planning for failure: Incorporating contingencies from the start * 33:00 - The Simple Sabotage Field Manual and organizational bureaucracy * 37:00 - Applying military frameworks to AI agents * 41:00 - Three layers of alignment: Values, doctrine, and experience * 45:00 - Second and third-order effect analysis * 49:00 - Software engineering as a creative pursuit * 52:00 - Showrunners, dailies, and creative direction * 56:00 - The Warhol Factory model for agentic systems * 59:00 - Wrap-up and key takeaways Links & References Core References * Palantir — Forward Deployed Engineering [https://blog.palantir.com/a-day-in-the-life-of-a-palantir-forward-deployed-software-engineer-45ef2de257b1] * OSS Simple Sabotage Field Manual [https://www.cia.gov/stories/story/the-art-of-simple-sabotage/] * Forward Deployed Episode 1: The Bitter Lesson [https://www.forwarddeployed.com/p/forward-deployed-episode-1-the-bitter] * Forward Deployed Episode 2: Claude Code Skills [https://www.forwarddeployed.com/p/forward-deployed-episode-2-claude] * Forward Deployed Episode 3: Context Engineering [https://www.forwarddeployed.com/p/forward-deployed-episode-3-context] Concepts & Frameworks * Special Forces (Green Berets) [https://en.wikipedia.org/wiki/United_States_Army_Special_Forces] — Force Multiplication doctrine * The Star Course — Special Forces land navigation assessment * NCO-led detachments — Decentralized command and planning * Andy Warhol’s Factory — Creative production model Related Content * The Bitter Lesson [http://www.incompleteideas.net/IncIdeas/BitterLesson.html] by Richard Sutton — General methods that leverage computation * Previous episodes of Forward Deployed [https://www.forwarddeployed.com/] About the Hosts Noah Brier is co-founder of Alephic [https://alephic.com], an AI consulting company helping brands build custom AI systems. He writes about AI strategy and implementation. Chris Papasadero is this episode’s guest, bringing deep experience at the intersection of Special Forces operations, defense technology, and enterprise software deployment. Connect with the Hosts Noah Brier: LinkedIn [https://linkedin.com/in/noahbrier] | X/Twitter [https://twitter.com/noahbrier] Subscribe for weekly episodes exploring how AI is actually being deployed in the real world. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.forwarddeployed.com [https://www.forwarddeployed.com?utm_medium=podcast&utm_campaign=CTA_1]

Forward Deployed, Episode 3: Context Engineering

Welcome to episode three of Forward Deployed. Noah and Lance dive deep into context engineering—the art and science of filling context windows with just the right information for agents to take the next action. Key Topics Covered - Context engineering: Why Karpathy’s term matters more than prompt engineering for agents - Three core techniques: Reducing context, isolating context, and offloading context to file systems - Skills vs MCPs: Why progressive disclosure beats loading everything into context - Claude Diary: Building agent memory through reflection and evolving CLAUDE.md - Why subagents should isolate context, not anthropomorphize org charts - Production patterns from Manus: Compaction, file system offloading, and sandbox architecture - The convergence of agent primitives: Read, write, reduce, and recombine - Why treating agents like humans works: Dual-use tools and new coworker onboarding Timestamps - 00:10 - What is context engineering and why should we care? - 00:37 - Karpathy’s definition: Filling context windows with just the right information - 01:15 - Context engineering vs prompt engineering: Tools bring context too - 02:27 - Three buckets: Reducing, isolating, and offloading context - 04:30 - Dynamic context loading: Skills as just-in-time context - 06:38 - Skills as context offloading: Progressive disclosure of tools - 09:15 - Sandboxes beyond Manus and Claude Code: Application integration patterns - 12:12 - Context isolation through subagents: Not org charts - 14:41 - Using isolation as a feature: Test-driven development with blank slate agents - 16:33 - Real-world subagent challenges: Shared file systems and context bottlenecks - 20:47 - Claude Diary: Automatic memory through session reflection - 22:53 - CLAUDE.md bloat: Reducing unnecessary words like Strunk and White - 28:06 - Dual-use tools: Why Claude Code uses bash, grep, and human-readable commands - 31:02 - Skills discovery problems: From manual search to automated finding - 34:22 - Agent primitives: Read, write, reduce, and creative recombination - 36:32 - Tool search and action space design: How to find the right function - 40:50 - Hooks as determinism: Injecting code into agent loops - 41:41 - Skills everywhere: ChatGPT’s progressive disclosure discovery - 43:12 - Nano Banana: Text on images unlocks new agentic workflows Links & References Core References * 🔗 Karpathy tweet on context engineering [https://twitter.com/karpathy/status/17932426212001755713] * 🎙️ Manus webinar on context engineering [https://www.youtube.com/watch?v=6_BcCthVvb8&utm_source=chatgpt.com] * 📄 Cognition blog post on multi-agents [https://cognition.ai/blog/dont-build-multi-agents Cognition] * 📄 Simon Willison on skills and file systems [https://simonwillison.net/2025/Jun/27/context-engineering/ Simon Willison’s Weblog] * 🔗 Anthropic Model Context Protocol announcement [https://www.anthropic.com/news/model-context-protocol?utm_source=chatgpt.com] * 🔗 GitHub MCP docs (Anthropic [https://github.com/barefootford/anthropic-mcp-docs GitHub]) Technical Resources * 🔗 Claude Code hooks documentation [https://docs.claude.com/en/docs/claude-code/hooks] * 🔗 Anthropic frontend design skills example [https://github.com/anthropics/claude-skills-examples] * 📄 Obra magic skills repository [https://github.com/obra-ai/magic-skills-repo] * 🔗 Vercel sandboxes docs [https://vercel.com/docs/concepts/edge-functions/sandbox-environment] Tools & Frameworks * 🔗 LangChain Docs (Python) [https://python.langchain.com/en/latest/index.html] * 🔗 Cerebras Systems – Technology [https://cerebras.ai/technology] * 🔗 DeepMind Nano Banana info [https://deepmind.google/blog/article/introducing-nano-banana] * 🔗 ChatGPT Skills directory [https://platform.openai.com/docs/guides/chat/skills] Related Content - 🎙️ Karpathy on Dwarkesh Podcast [https://www.dwarkesh.com/p/karpathy] - Discussion of AI development principles - 📚 The Elements of Style by Strunk and White [https://en.wikipedia.org/wiki/The_Elements_of_Style] - “Reduce unnecessary words” as principle for CLAUDE.md - 📄 The Bitter Lesson by Richard Sutton [https://www.cs.utexas.edu/~eunsol/courses/data/bitter_lesson.pdf] - General methods that leverage computation About the Hosts Noah Brier is co-founder of Alephic [https://www.alephic.com/], an AI consulting company helping brands build custom AI systems. He writes about AI strategy and implementation. Lance Martin is a founding engineer at LangChain [https://www.langchain.com/], where he works on developer tools for building AI applications. Connect with the Hosts - Noah Brier: LinkedIn [https://www.linkedin.com/in/noahbrier] | X/Twitter [https://twitter.com/heyitsnoah] - Lance Martin: LinkedIn [https://www.linkedin.com/in/lance-martin] | X/Twitter [https://twitter.com/RLanceMartin] * * * Subscribe for weekly episodes exploring how AI is actually being deployed in the real world. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.forwarddeployed.com [https://www.forwarddeployed.com?utm_medium=podcast&utm_campaign=CTA_1]

Forward Deployed, Episode 2: Claude Code Skills and the Progressive Disclosure Problem

Welcome back to episode 2 of Forward Deployed. This week Noah and Lance dive deep into Claude Code skills, a deceptively simple feature that’s changing how we think about building AI agents. Noah walks through the Alephic CLI he’s been building and reveals a wild hook-based routing system using Cerebras at 3,000 tokens per second. Plus: Why Andreessen thinks AI isn’t the Internet redux. Key Topics Covered * Claude Code skills and the progressive disclosure problem * How Noah built a hook to solve the 10% skill hit rate * Tier 1 vs Tier 2 action space: Why Manus and Anthropic converged on the same architecture independently * 3,000 tokens per second: Using Cerebras Llama 120B as an invisible routing layer for every user message * The MCP/skill/command convergence: Are they all just different flavors of the same primitive? * Vision feedback loop: Turning Gemini into a Pentagram creative director to critique Claude’s web designs * Andreessen’s “computers v2” thesis: Why AI isn’t the Internet redux, it’s the first von Neumann architecture replacement in 80 years * Git workflows with Claude Code: Why Lance and Noah don’t worry about merge conflicts anymore Timestamps * 00:11 – Welcome to episode 2 on Claude Code skills * 00:28 – What are Claude Code skills? Not much more than a folder full of prompts * 01:10 – Lance: Skills as “instructing a new hire” with subfolder instructions * 01:25 – Simon Willison and Jesse Vincent’s “superpowers” discovery * 04:45 – Noah demos the Alephic CLI skill directory structure * 07:32 – The hook-based skill search system using Cerebras * 08:19 – Lance reveals: YAML front matter always loads into system prompt * 09:32 – The 10% skill hit rate problem when you have 10+ skills * 10:08 – Cerebras Llama 120B running at 3,000 tokens per second for invisible routing * 13:17 – The universal pattern: Everyone’s trying to control context * 15:59 – Tier 1 vs Tier 2 action space: Manus and Anthropic converge independently * 21:29 – Noah’s big challenge: Getting models to consistently look for skills * 28:04 – Hit rate drops to 10% even with only 4–5 skills * 30:54 – Could progressive disclosure become built-in like chain of thought? * 34:06 – Lance on externalizing context to file systems * 35:15 – Vision feedback loop: Gemini as Pentagram creative director critiquing Claude’s designs * 37:57 – Andreessen: AI isn’t the Internet, it’s computers v2 * 42:08 – Why Noah and Lance don’t worry about merge conflicts anymore Links & References Core References * 📄 Anthropic Engineering Blog on Skills [https://www.anthropic.com/engineering] – The engineering blog post Lance mentions about YAML front matter and system prompts * 🎙️ Andrej Karpathy on Dwarkesh Podcast [https://www.dwarkesh.com/podcast] – Discussion on small models and reasoning engines * 🎙️ Andreessen on Cheeky Pint Podcast [https://www.youtube.com/watch?v=example] – “AI is computers v2” thesis: First von Neumann architecture replacement in 80 years * 🎙️ Claude Code Podcast with Boris and Kat [https://www.anthropic.com/podcast] – Discussion on dual-use tools Tools & Frameworks * 🔗 Claude Code [https://claude.ai/code] – Anthropic’s AI coding assistant * 🔗 Jesse Vincent’s Superpowers [https://github.com/jvincent/superpowers] – Original skills plugin that inspired Noah * 🔗 Manus [https://manus.ai] – Consumer agent with multi-tier action space architecture * 🔗 Cerebras [https://cerebras.ai] – Llama 120B at 3,000 tokens per second * 🔗 Puppeteer MCP [https://github.com/puppeteer/puppeteer] – Browser automation MCP * 🔗 Playwright MCP [https://playwright.dev/] – Browser automation alternative * 🔗 GitHub CLI [https://cli.github.com/] – Command line tool Lance loves for PR management Blog Posts * Simon Willison’s Blog [https://simonwillison.net/] – First place Noah saw Claude Code skills coverage * Cloudflare TypeScript Type Definitions Technique [https://blog.cloudflare.com/] – Alternative to classic MCP definitions Companies Mentioned * Anthropic [https://www.anthropic.com/] – Claude Code creator * LangChain [https://www.langchain.com/] – Where Lance is a founding engineer * Alephic [https://www.alephic.com/] – Noah’s AI consulting company * Pentagram [https://www.pentagram.com/] – Design agency Noah used as creative director persona Development Tools * Obsidian [https://obsidian.md/] – Note-taking use case for Claude Code * Git Work Trees [https://git-scm.com/docs/git-worktree] – How the team manages multi-branch development About the Hosts Noah Brier is co-founder of Alephic [https://www.alephic.com/], an AI consulting company helping brands build custom AI systems. He writes about AI strategy and implementation. Lance Martin is a founding engineer at LangChain [https://www.langchain.com/], where he works on developer tools for building AI applications. Connect with the Hosts * Noah Brier: LinkedIn [https://linkedin.com/in/noahbrier] | X/Twitter [https://twitter.com/heynoah] * Lance Martin: LinkedIn [https://linkedin.com/in/lancemartin] | X/Twitter [https://twitter.com/RLanceMartin] Subscribe for weekly episodes exploring how AI is actually being deployed in the real world. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.forwarddeployed.com [https://www.forwarddeployed.com?utm_medium=podcast&utm_campaign=CTA_1]

Forward Deployed, Episode 1: The Bitter Lesson

Welcome to the first episode of Forward Deployed (YouTube [https://www.youtube.com/watch?v=bw37s0yxpvY]), a podcast exploring the intersection of AI, software development, and the enterprise. We’re very excited to have you join us as we tackle the wild world of Forward Deployed engineering. We hope to make this a roughly bi-weekly show and look forward to inviting guests in the future. The idea is to dive deep into the realities of making this stuff work in companies, building on our expertise as builders both inside and outside the enterprise. Thanks for listening, and please let us know what you think. Thanks, Noah & Lance Subscribe to Forward Deployed to be the first to hear about new episodes and articles. In this inaugural episode, hosts Noah Brier [http://x.com/heyitsnoah] (Co-founder, Alephic [http://alephic.com]) and Lance Martin [https://x.com/RLanceMartin] (Founding Engineer, LangChain [http://langchain.com]) dive deep into one of AI’s most controversial ideas: The Bitter Lesson. They unpack Richard Sutton’s famous essay, debate whether LLMs truly follow its principles, and explore what this means for anyone building with AI today. Key Topics Covered * The Bitter Lesson: Why more compute beats clever algorithms (or does it?) * Richard Sutton’s surprising take on why LLMs aren’t “bitter lesson pilled” * The evolution from CNNs to transformers through Lance’s journey from Stanford to Uber’s self-driving program to LangChain * Chain of thought prompting vs reasoning models - why your prompts might be breaking * The real challenges of enterprise AI adoption * Why ICs are adopting AI faster than managers * Building for imperfection: Why optimizing for today’s models is a mistake Timestamps * 00:00 - Introductions and backgrounds * 00:53 - Lance’s journey: Stanford PhD to Uber self-driving to LangChain * 02:49 - Noah’s path from marketing to AI obsession * 04:04 - What “forward deployed” really means * 09:04 - The Bitter Lesson explained * 11:31 - Why Sutton thinks LLMs aren’t following the bitter lesson * 23:09 - Chain of thought prompting and the reasoning model revolution * 24:19 - Building for future models, not current ones * 45:20 - ICs vs managers in AI adoption About the Hosts Noah Brier is co-founder of Alephic [https://www.alephic.com/], an AI consulting company working with enterprise clients like PayPal, EY, Meta, and Amazon on AI-powered content intelligence and competitive analysis. Previously founded and sold Percolate (marketing tech). He also runs the BRXND conference series [https://brxnd.ai/] focused on marketing and AI. Lance Martin is a founding engineer at LangChain [https://www.langchain.com/] with a PhD from Stanford. Former computer vision lead for Uber’s self-driving truck program. Links & References Core References * 📄 The Bitter Lesson by Richard Sutton (2019) [https://www.cs.utexas.edu/~eunsol/courses/data/bitter_lesson.pdf] * 🎙️ Richard Sutton on Dwarkesh Podcast: “Father of RL thinks LLMs are a dead end” [https://www.dwarkesh.com/p/richard-sutton] (September 26, 2025) * YouTube version [https://www.youtube.com/watch?v=21EYKqUsPfg] * Apple Podcasts [https://podcasts.apple.com/us/podcast/richard-sutton-father-of-rl-thinks-llms-are-a-dead-end/id1516093381?i=1000728584744] * Dwarkesh’s follow-up reflections [https://www.dwarkesh.com/p/thoughts-on-sutton] * 📄 The Unreasonable Effectiveness of Recurrent Neural Networks by Andrej Karpathy (2015) [https://karpathy.github.io/2015/05/21/rnn-effectiveness/] * 📄 Trading Margin for Moat: Why the Forward Deployed Engineer Is the Hottest Job in Startups (A16Z) [https://a16z.com/services-led-growth/] Related Podcast Appearances * 🎙️ Noah Brier on Every’s AI & I: “Claude Code Can Be Your Second Brain” [https://every.to/podcast/how-to-use-claude-code-as-a-thinking-partner] (September 10, 2025) - Noah demonstrates his Claude Code-Obsidian setup for research and thinking * Listen on Spotify [https://open.spotify.com/episode/4D8G4ZhgmFrMDNYrrQOTbe] * Apple Podcasts [https://podcasts.apple.com/ca/podcast/claude-code-can-be-your-second-brain/id1719789201?i=1000725911151] Blog Posts from the Hosts * Learning the Bitter Lesson [https://rlancemartin.github.io/2025/07/30/bitter_lesson/] - Lance Martin * Context Engineering for Agents [https://rlancemartin.github.io/2025/06/23/context_engineering/] - Lance Martin * Thinking Ahead, Building Ahead [https://www.alephic.com/writing/thinking-ahead-building-ahead] - Charles Gallant * The Magic of Claude Code [https://www.alephic.com/writing/the-magic-of-claude-code] - Noah Brier * Strategic Software [https://www.alephic.com/writing/strategic-software] - Noah Brier * Things I Think I Think About AI [https://www.alephic.com/writing/things-i-think-i-think-about-ai] - Noah Brier Connect with the Hosts * Noah Brier: LinkedIn [https://www.linkedin.com/in/noahbrier/] | X/Twitter [https://x.com/heyitsnoah] * Lance Martin: LinkedIn [https://www.linkedin.com/in/lance-martin-64a33b5/] | X/Twitter [https://x.com/rlancemartin] * Alephic: alephic.com [https://www.alephic.com/] * BRXND: brxnd.ai [https://brxnd.ai/] Subscribe for weekly episodes exploring how AI is actually being deployed in the real world. Newsletter: Sign up for updates at forwarddeployed.com [https://forwarddeployed.com/] This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.forwarddeployed.com [https://www.forwarddeployed.com?utm_medium=podcast&utm_campaign=CTA_1]