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. A structured course covering naming, color research, and logo generation end to end. skillshare.com Course Branding with AI: name your brand and design a strong logo with ChatGPT + Canva Ronny Hermosa (Skillshare)
  2. The same skill set with a certificate format if you prefer guided projects. coursera.org Course Name your brand and design a logo with ChatGPT + Canva Coursera
  3. A clear decision framework for the exact moment every founder faces: bolt on AI, ignore it, or rethink the product. founderprompts.com Article "Should we add AI?" Here is how to decide Vasil (Founder Prompts)
  4. The UX research heavyweights on why novelty chatbots harm products and what user value actually looks like. nngroup.com Article AI Features Must Solve Real User Problems Nielsen Norman Group
  5. A blunt scorecard of which AI product ideas changed user behaviour and which quietly flopped. a16z.com Article State of Consumer AI 2025: Product Hits, Misses, and What's Next a16z
  6. The canonical reframe: sell the finished work, not a 15% productivity tool, and your market gets 10-50x bigger. sarahtavel.com Article AI startups: Sell work, not software Sarah Tavel (Benchmark)
  7. Tavel pressure-tests her own thesis with what she has since seen in real AI startups. sarahtavel.com Article A few "Sell Work, Not Software" updated thoughts Sarah Tavel (Benchmark)
  8. The full transcript, including the memorable rule against force-feeding users AI they never asked for. cheekypint.substack.com Article Des Traynor on reinventing Intercom and avoiding "foie gras" features Cheeky Pint (Stripe)
  9. A rare honest post-mortem from a product team on which AI bets worked in production and which had to be killed. hex.tech Article Bitter lessons building AI products Hex
  10. Includes Carta's hard-won lesson on separating model behaviour from UX when shipping AI features. review.firstround.com Article The 30 Best Pieces of Company Building Advice We Heard in 2025 First Round Review
  11. A top consumer investor answers the exact question, drawn from hundreds of a16z Speedrun applications. x.com Thread "Does my new startup idea need to have AI in it?" Andrew Chen (a16z)
  12. A data company's candid recap of which of its own AI features users adopted and why. amplitude.com Article What We Learned Building AI Products in 2025 Amplitude
  13. A case study of an incumbent rebuilding around one AI feature that customers demonstrably pay for. bvp.com Article How Intercom navigated the AI paradigm shift Bessemer Venture Partners
  14. The sharpest counterargument you will read; know the backlash before you ship an unwanted AI feature. honest-broker.com Article The Force-Feeding of AI on an Unwilling Public Ted Gioia (The Honest Broker)
  15. A respected discovery coach documents what surprised her when she actually built an AI product herself. producttalk.org Article Building My First AI Product: 6 Lessons from My 90-Day Deep Dive Teresa Torres (Product Talk)
  16. Free, thorough, and taught by the engineer who wrote much of LangChain's RAG tooling. freecodecamp.org Course Learn RAG from Scratch (Python tutorial from a LangChain engineer) freeCodeCamp (Lance Martin, LangChain)
  17. The follow-on course for when your prototype RAG needs to survive real users. freecodecamp.org Course Production RAG with LangChain and Vector Databases freeCodeCamp
  18. The primary source for letting the model trigger your app's actions, the step from chatbot to feature. developers.openai.com Guide Function calling (OpenAI API docs) OpenAI
  19. Guaranteed-JSON responses ended a whole class of parsing bugs; read this before writing a parser. openai.com Article Introducing Structured Outputs in the API OpenAI
  20. Free structured course covering prompting, extraction, streaming, and tool calls in real product code. vercel.com Course Builders Guide to the AI SDK Vercel Academy
  21. Six practitioners condense a year of production LLM scar tissue into tactical advice. oreilly.com Article What We Learned from a Year of Building with LLMs (Part I) Eugene Yan, Hamel Husain, Jason Liu, Shreya Shankar, et al.
  22. The whole LLM-product stack in one thread; a map of every decision you will eventually face. x.com Thread Patterns for LLM systems: evals, RAG, fine-tuning, caching, guardrails Eugene Yan (Anthropic)
  23. The most-read O'Reilly book of 2025; the reference text once you outgrow tutorials. oreilly.com Guide AI Engineering: Building Applications with Foundation Models Chip Huyen
  24. An India-based walkthrough from API key to working app, aimed at non-ML developers. analyticsvidhya.com Guide Build Your First LLM Application: A Beginner's Tutorial Analytics Vidhya

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
eChai Partner Brands The partnership →