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 cheapest same-day option: scrape your site, upload docs, embed a working support bot in under an hour. chatbase.co Guide How to Create a Chatbot: Build Your AI Bot for Free Chatbase
  2. Proof that even an enterprise deployment went start-to-live in one month, with the rollout steps visible. decagon.ai Article Decagon case study: Duolingo English Test Decagon
  3. The famous open-sourced prompt playbook powering support for Perplexity and Replit, a masterclass in agent prompting. parahelp.com Article AI prompt design at Parahelp Parahelp (YC)
  4. Answers the setup gotchas founders hit in week one, from content import times to channel coverage. intercom.com Guide Fin AI Agent FAQs Intercom
  5. 50 real workflows, several of them exactly this: dump support transcripts in, get validated product hypotheses out. lennysnewsletter.com Article Everyone should be using Claude Code more Lenny Rachitsky
  6. A hands-on course from a user-research veteran on turning raw feedback corpora into decisions with Claude Code. maven.com Course Claude Code for Customer Insights Caitlin Sullivan
  7. Notion cut its monthly user-insights report from 2 weeks to 3 days by unifying tickets with every other signal. enterpret.com Article How Notion supercharges its product feedback loop using Enterpret Enterpret
  8. The founder story behind feedback intelligence and why Canva, Figma and Notion all bought it. notoriousplg.ai Article Notorious: How Enterpret Disrupted the Customer Intelligence Space Zachary DeWitt (NotoriousPLG)
  9. A concrete recipe for pattern-mining feedback with Claude, straight from the model maker. claude.com Guide Analyze patterns in user feedback Anthropic
  10. An Indian fintech at scale showing how LLM ticket categorization went from 60% to 85% accuracy and feeds product fixes. engineering.razorpay.com Article Enhancing Customer Support through AI-powered ticket issue categorization Razorpay Engineering (Swati Agarwal)
  11. Practical CS-side workflows for mining tickets, NPS and usage data, written for operators not engineers. gtmaipodcast.com Article Claude Code for Customer Success J Moss (GTM AI Podcast)
  12. Includes Gumloop's real workflow that root-causes support complaints and links back to the raw conversations. lennysnewsletter.com Article Make product management fun again with AI agents Tal Raviv (Lenny's Newsletter)
  13. A CFO's-eye view of why $0.99 per resolution worked, and what that means for you as the buyer. mostlymetrics.com Article How Intercom Reaccelerated Growth With Outcome-Based Pricing CJ Gustafson (Mostly Metrics)
  14. Intercom's own definitions of the four billable outcome types, the fine print your invoice depends on. intercom.com Guide Fin AI Agent outcomes Intercom
  15. A worked cost example at startup ticket volumes, useful for a quick back-of-envelope. featurebase.app Article How Much Does Intercom's Fin AI Cost? Featurebase
  16. The landmark ruling every founder should know: you are legally liable for what your bot invents. forbes.com Article What Air Canada Lost In 'Remarkable' Lying AI Chatbot Case Forbes (Marisa Garcia)
  17. Runnable input/output guardrail patterns, including the accuracy-latency-cost tradeoffs. developers.openai.com Guide How to implement LLM guardrails OpenAI Cookbook
  18. A concrete notebook for building a hallucination checker in front of customer-facing answers. developers.openai.com Guide Developing Hallucination Guardrails OpenAI Cookbook
  19. The most-cited engineering guide on keeping agents simple, bounded, and predictable. anthropic.com Guide Building Effective AI Agents Anthropic
  20. How to trace exactly why your agent said what it said, the daily practice behind trust. intercom.com Guide Debug Fin AI Agent answers Intercom
  21. Defines a real resolution (accurate, complete, no follow-up) so you don't ship a bot that fakes its own metrics. zendesk.com Guide What is AI resolution rate and how to measure it Zendesk
  22. Realistic benchmark ranges by deployment maturity, an antidote to vendor headline numbers. notch.cx Article AI Customer Support Resolution Rate Benchmarks 2026 Notch (Elool Jacoby)
  23. An opinionated operator take: track resolution rate, not deflection, or an abandoning customer counts as a win. lorikeetcx.ai Article Customer Service Metrics That Actually Matter Lorikeet
  24. The CX-professional lessons from Cursor: monitoring, handoffs, and transparency about AI. cxnetwork.com Article Chatbot hallucination at Anysphere sparks customer backlash CX Network

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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