Early Adoptr

Last week, Kyle and special guest Sean debated whether Claude Code is worth switching to if you don't know how to code. The answer was: it depends. So Sean spent the following week finding out. In this episode, it's the second part of our interview with Sean. Kyle and Sean to go through what actually happened when Sean used Claude Code for a week, including the modes that made Claude Code manageable, the controls that give you more say over how it works, and where it still falls short of Cowork for everyday work. Plus, Jess is back from Cannes Lions with a round-up of what the advertising industry is saying about where AI is heading.Vibe Coding Series: Part 1 of Sean's interview: https://shows.acast.com/early-adoptr/episodes/claude-code-vs-cowork-what-non-technical-founders-need-to-knBasics of Vibe-coding: https://shows.acast.com/early-adoptr/episodes/vibe-coding-for-non-technical-founders-where-things-actuallyHow to set up your files & folders for vibe-coding: https://shows.acast.com/early-adoptr/episodes/your-ai-keeps-forgetting-everything-heres-how-to-fix-it-w-roHow to find Sean:https://breakthroughgrow.com/https://www.linkedin.com/in/seanbhardwaj/Use these links for a discount on the tools we recommend (and it supports the pod!)Wispr Flow - AI-powered voice dictation that works across every app on your desktop - https://ref.wisprflow.ai/early-adoptrGranola - The best AI meeting notes! New users get 100% off for their first month - https://www.granola.ai?via=early-adoptrIn this episode:How Claude Code's modes (plan, think, auto) work and which to reach forRunning several tasks at the same time and what it does to your output speedMonitoring and automation: setting Claude Code to act when something changesManaging how much effort Claude Code puts in and avoiding burning through your usageComparing Claude Code and Cowork: what each one is actually better atSean's week-long experiment switching exclusively to Claude CodeJess's round-up from Cannes Lions 2026 and what was different about AI conversations this yearTimestamps:00:00 - Introduction, Cannes Lions and the Claude Fable 5 update11:06 - What agents actually are in Claude Code13:26 - Plan mode, thinking mode and auto mode19:28 - How Claude Code can work on several things at once27:26 - Making the most of your Claude Code usage28:42 - Set it and forget it: monitoring with Claude Code31:05 - Why batching your focus time matters33:11 - Setting Claude Code to watch for something and act when it happens35:39 - The Claude Code controls that give you more say over how it works38:20 - How to stop Claude Code from using more than you need41:13 - Cowork vs Claude Code: Sean's verdict46:14 - Quick wins for non-technical users47:28 - Why Sean made the switch47:52 - One week in Claude Code: what actually happened50:28 - How to check in on a running Claude Code session from your phone53:20 - How skills work in Claude Code56:09 - Why thinking through what you want before Claude starts gets better results58:58 - When Claude Code overdoes it and Cowork is the simpler choice01:02:07 - Where AI tools like Claude Code are heading nextGet in Touchhello@earlyadoptr.aiTikTok: @early_adoptrInstagram: @early_adoptrYouTube: @early_adoptrLinkedIn: https://www.linkedin.com/company/early-adoptr/www.earlyadoptr.ai

AI has a memory problem. It is exceptionally capable within a session, helping you draft a pitch, review a contract, and write a client proposal in the same afternoon, but close the tab and it forgets everything. Open a new chat and you are back to square one, re-explaining who you are and what you do from scratch, every time, until it still never quite sounds like you.This week, Rob Webster, founder of TAU Marketing Solutions, joins Jess and Kyle to explain why this happens and how a simple file and folder structure gives your AI permanent, reliable context, so you stop losing ground at the start of every session.What You'll LearnWhy AI tools lose context between sessionsWhy folder-based context is better than any system promptThe difference between always-on context (the things permanently true about you, your role, and your business) and situational context you load in only for specific tasks or clientsHow to build a simple folder structure , what files to put in it, and how tools like Claude read that context automatically so you don't have to paste it in every timeHow to decide what information should live permanently in your files versus what's transitory context that should be removed once a project or idea is doneWhat "context drift" is and why long conversations degrade even when you've done the setup correctly — and how to catch it earlyHow this same folder structure becomes the foundation for more advanced AI work, including Claude Cowork and building your own AI agentsRob Webster - https://www.linkedin.com/in/digitalstrategyleader/ TAU Marketing Solutions - https://taums.ai/ Use these links for a discount on the tools we recommend (and it supports the pod!)Wispr Flow - AI-powered voice dictation that works across every app on your desktop - https://ref.wisprflow.ai/early-adoptrGranola - The best AI meeting notes! New users get 100% off for their first month - https://www.granola.ai?via=early-adoptrTimestamps:00:00 Introduction03:48 Why Boring AI Habits Beat Impressive Ones08:23 Two Kinds of Context: Always On vs Load When You Need It10:50 Reintroducing Rob Webster12:57 Why AI Forgets Everything Between Sessions16:43 What You're Losing Every Time You Open Claude Without Context22:37 Context Drift: Why AI Outputs Get Worse the More You Use It25:52 How to Start Giving Your AI Context About Who You Are32:01 Making It Stick: Naming Chats, Pinning Projects, Starting Your Folders35:28 What a Working Folder Structure Actually Looks Like37:04 Where to Store Your AI Context Files (Local vs Cloud)46:40 Global vs Project-Specific: The About Me Folder and Beyond53:47 How AI Reads Context56:12 How This Scales Into Agents, Claude Code, and Vibe CodingGet in Touchhello@earlyadoptr.aiTikTok: @early_adoptrInstagram: @early_adoptrYouTube: @early_adoptr

Vibe coding has made it possible to build working software without writing a line of code, and most non-technical founders haven't caught up with that yet. The assumption that you sketch something out with AI and then hand it to a developer is out of date for a lot of use cases. The tools have moved on, and this episode explains what that actually looks like now.Vibe coding was Collins Dictionary's Word of the Year for 2025, and it has moved well beyond the developer community. Founders, operators, and small business owners are using these tools to build working internal tools, automations, and web apps for themselves. The tools have matured to the point where knowing what to build and being able to describe it matters far more than knowing how to write the code.This episode is the first in a new series on vibe coding. Jess and Kyle cover what the tool landscape looks like today, which starting point fits your situation, how much the agent now does versus how much you need to manage, and what Anthropic's Claude Fable 5 means for where all of this is heading.If you've been curious about whether these tools are actually ready for someone without a technical background, this episode is the place to start.What You'll LearnWhy vibe coding has become genuinely usable for non-technical founders What the difference is between the tool you work in and the model underneath itWhich tools non-technical founders are actually building with - Cursor, Lovable, Bolt, Replit, and Claude Code - and how to decide where to startThe difference between the harness and the modelWhy clear briefs and good project management matter more than code when you're building with AI toolsWhat Claude Fable 5 is built forWhy the skills that matter most for building with AI in 2026 are the same ones you use when you brief a designer or hand a project to a team memberUse these links for a discount on the tools we recommend (and it supports the pod!)Wispr Flow - AI-powered voice dictation that works across every app on your desktop - https://ref.wisprflow.ai/early-adoptrGranola - The best AI meeting notes! New users get 100% off for their first month - https://www.granola.ai?via=early-adoptrTimestamps:00:00 Introduction08:51 Why We're Revisiting Vibe Coding14:19 Why Anthropic Is Building Both the AI Model and the Coding Tool15:01 How the Tool Landscape Has Changed Since Last Year25:42 What Fable 5 Changes for Vibe Coding (and Why You Can't Use It Right Now)30:42 How the Vibe Coding Workflow Has Changed32:11 What It Means That the Agent Now Runs the Whole Project, Not Just the Next Step37:54 What Your Role Actually Looks Like When the Agent Does More of the Work43:56 Persistent Agents: What They Are and Why They Matter for Vibe Coding50:01 What Non-Technical Founders Can Realistically Build Themselves Right Now54:39 Do You Still Need a Developer?55:18 Key Takeaways57:16 Wrapping Up for the WeekResources :Claude Code: https://claude.ai/codeCursor: https://cursor.comLovable: https://lovable.devBolt: https://bolt.newReplit: https://replit.comBase44: https://base44.comGitHub Copilot: https://github.com/features/copilotVellum: https://www.vellum.aiHow to make vibe coding sustainable inside the enterpriseAI vibe coding boosts output but strains oversightMCP, vibe coding and harness engineeringAmazon AI coding outage reviewStack Overflow Developer Survey 2025A quarter of startups in YC's current cohort have codebases almost entirely AI-generatedGoogle: 75% of code is now AI-generatedGet in Touchhello@earlyadoptr.aiTikTok: @early_adoptrInstagram: @early_adoptrYouTube: @early_adoptrLinkedIn: https://www.linkedin.com/company/early-adoptr/

Women are adopting AI tools at a 25% lower rate than men. 33% of men use AI daily at work versus 27% of women. Men are 23% more likely to be encouraged by their managers to try it, and 27% more likely to be praised when they do.Most of the conversation about women's lower AI adoption rates focuses on what women need to do differently. Instead, we're looking at the conditions that produced the gap in the first place, and why closing it matters far more than just productivity.This week on Early Adoptr, Kyle is away so Jess is joined by Nadia Koski, digital growth expert at The Marketeer Group, and Stefanie Beach, founder and CEO of The Marketeer Group, to get into what's actually driving the adoption gap and what women founders and small business owners can do about it. Because when women use AI tools less, that eventually shapes what the tools look like. It costs the economy. And it grows over time.We'll work through the stats, the barriers, and the guilt that comes with using AI at work. We also get into how to start without the overwhelm, the mental load, and why the caution women tend to bring to AI turns out to be an asset.The Digital Marketeer podcastFollow Nadia:Nadia Koski on LinkedIn: https://www.linkedin.com/in/nadiakoskiStill Human: Real Talk in the Age of AI Podcast: https://open.spotify.com/show/6xCZdhBOerROCuLatJoNay?si=FeYj2JidTtiA9xsREd9FtgFollow Stefanie:Stefanie Beach on LinkedIn: https://www.linkedin.com/in/stefanieg/Stefanie@TheMarketeerGroup.comwww.themarketeergroup.com Use these links for a discount on the tools we recommend (and it supports the pod!)Wispr Flow - AI-powered voice dictation that works across every app on your desktop - https://ref.wisprflow.ai/early-adoptrGranola - The best AI meeting notes! New users get 100% off for their first month - https://www.granola.ai?via=early-adoptrWhat You'll Learn: Why women are adopting AI tools at lower rates than men Why corporate AI training and rollouts tend to work better for men Why finishing a project faster with AI does not mean charging less for it, and why women are more likely to think it doesWhat a team leader needs to have in place before running internal AI training, and why protected experimentation time mattersWhy more women in their 40s are leaving corporate life for entrepreneurship, and what the AI revolution has to do with itWhy the caution women bring to AI tools is business advantageTimestamps:00:00 IIntroduction: Women and the AI Adoption Gap03:23 Introductions: Nadia & Stefanie08:19 The Data on Women and AI Adoption10:55 How Women in Tech Engage with AI Differently12:02 Why Women Set a Higher Bar Before Using AI15:36 How to Give Your Team a Safe Space to Try AI19:00 How to Actually Educate Yourself on AI21:13 Who Really Has Time to Learn AI24:31 Why the Founders Furthest Ahead on AI Have a Support Network at Home25:53 Why the AI Revolution Is Pushing More Women Into Entrepreneurship28:23 The Unpaid Work Research That Explains the Women's AI Adoption Gap29:46 Why Using AI to Brainstorm and Polish Your Work Is Not a Shortcut31:27 Fighting the Guilt and Redistributing the Mental Load as a Female Founder33:23 The Glass Cliff: Why Women Face Higher Stakes When AI Goes Wrong36:22 Why Doing Work Faster with AI Doesn't Mean You Should Charge Less38:20 What Workplaces Can Do to Give Women Equal Access to AI Learning42:45 Is Being Cautious About AI Actually a Business Advantage?47:24 Why Women Questioning AI Accuracy Is Good for Business47:39 How to Start Using AI Without the OverwhelmResources: Harvard Business School studyLean In studyWhy women aren't ‘missing’ the AI trainMalin Frithiofsson (Daya Ventures)Maya Betron (PowHer Data)Sinead Bovell Get in Touch:Email: hello@earlyadoptr.aiTikTok / Instagram / YouTube: @early_adoptrLinkedIn

Claude for Small Business is Anthropic's answer to the admin pile that never goes away. If you're running a small business or startup, you already know the problem: you're the one doing payroll, chasing invoices, building proposals, and following up with leads who went quiet, all at once, all the time. Claude for Small Business doesn't fix all that, but it does something almost more useful: it runs your most time-consuming jobs directly inside the tools you're already paying for, like QuickBooks, HubSpot, PayPal, Canva, and more.In this episode, Jess and Kyle get into what Claude for Small Business actually includes, how the workflows and skills fit together, what it looks like in practice, and what you need to know before you connect anything. If you've listened to our Cowork, Skills and MCP episodes, this is where those pieces click into place.They also give an update on last week's jobs episode, which already has multiple updates in the week since it was published.Full list of workflows & skills: https://claude.com/plugins/small-business The setup command: /smb-onboardTools we use:Wispr Flow - AI-powered voice dictation that works across every app on your desktop - https://ref.wisprflow.ai/early-adoptrGranola - The best AI meeting notes! New users get 100% off for their first month - https://www.granola.ai?via=early-adoptrWhat You'll LearnWhy Claude for Small Business isn't just another AI chatbot layerHow Claude asks for your approval before taking actionWhat Claude can do inside tools like QuickBooks, HubSpot, and PayPalWhat the 15 pre-built workflows are and what they actually doThe difference between a workflow (the full job you trigger) and a skill (the reusable technique running underneath it)How the approval model worksThe permissions and data access questions to answer before you connect anythingHow to decide whether Claude for Small Business is worth it at this stage of your businessTimestamps: 00:00 Introduction: Claude for Small Business Explained05:22 What Is Claude for Small Business?07:11 Understanding Connectors and Workflows09:33 Claude's Pre-Built Workflows and Skills: What's Included15:35 Why Claude Asks for Approval Before Acting on Your Data17:52 Data Security: What Claude Can and Cannot See19:43 Claude for Small Business: Permissions and Access Levels Explained21:50 Row-Level Access and How Permissions Actually Work23:23 Garbage In, Garbage Out: Why Data Quality Matters25:19 How to Set Up Claude for Small Business (Step by Step)31:02 Pros and Cons of Claude for Small Business33:20 Claude for Small Business: What It Costs and What You Get35:35 The Approval Mechanic: Smart Product Design or Speed Bump?36:31 How This Differs from ChatGPT and Microsoft Copilot37:25 Data Retention and Privacy: What You Need to Know43:33 Key Takeaways and How to Get Started with Claude for Small Business46:15 AI and Jobs — What's Changed This WeekRelated Episodes:Claude SkillsModel Context Protocol (MCP)Claude Co-WorkReference material:https://www.anthropic.com/news/claude-for-small-business https://www.forbes.com/sites/jodiecook/2026/05/24/run-your-whole-business-from-one-tab-with-claudes-new-update/ https://medium.com/@sebuzdugan/how-to-use-claude-to-automate-your-small-business-in-a-weekend-15c749aac5e0 https://www.technologyreview.com/2026/05/26/1137855/a-reality-check-on-the-ai-jobs-hysteria/https://fortune.com/2026/05/26/sam-altman-dario-amodei-walking-back-ai-jobs-apocalypse-prophecies-ipo/https://www.gov.ca.gov/2026/05/21/governor-newsom-signs-first-of-its-kind-executive-order-to-prepare-workers-and-businesses-for-potential-ai-disruption/https://fortune.com/2026/05/03/chinese-court-layoffs-workers-ai-replacement-labor-market/Get in Touch:Email: hello@earlyadoptr.aiTikTok: @early_adoptrInstagram: @early_adoptrYouTube: @early_adoptrLinkedIn:

AI layoffs are dominating the news, but the story being told isn't the full story. When Meta announced 8,000 cuts, the coverage landed the same way it always does. But Meta's savings from those cuts amount to roughly £3 billion, and their AI infrastructure spend this year runs to multiples of that. So what's actually going on?In this episode, Jess and Kyle work through the real economics behind the layoff headlines, from the infrastructure bets driving the cuts, to the compute costs that are now exceeding what companies spend on their own people, to the quietly alarming data on what's happening to early-career workers. They also cover the Musk v. Altman verdict, what it means for OpenAI's upcoming IPO, and why Anthropic keeps coming out looking like the adult in the room.The episode closes with practical guidance on what founders, team leaders, and employees can actually do right now, including why waiting to feel ready is the worst strategy available.What You'll Learn:Why Meta's 8,000 job cuts are better understood as a budget-clearing exerciseWhat AI washing is and how to spot it in a layoff announcementWhy infrastructure spending at Amazon, Meta, and Microsoft is projected to exceed total payroll costs by $50 billion this yearWhat MIT research actually found when it tested whether AI is economically viable compared to keeping humans in the roleWhy 43% of CEOs plan to reduce junior roles over the next two yearsWhy IBM's contrarian bet on junior hiring may look very smart in ten yearsWhy smaller businesses are better placed than large firms to make the same moveWhat AI fluency actually means in practiceTools we use and recommend:We only recommend tools we actually use. Both links below are affiliate links — if you sign up, it costs you nothing extra and helps support the show.Wispr Flow — AI-powered voice dictation that works across every app on your desktop - https://ref.wisprflow.ai/early-adoptrGranola — The best AI meeting notes! New users get 100% off for their first month.https://www.granola.ai?via=early-adoptrTimestamps:00:00 Introduction and Personal Updates04:58 Why the AI Layoff Headlines Don't Tell the Whole Story08:58 When Companies Cut Staff to Fund AI and Call It Efficiency18:16 How Meta Extracted Its Employees' Knowledge Before Letting Them Go22:40 Why the Productivity Gains Don't Justify the Scale of the Cuts28:12 When Running AI Costs More Than Paying Your Team29:58 MIT Research: AI Is Only the Cheaper Option in 23% of Cases32:14 Why Companies Are Cutting Jobs Before the AI Is Ready to Replace Them33:52 Why Junior Roles Are Being Cut First35:44 The Talent Pipeline Problem Nobody Is Planning For38:28 Redesigning Early-Career Roles Instead of Cutting Them40:27 What Schools Aren't Teaching About AI and Why It Matters for Junior Hires42:29 What Founders and Employees Can Actually Do Right NowResources: https://www.shrm.org/topics-tools/news/technology/ai-layoffs-transformation-scapegoathttps://www.linkedin.com/news/story/ceos-plan-to-reduce-junior-roles-8108505/https://www.forbes.com/sites/danrunkevicius/2026/05/20/meta-layoffs-signal-ai-bill-is-coming-due/https://fortune.com/2026/03/31/marc-andreessen-ai-layoffs-silver-bullet-excuse-overhiring/https://techcrunch.com/2026/05/19/openai-co-founder-andrej-karpathy-joins-anthropics-pre-training-team/https://www.bbc.co.uk/news/articles/cewpyv79pw1ohttps://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-in-the-enterprise.htmlhttps://www.pymnts.com/artificial-intelligence-2/2026/jpmorgan-prioritizing-ai-hires-over-bankers/https://fortune.com/2026/05/22/microsoft-ai-cost-problem-early%20adoptr%20-agents/www.moneycontrol.com/technology/mark-zukerberg-s-leaked-viral-audio-clip-suggest-meta-is-tracking-employees-to-train-ai-article-13924715.html

A year in AI doesn't feel like a normal year, it feels like about five. The AI landscape has shifted faster in the last twelve months than most businesses could track, let alone act on. For Early Adoptr's first anniversary, we're taking the opportunity to map what actually changed: the model landscape, the rise of MCP, what happened to agents, and what's worth paying attention to in the next twelve months. We close out with a look ahead at what's actually worth paying attention to: outcome-based pricing, orchestrated multi-agent systems reaching smaller businesses, and what we're calling agent debt, the accumulating consequences of workflows that were built in a hurry and haven't been stress-tested yet.Thanks for being with us for the last year, and here's to the next 12 months!What You'll LearnWhy reasoning models went from a premium add-on to the default , and what that shift enabled for agents and complex workflowsHow context windows grew from a operational constraint to a non-issue, and what that unlocks for businesses working with large volumes of documents, contracts, or correspondenceWhy smaller, more focused AI tools regularly outperform general-purpose models on the tasks they're built for, and what that means for how you structure your own stackWhat MCP actually solved and why it's the reason agents went from demo-quality to deployable for non-technical teamshat the two-tier internet is and why it decides whether AI recommends your business or your competitor's.Why ChatGPT's instant checkout failed commercially and what it tells us about how brands are learning to use AI for discoveryWhat AEO — Answer Engine Optimisation — means for any business that needs to be found onlineHow the security risk picture changed once agents got real access to real tools via MCPWhat agent debt isWhat outcome-based pricing meansResources and LinksAll previous episodes of Early Adoptr can be found here or via your podcast player of choice: https://shows.acast.com/early-adoptrTimestamps:00:00 What We've Been Up to This Week04:14 One Year of Early Adoptr: What We Got Right (and Wrong)06:27 The Model Landscape: Why ChatGPT Lost the Top Spot11:01 AI Pricing Is Changing — and Your Bill Is Going Up16:20 Context Windows: From Headache to Non-Issue20:03 When Smaller Is Better: The Case for Specialist AI Tools20:35 Use Cases for Small Language Models22:53 Agents: From Conference Buzzword to Actually Useful29:02 What MCP Did for the Agent Ecosystem31:29 Agentic Commerce and the Two-Tier Internet37:55 How Brands Are Using AI for Discovery Without Losing the Customer39:05 AI Security: How the Risk Picture Changed When Agents Got Real Access44:17 Prompt Injection, Data Leaks, and What to Actually Watch For48:26 From Subscriptions to Outcome-Based Pricing50:22 AI Regulation, Memory, and the GDPR Question Nobody's Asking Yet52:20 The Agent Debt Problem56:12 What's Worth Watching: AI Predictions for the Next 12 MonthsGet in Touch:hello@earlyadoptr.aiTikTok: @early_adoptrInstagram: @early_adoptrYouTube: @early_adoptr

Most people start their AI journey by asking how to save time. That is not a wrong question — but Anthropic's latest research, based on open-ended interviews with over 81,000 Claude users across 159 countries, suggests it may not be the most important one.The most commonly reported productivity gain in the study was not speed. It was scope. Not doing existing work faster, but doing things that you simply couldn't before, because of budget, skills, or just the assumption that certain capabilities belonged to someone else.This episode is about the difference between saving time with the boring middle and asking what is now possible that wasn't before, and why that second question is where the real opportunity lies.What You'll LearnWhy the Anthropic study's methodology is unusualThe difference between efficiency gains and capability gainsHow to identify your "boring middle" and what to do once you have sorted itHow to prevent your freed-up time from get absorbed back into more of the sameHow a delivery driver and landscape gardener from the illustrate capability gainsWhat the Pocket OS incident reveals about AI agent permissions, and the simple rule that would have prevented itTry GranolaIf you've ever sat in a meeting, taken what felt like decent notes, and then opened them afterwards and they didn't capture anything, Granola is the tool for you. It runs in the background, captures everything, and turns your notes into something you can actually use. Both Jess and Kyle use it, it plays really nicely with Claude, and it is one of our most highly recommended toolsNew users get 100% off their first month using our link: granola.ai?via=early-adoptrTimestamps:00:00 Introduction and Travel Plans01:37 About the Anthropic Research03:37 How the Study Actually Worked07:36 The Headline Productivity Stat10:35 The Four Types of Productivity Gain from AI11:54 What the Data Says About Job Displacement13:32 The Efficiency Game: What It Gets You and What It Misses16:45 Why Automating the Wrong Things Makes You Faster at the Wrong Things21:27 The Boring Middle: Why Consistency Is the Point25:00 Capability Gains: Doing Things That Were Previously Off the Table28:54 The Wrong Question: Efficiency vs. Capability31:39 How Efficiency and Capability Feed Into Each Other35:09 Practical Takeaways: What to Try This Week38:09 AI News of the Week: Lessons from Pocket OS IncidentResources:What 81,000 people told us about the economics of AI: https://www.anthropic.com/research/81k-economics https://www.linkedin.com/posts/oguzaliacar_anthropic-just-published-findings-from-80000-activity-7440462065959366657-IqJj/ https://medium.com/activated-thinker/an-ai-interviewed-81-000-people-what-it-discovered-exposes-our-deepest-insecurities-c231c7d2f77e https://www.reddit.com/r/AI_Agents/comments/1ssz7v3/anthropic_surveyed_81000_claude_users_about_ais/Get in Touch:hello@earlyadoptr.aiTikTok: @early_adoptrInstagram: @early_adoptrYouTube: @early_adoptrWhat 81,000 people told us about the economics of AI: https://www.anthropic.com/research/81k-economics https://www.linkedin.com/posts/oguzaliacar_anthropic-just-published-findings-from-80000-activity-7440462065959366657-IqJj/ https://medium.com/activated-thinker/an-ai-interviewed-81-000-people-what-it-discovered-exposes-our-deepest-insecurities-c231c7d2f77e https://www.reddit.com/r/AI_Agents/comments/1ssz7v3/anthropic_surveyed_81000_claude_users_about_ais/