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
- 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
- 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
- 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
- 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
- 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
What founders use most, ranked by how many answers lean on it.
- The most-cited year-in-review; explains why the leader changes constantly and why lock-in is a trap. simonwillison.net Article Things we learned about LLMs in 2024 Simon Willison
- The essay that made evals a founder-level topic; failed LLM products almost always skipped this. hamel.dev Article Your AI Product Needs Evals Hamel Husain
- A free written masterclass version if you want the method without the course fee. aakashg.com Guide How to Master AI Evals: Step-by-Step with Hamel and Shreya Aakash Gupta (Product Growth)
- Gets your first automated eval running in under an hour. datacamp.com Guide Promptfoo Tutorial: A Hands-On Guide to LLM Evaluation DataCamp
- A current map of the eval tooling landscape so you pick once, correctly. braintrust.dev Article Best Prompt Evaluation Tools (Tested and Compared) Braintrust
- A conversational companion to Hamel's essay with concrete team workflows. humanloop.com Article Why Your AI Product Needs Evals, with Hamel Husain Humanloop
- Distils the conference's eval takeaways, including hunting implicit user feedback signals. vellum.ai Article Big Ideas from the AI Engineer World's Fair Vellum
- How to make your AI coding tools carry the eval workload for you. hamelhusain.substack.com Article Evals Skills for Coding Agents Hamel Husain
- Turning evals into a deploy gate so a bad prompt change never reaches users. braintrust.dev Article Best AI Eval Tools for CI/CD Pipelines Braintrust
- A vendor-neutral ranking to cross-check the tool vendors' own comparisons. techsy.io Article 8 LLM Eval Tools Ranked: No Product to Sell TECHSY
- A trusted independent voice explaining why iteration speed is the whole game. simonwillison.net Article Simon Willison on "Your AI Product Needs Evals" Simon Willison
- How to use one model to grade another without inheriting its biases. deepeval.com Article LLM-as-a-Judge: Top evaluation techniques and best practices Confident AI (DeepEval)
- A practical setup guide for automated judging, the technique that makes evals scale. agenta.ai Guide LLM as a Judge: Guide to LLM Evaluation Best Practices Agenta
- The clearest end-to-end explainer of why hallucinations happen and the layered defences that work. lakera.ai Guide LLM Hallucinations: Understand and Tackle AI's Most Persistent Quirk Lakera
- Separates factuality from faithfulness errors and matches each to its fix. getzep.com Article How to Reduce LLM Hallucinations Zep
- A prioritized playbook: grounding and abstention first, verification where errors are expensive. futureagi.com Article How to Reduce LLM Hallucinations: 7 Proven Strategies Future AGI
- Production-focused checklist including the stat that layered guardrails cut hallucination rates 71-89%. airbyte.com Article 8 Ways to Prevent LLM Hallucinations in Production Airbyte
- Schema-guaranteed responses kill an entire category of made-up fields and invalid values. developers.openai.com Guide Structured model outputs (OpenAI docs) OpenAI
- Connects structured output techniques across providers in one practical reference. agenta.ai Article The guide to structured outputs and function calling with LLMs Agenta
- How the two main open-source guardrail approaches compose into one defence stack. guardrailsai.com Article Guardrails AI and NVIDIA NeMo Guardrails: A Comprehensive Approach to AI Safety Guardrails AI
- The legal analysis of the ruling, in plain enough language for a founder. mccarthy.ca Article Moffatt v. Air Canada: A Misrepresentation by an AI Chatbot McCarthy Tetrault
- Breaks the failure into design decisions you can audit your own bot against. envive.ai Article Case Study of Air Canada's Chatbot Misleading on Bereavement Fares Envive
- Short, shareable summary for convincing your team that reliability is a legal issue too. aibusiness.com Article Air Canada Held Responsible for Chatbot's Hallucinations AI Business
- A PM-friendly decision guide with real cost and time estimates for each rung of the ladder. news.aakashg.com Article RAG vs Fine-tuning vs Prompt Engineering: The Complete Guide Aakash Gupta (Product Growth)
Playbooks
A goal, and the route through it a step at a time.