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 360 answered questions on putting AI to work.

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. Argues for outbound that feels like inbound, the tone that works for Indian founders in US inboxes. expandusbusinesscoaching.com Article Inbound vs Outbound for US Sales from India: What Works ExpandUS
  2. Short mainstream interview connecting product lessons to global selling from India. forbesindia.com Podcast Srikrishnan Ganesan on vital market lessons in SaaS product development Forbes India
  3. The clearest outside teardown of how betting the company on an AI support agent took Fin from $1M to $100M+ ARR. growthunhinged.com Article Intercom's decisive bet on AI Kyle Poyar (Growth Unhinged)
  4. Taylor connects AI support resolution to the deeper shift from selling software to selling outcomes. sequoiacap.com Podcast How AI is Reinventing Software Business Models ft. Bret Taylor Sequoia Capital Training Data
  5. A grounded profile of Decagon with real customer names and numbers, useful for calibrating the hype. forbes.com Article This 28-Year-Old AI Founder Thinks His Customer Service Startup Can Beat Out Companies 10x His Size Forbes (Rashi Shrivastava)
  6. Survey of 2,400+ support teams showing real adoption and resolution numbers, not vendor marketing. intercom.com Guide 2026 Customer Service Transformation Report Intercom
  7. Concrete numbers from a product founders know: 34% faster resolution and a 3.4% ask-for-human rate. decagon.ai Article Decagon case study: Notion Decagon
  8. The category-defining AI support agent; its public resolution benchmarks set the bar everyone quotes. fin.ai Tool Fin by Intercom Intercom
  9. A punchy data-backed post on Fin's jump from 25% to 65% resolution, good for the 'can it really' skeptics. linkedin.com Thread The AI growth re-acceleration at Intercom Kyle Poyar
  10. The step-by-step for putting an AI agent live on chat first. intercom.com Guide Deploy Fin AI Agent over chat Intercom
  11. How to write tone, escalation and policy rules in plain language, which is most of the week's work. intercom.com Guide Provide Fin AI Agent with specific guidance Intercom
  12. 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
  13. 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
  14. 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
  15. 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)
  16. The reference tool for this workflow: feedback from every source unified and auto-tagged into roadmap-ready themes. enterpret.com Tool Enterpret Enterpret
  17. A concrete recipe for pattern-mining feedback with Claude, straight from the model maker. claude.com Guide Analyze patterns in user feedback Anthropic
  18. 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)
  19. 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)
  20. 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)
  21. 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)
  22. The primary source: current plan plus per-resolution pricing to plug into your own cost model. intercom.com Tool Intercom Pricing Intercom
  23. 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
  24. 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

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

Research & Knowledge

Marketing & Growth

Sales & Customers

Operations & Back-office

Strategy & The AI-Native Founder

Everyday AI

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