Early Adoptr: Simplifying AI For Founders & Small Businesses

Early Adoptr
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  • Technology
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Early Adoptr is the weekly AI podcast for founders and small-business owners who are curious about the technology and want to put it to work, without needing a technical background. Hosted by Jess and Kyle, the show gets into the questions behind the headlines: What can you trust AI to handle? Could you build something yourself? Is that new tool worth paying for? And what on earth is an agent harness? From explaining technical ideas to trying tools and exploring business applications, Jess and Kyle help you make sense of AI and what you could do with it. Understand the AI. See the possibilities. Decide what’s useful. New episodes every week on Apple Podcasts, Spotify, YouTube and wherever you listen. Hosted on Acast. See acast.com/privacy for more information.

  1. 6h ago

    Jev AI: Can a Model That Can’t Write Save You Money?

    What if the next AI model your business needs can’t write, chat, code or explain itself? Jev, the new AI model from San Francisco startup TypeSafe AI, picks from answers you provide. Could that make it useful for your business? Sorting support emails, flagging urgent requests and screening job applications can take hours every week, and paying a general chatbot to repeat those tasks can add up. Jev is built for these quick decisions and could reduce the cost of handling them at volume. n this week’s episode, Jess and Klye explain why everyone is talking about Jev, what it can and can’t do, and how to test it before you rely on it. We also cover the jobs it suits, and how you can start using it. Which AI Model Should You Use? AI Model Families Explained - https://earlyadoptr.ai/episodes/which-ai-model-should-you-use-ai-model-families-explained 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-adoptr Granola - The best AI meeting notes! New users get 100% off for their first month - https://www.granola.ai?via=early-adoptr Timestamps: What You'll Learn: What the Jev AI model is and how it differs from ChatGPT and ClaudeWhere AI classification and confidence scores fit into business automationHow combining specialist AI models with chatbots could reduce costsWhat Jev’s limitations and data privacy policies mean for your businessHow to define a task and test AI decisions before automating themHow businesses could access Jev through existing software and automation toolsWhat the Character.ai bankruptcy reveals about AI business costs and profitability Resources: How I AI: 8 Real Jev Use Cases - https://www.lennysnewsletter.com/p/how-i-ai-8-real-jev-use-cases-howJev YouTube Comment Analysis: https://www.chatprd.ai/how-i-ai/workflows/jev-youtube-comment-analysisJev Explained: Demos and Use Cases - https://www.youtube.com/watch?v=QbYBRjOaGOoJev: TypeSafe's System One Model That Never Hallucinates - https://www.datacamp.com/blog/system-one-models-jevJev Explained: Typesafe AI's Non-Autoregressive System-1 Model - https://www.mindstudio.ai/blog/jev-system-one-model-launchBuilding a Harness with Jev - https://www.langchain.com/blog/building-a-harness-with-jevJev: 8 real use cases this fast, cheap model - https://www.youtube.com/watch?v=dAIIaepNhQM Get in Touch hello@earlyadoptr.ai TikTok: @early_adoptr Instagram: @early_adoptr YouTube: @early_adoptr LinkedIn: https://www.linkedin.com/company/early-adoptr/ www.earlyadoptr.ai Get in touch with Early Adoptr: hello@earlyadoptr.ai Follow Us on Socials & Resources: IG: https://instagram.com/early_adoptr TikTok: https://tiktok.com/@early_adoptr YouTube: https://www.youtube.com/@early_adoptr Substack: https://substack.com/@earlyadoptrpod Hosted on Acast. See acast.com/privacy for more information.

  2. Oct 21

    Building Products with AI Without Losing Human Judgement | w/ Ben Bilbrough

    AI makes it easier to build a product, change your mind and start again. But when you can turn an idea into something usable over a weekend, it’s easy to fall in love with what you’ve made before you’ve worked out whether anyone needs it. In this week’s episode, Jess and Kyle speak with serial founder Ben Bilbrough about building products with AI. His latest project, U26.vote, helps Americans understand the potential influence of their vote, but his experience offers practical lessons for anyone using AI to turn an idea into a business. Ben shares how his team used AI to process complex data, develop ideas and iterate quickly—and where human expertise remained non-negotiable. They discuss what happens when Claude sounds right but isn’t, why easier development doesn’t always lead to better products, and how to keep a team focused when changing direction takes so little effort. From the freedom to scrap your own work to the risks of falling in love with it, we explore what AI changes about product development, what it doesn’t, and why knowing what not to build matters more than ever. Ben Bilbrough: https://www.linkedin.com/in/ben-bilbrough/ U26.vote: https://u26.vote/ ActionTank.io: https://actiontank.io/ Boardy: https://www.boardy.ai/ What You’ll LearnHow small teams can use AI to build products and iterate fasterWhy the freedom to scrap your work can be both an advantage and a riskWhere human expertise remains non-negotiable when building with AIWhy vibe coding makes it easier to skip the questions that matterHow to keep your team and your AI focused when changing direction is easyWhy falling in love with the problem matters more than falling in love with your product 00:44 Weekly Catch-Up 05:02 This Week: What It Takes to Build Something Useful with AI 09:23 Introduction to Ben Bilbrough 12:42 Ben's Background in SMB and the Wedding Industry 14:17 The Knot, AOL and Ben’s First Exit 16:16 Why Ad Tech Treats Us as Consumers 18:26 How Nonprofits Can Ask Supporters for More Than Money 21:28 Understanding Voter Engagement and Political Influence 23:25 U26.vote: Scoring the Power of Your Vote 26:40 Building U26.vote With AI 31:50 AI as a Force Multiplier 37:05 Who Do You Need in the Room When Building With AI? 40:31 Users Never Behave the Way You Think They Will 43:26 The Role of Domain Experts in AI Development 45:48 How to Reduce AI Hallucinations in a Real Product 48:29 Why Fast Iteration Needs Guiding Principles 54:49 Finding Focus: The Problem Before the Product Get in touch with Early Adoptr: hello@earlyadoptr.ai Follow Us on Socials & Resources: IG: https://instagram.com/early_adoptr TikTok: https://tiktok.com/@early_adoptr YouTube: https://www.youtube.com/@early_adoptr Substack: https://substack.com/@earlyadoptrpod Hosted on Acast. See acast.com/privacy for more information.

  3. Oct 14

    Open Weight vs Open Source AI: What the Adobe Clones Mean for Your AI | Re-release

    When does it make sense to stop renting your tools and start owning more of them? With the recent news that a developer used AI to create free open source versions of popular tools like Adobe’s Photoshop and Microsoft Word, we thought it was timely to re-release our episode on open weight models, because the concept is similar. Just like open source tools, open weight models can give your business more control over AI costs, data privacy and the tools you depend on. But what would you give up to get it? In this week's episode, Jess and Kyle get into what open weight models are, how they differ from closed models like ChatGPT and Claude and from open source, and why the real distinction comes down to access, control and cost rather than anything too technical. They cover the licensing terms to watch, the three ways to run a model and when fine-tuning a small model for one repeatable job beats a big general model on both cost and accuracy. Open weight models aren't something you need toswitch to tomorrow, but one to have on your radar as AI works its way into more of how your business runs. Local AI episode: https://earlyadoptr.ai/episodes/local-ai-how-to-run-private-low-cost-ai-on-your-own-computer "Software is over": Bold AI developer takes aim at Adobe with open source clones: https://arstechnica.com/ai/2026/10/software-is-over-bold-ai-developer-takes-aim-at-adobe-with-open-source-clones/ Llama: https://ai.meta.com/blog/large-language-model-llama-meta-ai/ Qwen: https://qwen.ai/home Gemma: https://deepmind.google/models/gemma/ Phi: https://huggingface.co/microsoft/phi-4 Groq: https://groq.com/ Together AI: https://www.together.ai/ What You'll Learn What open weight models are, and how they differ from both closed models and open sourceThe three ways to run one: your own machine, a hosted provider, or your own cloudWhat the licensing terms actually let you do, and when they start to matterWhen fine-tuning a small model for a repeatable task beats a big general model on cost and accuracyA simple framework for deciding when open weight is the right call, and when ChatGPT or Claude still wins Timestamps: 00:43 Why We’re Re-Releasing Our Open Weight AI Models Episode 03:06 Open Source vs Open Weight: How Both Reduce Your Dependence on One Supplier 05:37 Open Source Software and AI: Less Lock-In, More Competition 07:54 Why More Businesses Are Moving to Open Weight AI Models 12:21 Location vs Access: How Open Weight Goes Beyond Local AI 14:54 Why It Matters Now: Reducing Your Dependence on the Big AI Providers 16:54 What an Open Weight Model Actually Is 19:12 How Open Weight Differs From Open Source 24:05 What the Licence Lets You Do With an Open Weight Model 25:29 Why Your Subscription Price Hides the Real Cost of AI 28:32 How Flat Subscriptions Compare to Pay-As-You-Go API Costs 31:03 Control and Privacy Over Where Your Data Goes 34:54 The Three Ways to Run an Open Weight Model 38:18 Using a Model Off the Shelf or Fine-Tuning It 42:22 Llama and Qwen, the Best-Known Open Weight Models 44:02 Emerging AI Models and Their Capabilities 46:34 The Framework for Choosing a Model 51:52 How AT&T Fine-Tuned a Small Model to Sort Call Summaries 53:37 When to Start Considering an Open Weight Model Resources: https://www.wsj.com/cio-journal/why-at-t-is-betting-big-on-open-weight-ai-a0ea03b1https://medium.com/@bhagyarana80/why-open-weight-models-matter-more-than-you-think-1d1d8787a4fehttps://mitsloan.mit.edu/ideas-made-to-matter/ai-open-models-have-benefits-so-why-arent-they-more-widely-usedhttps://www.lawfaremedia.org/article/knives-are-out-for-open-weight-ai-modelshttps://www.forbes.com/sites/alexanderpuutio/2026/08/14/theres-inflation-and-then-theres-whatever-a-1100-increase-is/https://www.gumloop.com/blog/open-weight-vs-open-sourceGet in touch with Early Adoptr: hello@earlyadoptr.ai Follow Us on Socials & Resources: IG: https://instagram.com/early_adoptr TikTok: https://tiktok.com/@early_adoptr YouTube: https://www.youtube.com/@early_adoptr Substack: https://substack.com/@earlyadoptrpod Hosted on Acast. See acast.com/privacy for more information.

  4. Oct 7

    Which AI Model Should You Use? AI Model Families Explained

    Every new AI model claims to be the best—but best at what? If you’re choosing between different AI model families, the newest and most powerful option may not be the right one for the job. As OpenAI and Anthropic release growing families of AI models, choosing the newest or most expensive option no longer guarantees the best result. Different models are now designed for complex reasoning, everyday work and high-volume routine tasks, and using the wrong one can waste money, consume your usage allowance and produce worse output. In this week’s episode, we explain how to choose the right AI model for each job, why model pricing affects the software your business uses, and what cached context and benchmark scores actually tell you. We also discuss the different strengths of Claude and ChatGPT, before looking at OpenAI Dots and Meta's Muse, the new personal AI agents competing for access to your email, calendar and business tools. AI Agent Harness episode: https://earlyadoptr.ai/episodes/what-is-an-ai-agent-harness-how-better-ai-setup-makes-agents-more-reliable What You’ll Learn How to match premium, everyday and high-volume AI models to different types of workWhy the most powerful AI model is not always the best model for the jobHow model pricing, usage limits and cached context affect businesses and individual usersWhat AI benchmark tests measure—and why the headline scores can mislead youWhy the tools, data and agent harness around a model can matter more than the model itselfWhat OpenAI Dots and Meta Muse reveal about the next generation of personal AI agents Timestamps: 00:43 Introduction and Weekly Updates 03:23 The Latest OpenAI, Anthropic and Google AI Model Releases 06:08 AI Model Families Explained 08:33 How to Choose the Right AI Model 11:32 How AI Model Pricing Affects Your Costs 13:04 OpenAI and Anthropic Model Tiers Explained 15:07 AI Usage Limits and Context Caching 17:51 Why the Most Powerful AI Model Isn’t Always Best 28:13 How AI Context Caching Works 32:38 Can You Trust AI Benchmark Tests? 35:54 Why the AI Model Is Only Part of the Picture: Why the AI Agent Harnesses Matters 38:51 Why Claude and ChatGPT Feel Different 46:24 AI News of the Week: Here Come the Personal Agents https://www.reddit.com/r/codex/comments/1wopzcz/gpt6_luna_sol_or_astra_heres_what_id_use/https://www.tomsguide.com/ai/chatgpt-6-or-claude-opus-5-5-heres-which-ai-id-use-for-writing-planning-and-5-other-everyday-taskshttps://www.youtube.com/@howiaipodcasthttps://artificialanalysis.ai/articles/claude-opus-5-5https://venturebeat.com/technology/anthropic-releases-claude-opus-5-5-beating-fable-5-1-on-key-agentic-benchmarks-at-60-cheaper-api-pricehttps://aibusiness.com/generative-ai/openai-takes-ai-price-war-next-level-gpt-6-sol-luna-pricinghttps://app.therundown.ai/guides/claude-opus-5-5-vs-opus-5-vs-fable-5-1https://www.chatprd.ai/how-i-ai/claude-opus-5-5-reviewhttps://www.vellum.ai/blog/gpt-5-6-sol-terra-luna-explainedhttps://venturebeat.com/technology/anthropic-launches-claude-sonnet-5-5-with-30-cost-reduction-per-task-due-to-faster-speeds-and-fewer-tool-callsGet in touch with Early Adoptr: hello@earlyadoptr.ai Follow Us on Socials & Resources: IG: https://instagram.com/early_adoptr TikTok: https://tiktok.com/@early_adoptr YouTube: https://www.youtube.com/@early_adoptr Substack: https://substack.com/@earlyadoptrpod Hosted on Acast. See acast.com/privacy for more information.

  5. Sep 30

    Has Claude’s Output Got Worse? Here’s What You Can Control | Re-release with Rob Webster

    Claude’s output has felt harder to work with recently. It ignores instructions, produces overlong, overwritten answers and can get worse over a long conversation. But if you want to improve your AI output, the answer might just be sitting in your Documents folder. In this re-released episode, Jess and Kyle speak with Rob Webster, founder of TAU Marketing Solutions, about managing AI context. The tools and product names may be moving fast, but the practical problem has not changed: AI performs better when it has clear, well-managed context. In this episode, Rob explains how to set up a few plain text files and folders so your AI knows who you are, what you do and what good looks like before you type a word. He also explains why giving your AI everything at once tends to make answers worse, how to spot when your setup has got bloated, and why the same files are the foundation for Claude Code and AI agents. Follow Rob: LinkedIn: https://www.linkedin.com/in/marketingaivisionary/TAU Marketing Solutions: https://taums.ai/ What You'll Learn Why AI forgets instructions in long conversations, and how better context can improve outputThe difference between persistent and situational contextHow to organise plain-text and Markdown context filesWhy more connected documents do not always produce better AI answersWhat to retain permanently and what to remove when a project endsHow to identify context drift earlyWhy this approach provides a foundation for Claude Code, Claude Cowork and AI agents Timestamps: 00:43 Introduction and Weekly Updates 03:09 Claude’s Output Has Got Worse, So We’re Revisiting Our Setups 11:12 Markdown Files and the Two Types of AI Context 14:24 Reintroducing Rob Webster 16:31 The Goldfish with a PhD: Why AI Forgets Everything 20:17 What You're Losing Every Time You Open Claude Without Context 26:11 Context Drift: Why AI Outputs Get Worse the More You Use It 29:26 How to Start Giving Your AI Context About Who You Are 35:35 Making It Stick: Naming Chats, Pinning Projects, Starting Your Folders 39:02 What a Working Folder Structure Actually Looks Like 40:38 Where Your Files Should Live 50:14 Global vs Project-Specific: The About Me Folder and Beyond 57:21 How AI Reads Context 59:47 How This Scales Into Agents, Claude Code, and Vibe Coding Resources: https://tech-insider.org/anthropic-engineer-claude-writing-quality-worse-2026/https://news.ycombinator.com/item?id=49348163Get in touch with Early Adoptr: hello@earlyadoptr.ai Follow Us on Socials & Resources: IG: https://instagram.com/early_adoptr TikTok: https://tiktok.com/@early_adoptr YouTube: https://www.youtube.com/@early_adoptr Substack: https://substack.com/@earlyadoptrpod Hosted on Acast. See acast.com/privacy for more information.

  6. Sep 23

    How RAG Works: Turn Internal Knowledge Into Better AI Answers

    Your business already has the answers. The problem is that nobody can find them. But RAG (retrieval-augmented generation), can help with that. In this week’s episode, Jess and Kyle unpack RAG — retrieval-augmented generation — the method that lets an AI model retrieve relevant information from a defined set of documents, databases or research before it generates an answer. From product information and policies to research archives, client documentation and company knowledge, RAG can give an AI assistant the context it needs to answer questions using the information you have chosen. They cover how RAG works, why it differs from fine-tuning, the role of chunking, embeddings, vector databases and citations (but don't be worried by the jargon!), and how to start with a smaller RAG project before building something more sophisticated. They also discuss the biggest AI news story of the year, and the practical AI governance decisions businesses can make now. You’ll learn: What RAG is and how retrieval-augmented generation worksThe difference between RAG and AI fine-tuningHow AI retrieves relevant context from business documents and databasesChunking, embeddings, vector databases, semantic search and citations — explained without the technical overloadWhy current, well-structured documentation matters for reliable AI answersCommon RAG problems, including outdated information, duplicate documents and missing contextHow to start with a smaller RAG project before building a more sophisticated AI knowledge base or internal AI assistant Nishma Patel Robb: https://www.linkedin.com/in/nishmapatelrobb/ Timestamps: 00:43 What We've Been Up To This Week 03:29 What Is RAG (Retrieval Augmented Generation) 07:23 Why General Chatbots Get Your Business Wrong 10:03 How RAG Works Under the Hood 11:49 Chunking: How RAG Breaks Your Documents Into Pieces 12:59 Embeddings and the Vector Database, Explained 15:23 Citations: How RAG Shows Its Sources 16:13 RAG vs Fine-Tuning: What's the Difference 18:25 Real-World RAG: Onboarding and Shared Team Knowledge 23:06 Real-World RAG: Making a News Archive Searchable 30:18 Optimizing Onboarding Processes with AI 30:54 Why RAG Is Really a Documentation Problem 31:30 The Importance of Documentation in RAG Systems 33:22 Creating a Single Source of Truth 34:51 Ensuring Consistency in Data 36:23 Understanding AI Limitations and Hallucinations: RAG Failure Modes 40:34 How RAG Handles Conflicting Documents and Version Control 43:30 Abstention: Why RAG Should Admit It Doesn't Know 44:59 How to Build a Simple RAG With Claude, ChatGPT or NotebookLM 48:24 Scaling RAG Systems for Larger Teams 49:25 Takeaways 51:03 AI News: Dario Amodei on Slowing the AI Frontier Resources: https://towardsdatascience.com/the-ultimate-guide-to-rags-each-component-dissected-3cd51c4c0212/https://bytevagabond.com/post/how-to-build-enterprise-ai-rag/https://medium.com/aingineer/a-complete-guide-to-implementing-hybrid-rag-86c0febba474https://arxiv.org/html/2403.01432v3https://www.ibm.com/think/topics/multimodal-raghttps://memgraph.com/blog/what-is-rag Get in Touch hello@earlyadoptr.ai TikTok: @early_adoptr Instagram: @early_adoptr YouTube: @early_adoptr LinkedIn: https://www.linkedin.com/company/early-adoptr/ www.earlyadoptr.ai Get in touch with Early Adoptr: hello@earlyadoptr.ai Follow Us on Socials & Resources: IG: https://instagram.com/early_adoptr TikTok: https://tiktok.com/@early_adoptr YouTube: https://www.youtube.com/@early_adoptr Substack: https://substack.com/@earlyadoptrpod Hosted on Acast. See acast.com/privacy for more information.

  7. Sep 16

    Beyond AI Slop: Generative AI, Taste & Creative Judgment (w/ Tom Evans)

    Is AI making creative work better, or just making more of it? AI can now create ads, social posts, images and campaign ideas in seconds. But when everyone can produce polished content at scale, how do brands avoid generic AI output, and more importantly....still make work that actually stands out? In this episode of Early Adoptr, Jess and Kyle are joined by Tom Evans, founder of brand consultancy BigSmall, to explore where generative AI genuinely helps creative people and where it risks producing more generic, forgettable content. The conversation moves beyond the usual “AI will replace creatives” debate. Instead, it looks at AI as a fast, strange and endlessly available thinking partner...a way to test half-formed thoughts, explore unexpected directions, prototype ideas and close the gap between “what if?” and a tangible first version. They discuss why taste, discernment and a genuine point of view matter more as content becomes cheaper to make; why polished execution is not the same as a good idea; and why small businesses should resist the temptation to publish the first thing an AI tool gives them. How to find Tom & BigSmall: https://www.bigsmall.works/https://www.linkedin.com/in/tomevansbigsmall/ What You'll Learn: How generative AI is changing advertising, design, brand strategy and marketingHow to use AI for creative ideation without producing generic content or AI slopWhy AI-generated ads, images and social posts need stronger creative directionHow small businesses can use AI to develop campaign ideas and marketing conceptsWhat generative AI could mean for creative teams, agencies and junior creative rolesHow AI prototyping tools help non-technical people turn ideas into tangible projects Get in Touch: hello@earlyadoptr.ai TikTok: @early_adoptr Instagram: @early_adoptr YouTube: @early_adoptr LinkedIn: https://www.linkedin.com/company/early-adoptr/ www.earlyadoptr.ai Get in touch with Early Adoptr: hello@earlyadoptr.ai Follow Us on Socials & Resources: IG: https://instagram.com/early_adoptr TikTok: https://tiktok.com/@early_adoptr YouTube: https://www.youtube.com/@early_adoptr Substack: https://substack.com/@earlyadoptrpod Hosted on Acast. See acast.com/privacy for more information.

  8. Sep 9

    How AI Agents Can Model Your Business Before It Breaks (w/ Rich Welsh)

    What if a digital twin could let you test a business decision before it disrupted your business? Once the preserve of robotics, manufacturing and supply chains, AI is helping digital twins become a practical way to model everyday business decisions, from whether your team can take on another client, what happens if a supplier fails, how a staff shortage affects a schedule, or where a production workflow is likely to bottleneck. In this week's episode, Kyle is away so Jess is joined by Rich Welsh, President of SMPTE (the Society of Motion Picture and Television Engineers) and Chairman of Volustor, to unpack what digital twins actually are and why AI is making them more accessible to smaller businesses. AI can pull together information from the systems you already use, help turn your knowledge of a process into a working model, and spot patterns across schedules, customer behaviour, supplier data and workloads that a human team is unlikely to see in time. They cover how to start with one process rather than trying to model the entire business, how AI agents can monitor what "normal" looks like and flag early warning signs, and how a digital twin can help you test a change before it costs you time, money, or customer trust. Find Rich: https://www.linkedin.com/in/richwelsh-technologist/ Join SMPTE: https://www.smpte.org/ Support the Pod: Wispr Flow - AI-powered voice dictation that works across every app on your desktop - https://ref.wisprflow.ai/early-adoptr Granola - The best AI meeting notes! New users get 100% off for their first month - https://www.granola.ai?via=early-adoptr Timestamps: 00:56 What Is an AI Digital Twin? 02:44 Welcome Rich Welsh 05:33 Defining an AI Digital Twin: From 3D Scans to Industrial Process Models 08:32 How AI Digital Twins Apply to Small Businesses, Not Just Supply Chains 11:26 Why Small Businesses Need an AI Digital Twin 13:46 Building an MVP with an AI Digital Twin: Lessons From Robotics and Space 15:04 The Flip Side: Building an AI Digital Twin of Your Ideal Customer 17:11 Using an AI Digital Twin to Predict How Your Team and Customers Will React 22:08 Walmart's AI Digital Twin and Why External Factors Need Real AI to Track 24:37 The AI Digital Twin That Predicted a Formula One Car Failure Before It Happened 31:46 Why a Hybrid Local and Cloud AI Model Wins on Cost 37:34 Digital Twins Everywhere by 2030 Resources: https://www.ciodive.com/news/Walmart-supply-chain-ai-digital-twin/825119/ https://www.ceepla.com/en/insights/digital-twins-for-sme linkedin.com/pulse/digital-twins-budget-how-smes-can-compete-enterprise-varenas-mba-dtyvc https://iotdigitaltwinplm.com/agentic-digital-twins-ai-driven-industrial-analysis-2026/ https://www.celonis.com/blog/revolutionizing-workflows-with-process-digital-twins google.com/url?q=https://www.aidoos.com/blog/Digital-Twins-for-Small-and-Medium-Businesses-A-Practical-Guide-for-CIOs-and-Business-Owners/&sa=D&source=docs&ust=1788814501342313&usg=AOvVaw08EY_URPU8n3OqSGWsk1KT Get in Touch hello@earlyadoptr.ai TikTok: @early_adoptr Instagram: @early_adoptr YouTube: @early_adoptr LinkedIn: https://www.linkedin.com/company/early-adoptr/ www.earlyadoptr.ai Get in touch with Early Adoptr: hello@earlyadoptr.ai Follow Us on Socials & Resources: IG: https://instagram.com/early_adoptr TikTok: https://tiktok.com/@early_adoptr YouTube: https://www.youtube.com/@early_adoptr Substack: https://substack.com/@earlyadoptrpod Hosted on Acast. See acast.com/privacy for more information.

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Early Adoptr is the weekly AI podcast for founders and small-business owners who are curious about the technology and want to put it to work, without needing a technical background. Hosted by Jess and Kyle, the show gets into the questions behind the headlines: What can you trust AI to handle? Could you build something yourself? Is that new tool worth paying for? And what on earth is an agent harness? From explaining technical ideas to trying tools and exploring business applications, Jess and Kyle help you make sense of AI and what you could do with it. Understand the AI. See the possibilities. Decide what’s useful. New episodes every week on Apple Podcasts, Spotify, YouTube and wherever you listen. Hosted on Acast. See acast.com/privacy for more information.

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