How Founders Use AI

How people use AI, and the tool for each job.

The AI map of which tool is for which job, checked on 29 October 2026, what changed since July, and every video, thread, guide, podcast and tool behind 278 answered questions on putting AI to work.

The AI map: which tool is for which job, as of 29 October 2026

Models and assistants AI assistants Frontier models Open-weight models Decision models

Building with AI Coding agents App builders Design and presentations Spreadsheets, data and internal tools

Agents and research Agents that do tasks for you AI browsers No-code automation with AI steps Research and search Meeting notes and everyday productivity

Making media Video generation Images Avatars and voice Music and audio Video editing

AI at work Prospecting and sales Marketing, ads and AI search Customer support agents Legal and contracts Finance and accounting Hiring and HR

What changed since July

  1. 28 Oct 2026 GitHub began including Copilot with GitHub Enterprise licences and added projects to the Copilot app, where several agents work across repositories. Coding agents github.blog
  2. 27 Oct 2026 n8n released the 3.0 beta, a reliability and security release with breaking changes; self-hosting now runs on Docker only and the stable release is due in early December. No-code automation with AI steps blog.n8n.io
  3. 27 Oct 2026 Hex released Hex 4.0, rebuilt for analysts and AI agents working together, with a $100 million raise. Spreadsheets, data and internal tools hex.tech
  4. 26 Oct 2026 Replit launched Replit for Business, and the next day Cloud Agents that let non-engineers propose changes to a company codebase. App builders blog.replit.com
  5. 26 Oct 2026 OpenAI released GPT-6.1 Terra at $1 / $5 per million tokens, half the price of GPT-6.1 Sol. Frontier models openai.com
All 108 changes

What founders use most, ranked by how many answers lean on it.

  1. The psychology of waiting, which AI products live or die by. pencilandpaper.io Article UX Design Patterns for Loading and Feedback Pencil and Paper
  2. The clearest playbook for escaping wrapper status: own the value chain of one vertical. nfx.com Article The AI Wrapper is Dead: 3 Approaches to Verticalization NFX
  3. The canonical essay: most startups start without moats and earn them over time. blog.eladgil.com Article Defensibility and Competition Elad Gil
  4. The five-minute thread version, perfect for a worried co-founder or investor meeting. x.com Thread Is the "wrapper on GPT" company defensible? (thread) Elad Gil
  5. Documents platform encroachment: OpenAI absorbed four wrapper categories in 18 months. forbes.com Article AI Wrappers Lack Defensibility: Why Barriers To Entry Matter Forbes Business Development Council
  6. Names the three real layers: data moat, behavioral moat, workflow moat. hatchworks.com Article AI Wrapper Product Strategy: Most Founders Get the Moat Wrong HatchWorks
  7. An Asia-market VC's nuanced answer: data moats work in specialized domains, not generically. review.insignia.vc Article Is Proprietary Data Still a Moat in the AI Race? Insignia Ventures (Southeast Asia)
  8. A growth-stage investor's checklist of which classic moats survive AI and which do not. insightpartners.com Article Building a moat in the age of AI Insight Partners
  9. What investors actually screen for when they hear the word wrapper. techcrunch.com Article VCs say AI companies need proprietary data to stand out TechCrunch
  10. A skeptical, technical take on when data actually compounds into advantage. v7labs.com Article Data Moats: Do They Exist In The Age of AI? V7 Labs
  11. Actionable moves for capturing data your competitors structurally cannot get. thestrategystack.substack.com Article How to Build a Proprietary Data Moat in AI (7 Practical Moves) The Strategy Stack
  12. A crisp synthesis of the Gil and Tavel schools applied to today's AI stack. ntkris.substack.com Article Defensibility in AI Krishna's Newsletter
  13. The contrarian 2026 update: distribution, not technology, decides who wins. forbes.com Article Every Company Is Now An AI Wrapper So GTM Is The New Moat Josipa Majic (Forbes)
  14. A taxonomy of AI-era moats with named startup examples for each. eoncodes.substack.com Article The Startup Moats Defining the AI Era Andre J (Substack)
  15. How systems design makes usage data inseparable from the product, the subtlest moat. latitudemedia.com Article In the age of AI, can startups still build a moat? Latitude Media
  16. Practitioners on building with LLMs without getting outmaneuvered by the labs. oreilly.com Article What We Learned from a Year of Building with LLMs (Part III): Strategy Eugene Yan, Hamel Husain, et al.
  17. The manifesto that successful agents are mostly well-engineered software with LLM sprinkled at key points. github.com Guide 12-Factor Agents: principles for production LLM software Dex Horthy (HumanLayer)
  18. A working engineer's decision criteria with cost and reliability tradeoffs spelled out. towardsdatascience.com Article A Developer's Guide to Building Scalable AI: Workflows vs Agents Towards Data Science
  19. Short and sharp: if the steps are known in advance, a workflow wins on every axis. redis.io Article AI Agents vs Workflows: When to Use Each Redis
  20. A neutral reference explainer to align your team on terminology before the build debate. promptingguide.ai Guide AI Workflows vs AI Agents Prompt Engineering Guide (DAIR.AI)
  21. How a regulated enterprise makes the call, useful discipline for any founder. medium.com Article AI agents vs. predefined workflows: practical decision guide Capital One Tech
  22. Brings the production data: only 23% of orgs have scaled an agent anywhere. intuitionlabs.ai Article AI Agents vs. AI Workflows: Why Pipelines Dominate IntuitionLabs
  23. The founder-flavoured argument against reaching for the harder, smarter-sounding option. buildmvpfast.com Article AI Workflows vs Agents: Why Workflows Win BuildMVPFast
  24. The next interaction pattern: agents that act on events, with humans approving at checkpoints. inferencebysequoia.substack.com Article Ambient Agents and the New Agent Inbox Sequoia Capital

Show the next 24

Playbooks

A goal, and the route through it a step at a time.

Start using AI well Pick an assistant, learn with it, hand it real work, and keep yourself and your data safe. 5 steps Build your product with AI From a prompt to a shipped product: prototype, build, and wire AI into what you ship. 6 steps Code and ship with AI Write, ship, and maintain real software as a founder, with AI as your pair. 4 steps Design and prototype with AI Go from idea to a clickable prototype without a designer. 3 steps Build AI agents and automations Wire up agents and internal tools that do real work for you. 3 steps Put AI inside your product Ship AI features users actually feel, not a bolted-on chatbot. 3 steps Research your market with AI Size the market, study competitors, and read data in hours, not weeks. 3 steps Market and grow with AI Content, creative, and distribution: fill the top of the funnel without a big team. 5 steps Create content with AI Write, film, and design a content engine that runs without a team. 3 steps Get found in AI search Show up when founders and buyers ask AI, not just Google (AEO/GEO). 3 steps Run ads with AI Brief creatives, read the numbers, and optimize spend with AI. 3 steps Find and serve customers with AI Research the market, prospect, close, and support, with AI doing the heavy lifting. 4 steps Sell and prospect with AI Find leads, personalize outreach, and run better sales calls. 3 steps Support customers with AI Answer faster and deflect tickets without losing the human touch. 3 steps Run the back office with AI The unglamorous grind: workflows, finance, legal, and hiring, automated where it counts. 5 steps Automate your workflows Stitch your tools together so the busywork runs itself. 3 steps Hire and manage your team with AI Source, screen, and onboard faster, and keep the team in sync. 3 steps Handle legal and finance with AI Draft contracts and stay on top of the numbers without a big spend. 2 steps Be more productive with AI Get more done and think sharper with AI as a daily habit. 3 steps Become an AI-native founder The meta-skills: build your stack, prompt well, and use AI to research, think, and decide. 6 steps Build your AI stack Pick the tools worth paying for and the prompts worth reusing. 3 steps

The questions, by topic

Building & Product

Vibe Coding 15 Databases & Internal Tools 11 AI Agents 15 Design & Prototyping 12 AI in Your Product 13

Research & Knowledge

Search & Research 13 Market Research 13 Data Analysis 13

Marketing & Growth

Content Creation 12 Video, Image & Audio 14 Getting Found in AI Search (AEO/GEO) 12 Ads & Performance Marketing 14 Social & Community 12

Sales & Customers

Sales Prospecting 13 Customer Support 6 CRM & Sales Calls 12

Operations & Back-office

Legal & Contracts 13 Finance & Accounting 3 Hiring & HR 3 Productivity 3 Workflows & Automation 3

Strategy & The AI-Native Founder

Fundraising 6 Prompting 3 Building Your AI Stack 3 AI as a Thinking Partner 4

Everyday AI

Choosing Your AI Assistant 8 Learning with AI 7 Working with AI Agents 7 Using AI Safely 8 AI in Indian Languages 7
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