End-to-End with Shape Up: A Real-World Case Study

Ryan Singer is one of the earliest employees and the former Head of Strategy at 37signals (the makers of Basecamp), where he spent nearly two decades refining a product development approach that helped the company build super-successful products with small teams. Based on these lessons, he wrote "Shape Up: Stop Running in Circles and Ship Work that Matters," and Ryan now works with companies of all sizes to help them escape the cycle of endless sprints, missed deadlines, and dragging projects. What you’ll learn: 1. Why traditional Agile and Scrum methods often lead teams into endless cycles of work without meaningful shipping milestones. 2. The “appetite-driven” approach to product development where teams set fixed timeboxes (usually six weeks maximum) and vary the scope instead of expanding timelines. 3. The exact process for running effective “shaping” sessions that collaboratively define projects before committing resources. 4. Why most teams struggle with too little detail in their planning, not too much. 5. Why a 30-to-50-person team size is the critical breaking point when growing startups need to adopt more structured processes. 6. Practical techniques for bridging the engineering-design divide by bringing technical and product perspectives together earlier in the process. 7. The powerful “breadboarding” and “fat marker sketching” techniques that help teams align on solutions without getting lost in high-fidelity details. 8. The clear warning signs that your current development process is failing before it’s too late to change course. 9. Proven strategies to implement Shape Up methods, whether you’re working in a startup or enterprise environment. 10. A step-by-step approach to transitioning from Scrum to Shape Up by piloting the methodology with a single team before broader implementation. 11. Why the PM role shifts upstream in Shape Up, focusing more on problem definition than project management. 12. How to adapt Shape Up principles to your company’s unique context, even if it’s nothing like Basecamp. — Brought to you by: • WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs: https://workos.com/lenny • Merge—A single API to add hundreds of integrations into your app: http://merge.dev/lenny • Airtable ProductCentral—Launch to new heights with a unified system for product development: https://www.airtable.com/lenny Find the transcript at: https://www.lennysnewsletter.com/p/shape-up-ryan-singer Where to find Ryan Singer: • X: https://x.com/rjs • LinkedIn: https://www.linkedin.com/in/feltpresence/ • Website: https://www.ryansinger.co/ • Course: https://www.ryansinger.co/srl/ Where to find Lenny: • Newsletter: https://www.lennysnewsletter.com • X: https://twitter.com/lennysan • LinkedIn: https://www.linkedin.com/in/lennyrachitsky/ In this episode, we cover: (00:00) Ryan’s background (04:38) The origins of Shape Up (07:40) Implementing Shape Up in different companies (09:56) How Shape Up is different (19:02) The core elements of Shape Up (26:29) Shaping sessions and timeboxing (37:23) Flexible sprint planning (38:56) The output of a shaping session (46:57) Balancing detail and flexibility (53:50) A deep dive into shaping sessions (01:01:32) Fat marker sketches (01:02:48) Getting started using Shape Up (01:13:20) Signs it's time to try the Shape Up method (01:18:25) Feature factories (01:25:59) The role of the PM in Shape Up (01:28:26) What makes Basecamp unique (01:35:55) The second edition of the book (01:38:30) Linking product strategy and shaping (01:41:53) Conclusion and final thoughts Referenced: • Basecamp: https://basecamp.com/ • David Heinemeier Hansson on LinkedIn: https://www.linkedin.com/in/david-heinemeier-hansson-374b18221/ • Jason Fried on LinkedIn: https://www.linkedin.com/in/jason-fried/ • Jason Fried challenges your thinking on fundraising, goals, growth, and more: https://www.lennysnewsletter.com/p/jason-fried-challenges-your-thinking • Des Traynor on LinkedIn: https://www.linkedin.com/in/destraynor/ • Intercom: https://www.intercom.com/ ...References continued at: https://www.lennysnewsletter.com/p/shape-up-ryan-singer Recommended books: • Shape Up: Stop Running in Circles and Ship Work That Matters: https://basecamp.com/shapeup • Demand-Side Sales 101: Stop Selling and Help Your Customers Make Progress: https://www.amazon.com/Demand-Side-Sales-101-Customers-Progress/dp/1544509987/ • Competing Against Luck: The Story of Innovation and Customer Choice: https://www.amazon.com/Competing-Against-Luck-Innovation-Customer/dp/0062435612/ • Job Moves: 9 Steps for Making Progress in Your Career: https://www.amazon.com/Job-Moves-Making-Progress-Career/dp/0063283581 Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com. Lenny may be an investor in the companies discussed.

This talk was recorded at Copenhagen Developers Festival in Copenhagen, Denmark. #cphdevfest #ndcconferences #developer #softwaredeveloper Attend the next NDC conference near you: https://ndcconferences.com https://cphdevfest.com/ Subscribe to our YouTube channel and learn every day: / @NDC Follow our Social Media! https://www.facebook.com/ndcconferences https://twitter.com/NDC_Conferences https://www.instagram.com/ndc_conferences/ #agile #softskills In this talk, we look at the Shape Up methodology, a project management approach, or more correctly, a risk management technique, developed by Basecamp. We'll be focusing on its application in a real-world startup environment, drawing from two years of experience in implementing Shape Up. You'll get an overview of how this method contrasts with traditional project management techniques, particularly in terms of team organization and project execution. We will talk about our transition away from the traditional backlog system to embracing six-week work cycles and a project 'betting table', which has brought notable changes in our approach to task prioritization and execution. Our journey with Shape Up has given us several advantages, especially in moving away from exhaustive and often overwhelming backlogs. Another key aspect of our experience has been the shift from using time estimates over to implementing time budgets. While the approach has helped with our focus and with managing the uncertainties inherent in product development, it has not been without trade-offs. The talk will provide attendees with real-life examples and actionable insights, aiming to show how the Shape Up methodology can be effectively adapted in various organizational contexts and what challenges you can face. Whether you are part of a startup or a larger company, the session will offer valuable perspectives on balancing structure with flexibility in project management.

Learn to use Anthropic's Claude Agent SDK (formerly Claude Code SDK) for AI-powered development workflows! https://platform.claude.com/docs/en/agent-sdk/overview https://x.com/trq212 **AI Summary** This workshop by Thariq Shihipar (Anthropic) details the architecture and implementation of the **Claude Agent SDK**. The session moves from high-level theory—defining "agents" as autonomous systems that manage their own context and trajectory—to a live-coding demonstration. Shihipar builds an agent "Harness" from scratch, implementing the core **Agent Loop** (Context Thought Action Observation), integrating the **Bash tool** for general computer use, and demonstrating **Context Engineering** via the file system to maintain state across long tasks. **Timestamps** 00:00 Introduction: Agenda and the "Agent" definition 05:15 The "Harness" concept: Tools, Prompts, and Skills 10:10 Live Coding Setup: Initializing the Agent class and environment 15:45 implementing the "Think" step: Getting the model to reason before acting 25:20 The Agent Loop: connecting `act`, `observe`, and `loop` 33:10 Tool Execution: Handling XML parsing and tool inputs 42:00 The "Bash" Tool: Giving the agent command line access 49:30 Safety & Permissions: "ReadOnly" vs "ReadWrite" file access 58:15 Context Engineering: Using `ls` and `cat` to build dynamic context 01:05:00 The "Monitor": Viewing the agent's thought process in real-time 01:12:45 Handling "Stuck" States: Feedback loops and error correction 01:21:20 Multi-turn Complex Tasks: Building a "Research Agent" demo 01:35:10 Refactoring patterns: "Hooks" and deterministic overrides 01:48:39 Q&A: Reproducibility, helper scripts, and non-determinism 01:50:31 Q&A: Strategies for massive codebases (50M+ lines) 01:52:00 Closing remarks and future SDK roadmap * **Evolution of AI Capabilities:** Shihipar argues we are shifting from **LLM Features** (categorization, single turn) to **Workflows** (structured, multi-step chains like RAG) to **Agents**. He defines agents as systems that *"build their own context, decide their own trajectories, and work very autonomously"* rather than following a rigid pipeline. * **The Claude Agent SDK Architecture:** The SDK is built directly on top of **Claude Code** because Anthropic found they were *"rebuilding the same parts over and over again"* for internal tools. * **The Harness:** A robust agent requires more than just a model; it needs a "Harness" containing Tools, Prompts, a **File System**, Skills, Sub-agents, and Memory. * **Opinionated Design:** The SDK bakes in lessons from deploying Claude Code, specifically the "opinion" that general computer use (Bash) is often superior to bespoke tools. * **The Power of the Bash Tool:** A key technical insight is that the **Bash tool** is often the most powerful tool for an agent. Instead of building custom tools for every action (e.g., a specific API wrapper for a file conversion), giving the agent access to the shell allows it to use existing software (like `ffmpeg`, `grep`, or `git`) to solve problems flexibly, similar to how a human developer works. * **Context Engineering:** Shihipar introduces the concept of **Context Engineering** via the file system. Instead of just "Prompt Engineering," the agent uses the file system to manage its state and context. * **Files as Memory:** The agent can write to files to "remember" things or create its own documentation (e.g., `CLAUDE.md`) to ground future actions. * **Verification:** The file system serves as a ground truth for the agent to verify its work (e.g., checking if a file was actually created). * **The Agent Loop & Intuition:** Building a successful agent loop is described as *"kind of an art or intuition"*. The loop generally follows a **Gather Context Take Action Verify Work** cycle. Shihipar emphasizes that this loop allows the agent to self-correct, a capability missing from rigid workflows. * **Strategies for Determinism (Hooks):** During the Q&A, a technique for controlling agent behavior is discussed: **Hooks**. * If an agent hallucinates or skips a step (e.g., guessing a Pokemon stat instead of checking a script), a hook can intercept the response and inject feedback: *"Please make sure you write a script, please make sure you read this data."* * This enforces rules like "read before you write" without retraining the model. * **Scaling to Large Codebases:** For massive codebases (50M+ lines), standard tools like `grep` or basic context window stuffing fail. * **Semantic Search Limitations:** Shihipar notes that while semantic search is a common solution, it is *"brittle"* because the model isn't trained on the specific semantic index. * **Solution:** He recommends good **"Claude MD"** files (context files) and starting the agent in a specific subdirectory to limit scope, rather than trying to index the entire 50M lines at once.

Matt will be back on stage at the World's Fair next week! see https://ai.engineer/wf and use YOUTUBEPROMO for new tickets only. Join 6000 AI engineers at the "Superbowl of AI"! --- A hands-on workshop covering the full lifecycle of AI-assisted development, from turning ambiguous requirements into agent-ready plans to running autonomous coding agents that ship production features. You'll learn to stress-test vague briefs into structured PRDs, slice work into thin "tracer bullet" vertical slices, and run an AI agent with TDD. You'll watch it select tasks, write tests, implement code, and commit. You'll then refine your prompts based on where it struggles, graduate to fully autonomous (AFK) runs, and learn to design codebases that maximize agent effectiveness. You'll walk away knowing how to: - Turn ambiguous requirements into agent-ready issues - Slice work into vertical tracer bullets an agent can grab independently - Run AI agents human-in-the-loop and autonomously with TDD - Design codebase architectures that AI agents love to work in For: Engineers ready to move beyond chat-based AI assistance and build a real workflow for shipping features with autonomous coding agents. Speaker info: - https://x.com/mattpocockuk - https://www.linkedin.com/in/mapocock/ - https://youtube.com/@mattpocockuk Timestamps: 00:00:00 - Introduction 00:00:14 - The Thesis of AI Engineering 00:04:20 - Phase 1: Research & Prototyping 00:12:45 - Phase 2: The Grill Session 00:22:10 - Phase 3: Writing the PRD 00:35:50 - Phase 4: Slicing Work into Issues 00:48:15 - Phase 5: Implementation with AI Agents 01:05:30 - Phase 6: Human-in-the-Loop Review 01:18:45 - Phase 7: Deployment & Monitoring 01:28:10 - Designing Codebases for AI Effectiveness 01:34:06 - Final Takeaways & Summary

An LLM is an incredibly powerful brain that knows everything about humanity and nothing about you or the software you run. This video walks through the four buzzwords that turn that raw brain into a system you can trust: agent harness, loop engineering, LLM Ops, and eval. No jargon, step by step, technical or not. You can build anything. You can learn anything. 💪 Timeline 0:00 Intro: the 4 AI agent buzzwords 0:42 What an AI agent run actually is 1:52 The memory system: procedural, semantic, episodic 3:37 What "harness" really means (the horse) 5:07 Storing and updating memory (databases, skills, summarizer agent) 8:28 Retrieval: RAG, SQL vs semantic search 10:00 Tool calling and why agents loop 10:52 Loop engineering and end-loop guardrails 13:21 A Claude Code hooks example 14:18 Eval and LLM Ops: why you need them 15:55 Tracing every run (Langfuse, LangSmith) 16:43 Evaluation: LLM as a judge 17:20 Diagnosing what broke 18:16 The gate: ship the fix or fix the bug 18:57 Zoom out: the full system 19:53 Wrap up Launch Full-Stack App Template: https://github.com/ShenSeanChen/launch-mvp-stripe-nextjs-supabase My AI Agent Startup AutoManus.io is an AI sales lead manager for made-to-order product sales. We embed directly where conversations happen (WhatsApp, email, web chat) to capture inbound, automate follow‑ups, and kill CRM busywork; live with 4 pilots and 2 contracts in motion, pre‑seed backed by Character VC. Focused on US/UK/Germany, raising to expand engineering and scale deployments. ☕️ Buy me a coffee: https://buy.stripe.com/5kA176bA895ggog4gh - X: https://x.com/ShenSeanChen - Sean's Discord: https://discord.gg/tvECErKcFr - AutoManus Discord: https://discord.gg/5HhcNjCR - LinkedIn: https://linkedin.com/in/shen-sean-chen - Github Link: https://github.com/ShenSeanChen - Instagram: https://www.instagram.com/sean_ai_stories Sub Count when launched: 13,050 Top Github Repos - LaunchMVP NextJS,Supabase,Stripe (1015 stars): https://github.com/ShenSeanChen/launch-mvp-stripe-nextjs-supabase - ReactNextJSTips (114 stars): https://github.com/ShenSeanChen/yt-react-nextjs-tips - DeepResearchAgentBackend (70 stars): https://github.com/ShenSeanChen/yt-DeepResearch-Backend - SupabaseTipsKanban (64 stars): https://github.com/ShenSeanChen/yt-supabase-tips-kanban - RAGVectorDB (56 stars): https://github.com/ShenSeanChen/yt-rag - KimiK2Claude (37 stars): https://github.com/ShenSeanChen/yt-kimi-k2-claude - DeepResearchAgentFrontend (33 stars): https://github.com/ShenSeanChen/yt-DeepResearch-Frontend - AgenticRAG (13 stars): https://github.com/ShenSeanChen/yt-agentic-rag You Can Build Anything Playlist (Full-Stack Dev Without CS Degrees) - Core7: 95% React/NextJS Use Cases https://www.youtube.com/watch?v=vZzFlAjz4rA&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=16 - Core6: 95% Supabase Use Cases https://www.youtube.com/watch?v=Pnoq2tIif3s&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=15 - Core5: StripeNextJSSupabase https://www.youtube.com/watch?v=ad1BxZufer8&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=8 - Core4: AuthSupabaseGoogle https://www.youtube.com/watch?v=AZAU3ClAWWE&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=6 - Core3: FastapiGCPPro https://www.youtube.com/watch?v=u3sfqpzzo-U&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=5 - Core2: SupabaseHero https://www.youtube.com/watch?v=V0kmgkyPsVQ&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=4 - Core1: LaunchAnApp https://www.youtube.com/watch?v=iQ2izvGG4tQ&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=3 - Launch WhereToMeet w/ GoogleMaps, Calendar, Supabase, Cursor: https://www.youtube.com/watch?v=5xMjX1QxGUY&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR&index=2 - Launch EncourageMe w/ Cursor, Supabase, Vercel https://www.youtube.com/watch?v=hnvL4xa2DHA&list=PLE9hy4A7ZTmpGq7GHf5tgGFWh2277AeDR

🚀 Work with us - https://aifoundations.io/apply ✨ Join Ai Foundations - https://aifoundations.io This is the only Claude tutorial you’ll ever need. With this guide you can go from beginner to pro using Claude. I cover the basics like signing up, settings, memory, prompting and we work our way up to the intermediate features like Claude projects, artifacts, inline visualizations, data analytics and more. Then we finally dive into Claude desktop, where I teach you how to use Claude Cowork with computer use, scheduled tasks, and connectors for Notion, Gmail and Google Calendar. I even show you how to build Claude skills from scratch. After you have a beginner's understanding of Claude we dive into Claude Code. I show you how to deploy a real website in Netlify and even control Claude through a remote environment on Anthropics servers. We cover github, environment variables, pretty much everything you need, explained in beginner terms. I even cover exporting your ChatGPT memories and bringing them over to Claude. If you've been hearing about Claude AI, Claude Cowork, or Claude Code and wondering how it all fits together: this is the video you’ve been searching for. I walk through everything step-by-step leaving no stone unturned. Utilize the chapters and resources below to get the most out of this video. If it’s your first time watching, I recommend watching all the way through at least once, then coming back to spend extra time on specific chapters! Resources Mentioned: Join Ai Foundations - https://aifoundations.io DBS Framework Skill - https://aifoundations.io/resources/the-dbs-framework-skill Claude Code Mastery - https://aifoundations.io/products/claude-code-mastery Sign up for Claude - https://claude.ai Chapters: 0:00 - Claude Tutorial Intro 0:25 - How to Use This Guide 0:40 - Claude Pricing Comparison 1:22 - Sign Up for Claude 1:49 - Claude Onboarding 3:10 - Claude Chat Layout 3:50 - General Settings 4:53 - Notifications 6:00 - Claude Appearance 6:35 - Claude Voices 6:51 - Privacy and Billing 8:02 - Claude Memory 8:26 - Exporting Memories from ChatGPT 9:21 - Tool Settings 10:14 - Claude Artifact Settings 11:23 - Code Permissions 12:10 - Connector Settings 13:00 - Language Settings 13:15 - Claude Status and Support 13:50 - Gifting Claude 14:23 - Keyboard Shortcuts 14:40 - Claude Models 16:15 - Attachments and Connections 17:10 - Writing Styles in Claude 17:53 - Talking to Claude Voice 19:00 - Organizing Chats 19:40 - Incognito Chats 20:20 - GCAO Prompt Template 21:50 - Prompting Claude 24:50 - Ai Foundations Offers 25:38 - Claude Chat Search 26:34 - Claude Projects Guide 27:18 - Project Instructions 29:40 - Projects Guide Continued 30:56 - Claude Artifacts Library 32:37 - Creating Claude Artifacts 36:40 - Sharing Artifacts 37:15 - Mini App Artifacts 38:35 - Inline Visualizations 39:00 - Visualizing Data Analytics 41:15 - Claude Desktop 42:45 - Claude Cowork Setup 44:00 - Claude Quick Chat 45:00 - Cowork Settings Continued 47:00 - Organizing Files in Cowork 48:20 - Claude Computer Use 49:30 - Cowork Scheduled Tasks 51:22 - Cowork Projects 52:40 - Cowork Prospecting Project 55:00 - Claude in Chrome Extension 56:10 - Cowork Project Results 57:05 - Claude Dispatch Setup 57:50 - Cowork Connectors 58:20 - Claude Notion MCP Connector 59:30 - Using Connectors 1:00:18 - Claude Gmail Connector 1:02:40 - Claude Skills 1:04:18 - DBS Framework Skill 1:05:30 - Uploading Skills 1:06:00 - Creating a Basic Skill 1:07:36 - Testing the Recipe Skill 1:09:25 - Creating an Advanced Skill 1:10:20 - Google Calendar Connector 1:12:24 - Testing the Calendar Skill 1:13:10 - Claude Code Prerequisite 1:14:20 - Claude Code Mastery 1:15:23 - Two Ways to Use Claude Code 1:15:48 - Claude Code Environments 1:17:45 - Claude Code Models 1:18:10 - Claude Code Effort 1:18:34 - Claude Code Permissions 1:18:50 - Claude Code Enhancements 1:20:20 - Folder Setup 1:21:30 - Creating Claude MD 1:22:12 - Opening Files Quickly 1:22:31 - Building a Personal Website 1:25:15 - Planning with Claude Code 1:28:05 - Plan Mode in Claude Code 1:28:45 - Editing My Site 1:29:19 - The Complete Website 1:30:00 - Deploying with Netlify Connector 1:31:12 - Setting a Domain Name 1:31:45 - Adding Environment Variables 1:34:00 - Testing Email Connection 1:34:30 - Creating Remote Skills 1:36:18 - Github Repo Setup 1:37:00 - Initial Commit in Github 1:38:00 - Claude Code Cloud Environments 1:39:00 - Claude Code on my Phone 1:39:55 - Netlify + Github Deployment Setup 1:41:00 - Updating My Website 1:42:00 - Website Complete 1:42:20 - Claude Code Scheduled Tasks 1:44:24 - Scheduled Tasks with Skills 1:47:30 - Updating My Website from Anywhere 1:49:50 - Claude Code Terminal 1:50:30 - Claude Code Commands 1:51:10 - Claude Code Terminal Test 1:51:58 - Final Thoughts #claude #claudecowork #claudecode