Early Adoptr

Your AI has a PhD in everything and the memory of a goldfish. It can help you write a pitch deck, analyse a contract, and draft a client proposal in the same afternoon, but open a new chat and you are back to square one, re-explaining yourself for what feels like the hundredth time, and it still never quite sounds like you.Rob Webster, founder of TAU Marketing Solutions, returns to Early Adoptr to explain exactly what is going wrong and how a simple file and folder structure fixes it. AI tools have a memory problem: they are smart but they forget everything between conversations, or drift off course when a chat runs too long. Rob, Jess, and Kyle dig into how to create files and build a folder structure that gives your AI permanent, reliable context about who you are and what you do, so you stop explaining yourself from scratch every session.What You'll LearnWhy AI behaves like a goldfish with a PhDThe 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/ Timestamps:00:00 Introduction03:47 Vibe Coding Insights with Rob Webster03:48 The Case for Getting Boring About AI08:23 Two Kinds of Context: Always On vs Load When You Need It10:50 Reintroducing Rob Webster12:57 The Goldfish with a PhD: Why AI Forgets Everything16:43 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 Your Files Should Live 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

Most non-technical business owners and founders assume that building software still requires a developer. You might use AI to sketch something out, but at some point you hand it to someone who actually knows what they're doing. For a lot of use cases in 2026, that assumption is out of date.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 itWhat the tool landscape looks like nowThe difference between the harness and the modelWhy the brief matters more now than ever What Claude Fable 5 is built for, and what the US government directive that suspended public access on 13 June 2026 means for you right nowWhy 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-adoptrResources :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 enterprise: https://martech.org/how-to-make-vibe-coding-sustainable-inside-the-enterprise/AI vibe coding boosts output but strains oversight: https://itbrief.co.uk/story/ai-vibe-coding-boosts-output-but-strains-oversightMCP, vibe coding and harness engineering: https://www.infoq.com/podcasts/mcp-vibe-coding-harness-engineering/Amazon AI coding outage review: https://www.fintechweekly.com/news/amazon-ai-coding-outage-reviewStack Overflow Developer Survey 2025: https://shiftmag.dev/stack-overflow-survey-2025-ai-5653/A quarter of startups in YC's current cohort have codebases almost entirely AI-generated: https://techcrunch.com/2025/03/06/a-quarter-of-startups-in-ycs-current-cohort-have-codebases-that-are-almost-entirely-ai-generated/Google: 75% of code is now AI-generated: https://www.businessinsider.com/google-ai-generated-code-75-gemini-agents-software-2026-4Get in Touchhello@earlyadoptr.aiTikTok: @early_adoptrInstagram: @early_adoptrYouTube: @early_adoptrLinkedIn: https://www.linkedin.com/company/early-adoptr/

We've all seen the stats. 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.If you're going to Cannes, make sure to check out the sessions that Nadia and Stefanie are running:Cannesversations Series - LIVE FROM CANNESYouTube Channel or LinkedIn for contextFor Cannes 2026 -  Cannesversations Interest Form The Digital Marketeer podcast: Follow 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 corporate AI challenges often exclude women without meaning toWhy 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 itTimestamps:00:00 Where's Kyle + Women & AI 03:23 Introductions: Nadia & Stefanie08:19 The Data on Women and AI Adoption10:55 How Women in Tech Engage with AI Differently12:02 The Perfectionism Problem15:36 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 Don't Be Afraid to Start: Final Advice for Women Using AIResources: 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

Running a smaller business or start up means you're also doing payroll. And chasing invoices. And trying to figure out if last month closed in the black, while also building a proposal that's due tomorrow and following up with the three leads who went quiet last week. Not to mention marketing! The admin never stops, and you're always the one doing everything.Anthropic's new Claude for Small Business package doesn't fix that, but it does something almost more useful. It runs your most time-consuming jobs directlly in 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-onboard Tools 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 layerWhat 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 issue to be aware ofHow to work out whether this is the right tool for you right nowRelated Episodes:Claude Skills: https://www.earlyadoptr.ai/episodes/claude-skills-explained-how-to-stop-repeating-yourself-in-every-sessionModel Context Protocol (MCP): https://www.earlyadoptr.ai/episodes/stop-switching-tabs-how-to-connect-your-ai-to-your-business-tools-safely-using-model-context-protocol-mcpClaude Co-Work: https://www.earlyadoptr.ai/episodes/claude-cowork-explained-can-ai-really-organize-your-files-and-dataReference 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:Timestamps: 00:00 What We've been Up To05:22 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 the Approval Step Is So Important17:52 Data Security: What Claude Can and Cannot See19:43 Understanding Permissions and Access Levels21:50 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 Cost Considerations for Small Businesses35:35 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 News: More Jobs News from Last Week56:25 Fifteen Street

AI layoffs are dominating the news, but the story being told isn't the full story. In this episode, Jess and Kyle break down what's really driving the cuts, and what it means for your job and your business.When Meta announced 8,000 job cuts, the coverage landed the same way it always does: AI is replacing people, the future is here. But the numbers don't support that story. Meta's savings from the cuts amount to roughly three billion dollars. 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 The Disconnect in AI Implementation33:52 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 The Skills Gap in Education42:29 Key TakeawaysResources: 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. In honour of Early Adoptr's first anniversary,  we thought it was worth stopping to take stock of what's changed in the last year. When we launched Early Adoptr, there was a pretty clear hierarchy, with ChatGPT was at the top, everyone else was catching up, and agents were something people talked about at conferences without anyone being entirely sure what they meant. Twelve months later, almost none of that is still true.In this episode, we take a proper look back at what actually changed. From the model landscape and the slow collapse of the "ChatGPT is the Google of AI" era, to reasoning becoming the baseline rather than the premium tier, to context windows going from a genuine operational headache to essentially a non-issue, the foundations shifted faster than most businesses could keep up with. We also get into what happened with agents once MCP — Model Context Protocol — gave them a shared language to work with, why agentic commerce looks completely different to how we predicted it would, what Answer Engine Optimisation means for any business that needs to be found online, and what has changed with the security picture once agents got access to real tools.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 teamsWhat the two-tier internet looks like in practice and why it mattersWhy 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-adoptr Get in Touch:hello@earlyadoptr.aiTikTok: @early_adoptrInstagram: @early_adoptrYouTube: @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 gents: 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 The Evolving Landscape of AI Security44:17 The Shift in AI Risks and Management48:26 From Subscriptions to Outcome-Based Pricing50:22 AI Regulation, Memory, and the GDPR Question Nobody's Asking Yet52:20 The Agent Debt Problem56:12 Where Does AI Go From Here?

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/

This is the second part of our interview with Rob Webster, who has spent over 20 years in media and marketing, ran data and technology at MediaCom for some of the world's biggest brands, built and sold a MarTech and AdTech consultancy, and now works with enterprise businesses on how they actually adopt AI.In this episode, Jess and Kyle talk to Rob about everything from navigating the messy middle to what the future of work for juniors, where AI should play in your business, what it means for how you hire and develop people, why so many organisations are stuck between experimenting and scaling, and what it actually takes to move forward.We also cover the OpenAI vs Elon Musk trial, and how South Africa's AI Policy offers a useful reminder to always check your citations.What You'll LearnHow to identify your best AI use cases by starting with outcomes rather than tasksWhy AI multiplies what you're doingHow junior employees can move faster and take on more accountability earlier when they have AI as a working layerHow smaller businesses are now better placed to train entry-level hires than they've ever been.Why real-world wisdom is the skill that can never be replaced.What the messy middle of AI adoption looks like in practice and why most organisations are stuck in itHow leaders can model AI adoption in a way that actually moves teams forwardTry 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 Intro & What We've Been Up To04:09 The 10,000 Foot View: Why You Should Start Broad Before Picking an AI Use Case10:42 What AI Means for Hiring and Training Junior Employees14:55 Why Smaller Businesses Can Now Compete on Talent Development16:20 Human in the Loop: Why Oversight Still Matters19:35 The Messy Middle: Why Most Businesses Get Stuck Between Testing and Scaling23:17 How Leaders Can Drive AI Adoption34:02 AI News of the Week: OpenAI vs Elon Musk34:31 AI Gone Wrong: South Africa's AI Policy Debacle37:55 Wrapping Up for the WeekResources:Rob Webster - https://www.linkedin.com/in/digitalstrategyleader/ TAU Marketing Solutions - https://taums.ai/ AI Agents in Media Planning and Buying: https://taums.ai/ai-agents-in-media-planning-and-buying/Judging the Coming Wave of Agentic Adtech: https://taums.ai/judging-the-coming-wave-of-agentic-adtech/Mastering the Messy Middle: https://taums.ai/mastering-the-messy-middle-with-a-balanced-approach-to-ai-implementation/10 Predictions for Marketing and AI in 2026 (Futureweek): https://futureweek.com/rob-webster-10-predictions-for-marketing-and-ai-in-2026/The AI Land Grab interview (AdWorldNews): https://www.adworldnews.com/news/robert-webster-tau-marketing-ai-land-grabGet in Touchhello@earlyadoptr.aiTikTok: @early_adoptrInstagram: @early_adoptrYouTube: @early_adoptr

It's here! The culmination of our series on agents, and if you've ever wondered how to make the most of the AI agents in your business (without a huge budget or a team of developers), this is the episode for you.This week on Early Adoptr, we are joined by Rob Webster, who has spent 25 years working at the intersection of data, machine learning, and marketing, including working on data and technology for brands like Dell, Tesco, and Coca-Cola. He now runs Tau Marketing Solutions, where he helps businesses adopt AI and build agents to solve real marketing problems. In this episode he joins Jess and Kyle and shares everything he has learned about making agents that actually work. From the "Fisher Price Agent" to building a daily action plan, the four components every working agent needs and why most agents fail, this episode is a goldmine of tips from years of experience.We also cover a major deal between SpaceX and Cursor, and what it tells us about where the real competition in AI is playing out right now.What You'll LearnThe two-prompt method Rob uses to turn a vague goal into a concrete daily action planThe four components every working agent needs and the reason most agent setups fail to produce useful outputWhy the most valuable skill in AI right now has nothing to do with technology, and how anyone can develop itWhat human-in-the-loop looks like as a working habit rather than a safety conceptHow to start with a "Fisher Price Agent"Rob's tips for getting unstuck when you hit a wallTry 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 What We've Been Up to This Week03:16 Interview with Robert Webster05:07 AI News: SpaceX and Cursor Deal05:47 Meet Rob Webster10:51 The Two-Prompt Method: Going from Vague Goal to Concrete Plan13:28 The Four Components Every Working Agent Needs18:14 Why Knowing What Good Looks Like Is the Real Skill20:26 Human-in-the-Loop in Practice26:20 Building a Co-CEO Agent: From Fisher Price to Advanced33:01 Where to Start If You Are Not Technical37:42 Takeaways40:07 AI News of the Week: SpaceX & CursorResources:Rob Webster - https://www.linkedin.com/in/digitalstrategyleader/ TAU Marketing Solutions - https://taums.ai/ AI Agents in Media Planning and Buying: https://taums.ai/ai-agents-in-media-planning-and-buying/Judging the Coming Wave of Agentic Adtech: https://taums.ai/judging-the-coming-wave-of-agentic-adtech/Mastering the Messy Middle: https://taums.ai/mastering-the-messy-middle-with-a-balanced-approach-to-ai-implementation/10 Predictions for Marketing and AI in 2026 (Futureweek): https://futureweek.com/rob-webster-10-predictions-for-marketing-and-ai-in-2026/The AI Land Grab interview (AdWorldNews): https://www.adworldnews.com/news/robert-webster-tau-marketing-ai-land-grabGet in Touchhello@earlyadoptr.aiTikTok: @early_adoptrInstagram: @early_adoptrYouTube: @early_adoptr