『AI-Ready Or Not?』のカバーアート

AI-Ready Or Not?

AI-Ready Or Not?

著者： Travis Scott
無料で聴く

【Amazonプライム会員限定】今ならプレミアムプランが4か月 月額99円。

10月19日まで。※適用条件あり
Most companies are buying AI tools. Almost none of them have the data, processes, or systems in place for those tools to deliver. The CRM is a mess. The processes aren't written down. The tribal knowledge is locked in three people's heads. Then the AI gets layered on top, and nobody understands why it doesn't work. AI-Ready or Not is the show about fixing the foundation first. Host Travis Scott talks with founders, operators, authors, and practitioners about how they're actually using AI. What's working. What's not. What they had to do to make it work. New episodes every two weeks.©️RainierDigital LLC 2026 経済学
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  • The Retention Leak: How AI Can Catch Churn Before It Happens

    The Retention Leak: How AI Can Catch Churn Before It Happens
    2026/09/22
    Most founders would notice a kitchen fire. A slow leak in the basement is different. Everything looks fine for months, and by the time the water shows up the damage is already done. That is how Alisha Esmail describes client retention, and it is the reason she went from running a coffee company to building Latch AI, a tool that flags which clients are slipping before they leave."It's like the leak in your basement. It's not a kitchen fire, it's not a dumpster fire, but your basement is filling with water."About This EpisodeAlisha's path into AI did not start with software. It started with a coffee company that worked directly with farmers around the world, building supply chains for female farmers and a microloan program to help them out of poverty. Running a physical product business across continents taught her where the manual work piles up, and that is where she started adding software, then agents, then AI, to buy her team's time back.The turning point was an email. At the dinner table with her family, she learned that her biggest client, half of her monthly recurring revenue, had decided to go in a different direction. She had to excuse herself from the table. That moment pushed her to become, in her words, a retention expert if she was going to build a successful company. She won that client back, and they are still a client today, but the lesson stuck: keeping a client is far cheaper and far easier than reselling them after they leave.Latch AI is the system that grew out of that lesson. It connects to the tools a business already uses, its CRM, calendar, payment system, and support tickets, and sorts every client into one of four categories: at risk, slipping, ready, or stable. Two of those are time-sensitive windows. The point is to catch someone while they are slipping, before they hit red, and to ask for the renewal or the referral at the moment the client is actually ready rather than when the business happens to need cash. Alisha also explains why she did not start with AI at all. The retention engine ran as a manual process first, then her team ran it, then automation, and only then AI. Throwing the kitchen sink at a model without a real problem and a real process is, in her view, the most common mistake people are making right now.Travis brings the revenue operations side of the same problem. Most CRMs are a mess: duplicate contacts, pipeline stages nobody defined the same way, stale deals, and historical data dragged over from two previous systems. Layer AI on top of that and it amplifies the mess. Alisha agrees without hesitation: the cleanup comes first. The conversation closes on a counterintuitive point from Travis. Companies often document why they lost a deal, but almost nobody documents why they won one, and the expectations set at the moment a client says yes are where a lot of churn is born.About Alisha EsmailAlisha Esmail is the founder of Latch AI. Her background is in international development, which led her to start a coffee company that worked directly with farmers, created streamlined supply chains for female farmers, and ran a microloan program. She went through a tech incubator and won funding to build a platform around those microloans before the pandemic put it on pause. Inside the coffee business she built an AI brain and agents to streamline the workflow, and a manual retention and client-intelligence system that eventually became Latch. Today she helps business owners keep their clients longer and grow through expansion revenue, working with an invite-only early adopter program of agencies, coaches, clinics, and other repeat-relationship businesses.Key TakeawaysRetention is a leak, not a fire - Nobody ignores a fire. Slow client loss feels like nothing is wrong, which is exactly why founders notice it too late. Treat it as urgent before it is visible.Build the manual system before the AI - Alisha ran her retention process by hand, then handed it to her team, then automated it, and only then added AI. The model speeds up a process that already works; it does not invent one.Ask at the right time - Renewals, upsells, and referrals fail when they are asked for at the wrong moment, usually when the business needs revenue. Latch's "ready" category exists to find the moment the client is actually a cheerleader.A few points of retention move profit, not just revenue - Once hard costs are covered, retained revenue can have an outsized effect on profit. In one example Alisha shares, a company that believed it retained about 80 percent of its clients discovered the real number was closer to 60 percent.Clean the CRM first - Duplicate contacts, undefined pipeline stages, and stale deals are exactly the variables AI has to grab onto. Feeding it a mess only makes the mess faster.Document why you won - Closed-lost reasons are common. Closed-won reasons almost never are, and the gap between what a client expected at yes and what got delivered is where churn starts.Chapter Markers00...
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    34 分
  • Her Business Was Going Under, Then She Saved It With AI

    Her Business Was Going Under, Then She Saved It With AI
    2026/07/06
    She Almost Lost the Business. Then She Rebuilt It With AI. Andrea Palacio and her husband bought a "boring" landscaping company expecting an easy win — and nearly lost everything within a month. This is the story of how she clawed it back with AI and automated it into a business that runs without her. "Those companies are losing between 30 and 40% of their revenue just because they're not answering the phone on time." — Andrea Palacio About This Episode After a decade as an entrepreneur — including seven years running an e-commerce business from a sailboat in the Caribbean — Andrea Palacio and her husband decided to buy a "boring business" and put an operator in place. The reality hit fast: within a month of acquiring a landscaping company, the manager quit and told the crew to find other jobs, staff dropped from 12 to 2, and revenue was cut nearly in half. With their home attached as SBA-loan collateral and a second baby on the way, they were working 80-hour weeks and ready to sell. Instead, Andrea went down the "YouTube University" rabbit hole and started solving her own problems with AI. In this conversation you'll hear how she put AI on every inbound phone call (answering and booking every lead automatically), how that stopped a 30–40% revenue leak, and how AI-optimized Google Ads increased their leads 20% while cutting ad spend. You'll also hear exactly how she runs ads with AI today — connecting Claude Code directly to Google Ads with an AI agent, while her non-technical husband uses Claude's Chrome extension to audit the account, catch broken links, and find ads running without landing pages. The business became automated enough that a buyer offered full asking price — so they kept it, hired an operations manager, and stepped away. That turnaround became RunCrewless.com, where Andrea now helps service-business owners build self-operating companies. A note on this episode: Andrea and I ran into internet connection problems during recording, and much of the second half of our conversation couldn't be saved. The good news: the best moments from that half were captured — find them as Shorts on the Rainier RevOps YouTube channel, including her take on the founder "productivity trap," using AI to clean up messy CRMs, and why she tells business owners to go all-in on one AI tool. About Andrea Palacio Andrea spent 10 years building and exiting businesses — an e-commerce company she ran while living on a sailboat, then a landscaping company (Mokai) she and her husband acquired and nearly lost before automating it with AI. That turnaround led her to found RunCrewless.com, where she now helps service business owners run self-operating companies using Claude Code and automation. She's also a business coach in Dan Martell's Elite program. Key Takeaways Not answering the phone quietly kills revenue — Andrea estimates service businesses lose 30–40% of revenue by missing calls. AI that answers every call and books every lead removes the leak.AI turned their Google Ads around — leads up 20%, ad spend down significantly, and the account gets audited automatically for broken links and ads with no landing page.You don't have to be technical — Andrea connects Claude Code straight to Google Ads; her husband gets the same results with Claude's Chrome extension in the browser.Automation raised the value of the business — the company became self-operating enough that a buyer offered full asking price; they kept it and stepped away instead.Solve your own problem first — Andrea started with zero AI experience; she just aimed it at the thing burning her day (the phone) and built from there. Chapter Markers (00:00) Cold Open(00:26) Meet Andrea: 10 Years From a Sailboat(01:31) Buying the "Boring Business"(03:20) The Crash: 12 Employees Down to 2(04:53) Discovering AI With Zero Experience(09:33) AI on the Phones + Google Ads(11:51) Claude Code vs. the Chrome Extension(13:52) Technical Difficulties + More From Andrea on YouTube Resources & Links Mentioned RunCrewless — Andrea's company, helping service businesses run self-operating: https://runcrewless.comDan Martell — Elite coaching program: https://www.danmartell.comClaude / Claude Code — https://claude.aiClaude in Chrome (extension) — https://claude.ai/chromeChatGPT / OpenAI — https://chatgpt.comMake.com (automation platform) — https://www.make.comUpwork — https://www.upwork.comGoogle Ads — https://ads.google.comMore from this conversation — Shorts on the Rainier RevOps YouTube channel: https://www.youtube.com/@RainierRevOps Connect with Andrea Palacio Website: https://runcrewless.comLinkedIn: https://www.linkedin.com/in/andreapalacioInstagram: @andreapalacio Connect with Travis Rainier RevOps: https://rainierdigital.comLinkedIn: https://www.linkedin.com/in/travisscott24Instagram: https://www.instagram.com/travis.revopsYouTube: https://www.youtube.com/@RainierRevOps If This Episode Resonated If your company is buying AI tools ...
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    15 分
  • Divine Intervention: How One Founder Cracked a Two-Company Monopoly with AI

    Divine Intervention: How One Founder Cracked a Two-Company Monopoly with AI
    2026/06/18
    Divine Intervention: How One Founder Cracked a Two-Company Monopoly with AIFor as long as anyone can remember, an online pharmacy could only get accredited by one of two companies — and the backlog showed it. Aaron VanStone is building the third, ScriptSafe, and he coded the entire platform himself, with no software background, using Claude Code."The classic thing they teach you in every coding class is that the more preparation you do beforehand, the better the end output's gonna be. It's no different with these models."About This EpisodeAaron VanStone has spent more than 20 years in payments. In 2008 he founded Processing Brokerage, a pay-for-performance firm that audits merchants' credit-card processing fees across the U.S., Canada, and the U.K. A project with a compounding-pharmacy trade group pulled him into the pharmacy world — where he ran headfirst into a bottleneck: to accept online payments or run Google ads, a pharmacy needs third-party accreditation, and "since the beginning of time" there have been only two accreditors. The backlog was enormous.His answer is ScriptSafe, an AI-powered accreditation platform that reviews a pharmacy's licenses and then monitors its website every night to confirm it isn't selling anything illegal. What makes the story remarkable is that Aaron built the technology himself — starting at the end of January with zero coding experience, using Claude Code (with Codex as a second set of eyes). As he puts it, the timing felt like "divine intervention": the tools arrived exactly when he needed them, and what he built "wasn't possible a year ago."This is a tactical conversation. Aaron and Travis get into the workflow that actually works: writing a detailed planning document before building, running two models against each other so they have to agree, building a brand system for consistent design, and the cheap starter stack — Vercel, GitHub, and Supabase — that lets anyone ship. They also dig into the lesson that cost Aaron a month: there was no observability layer, so the AI was guessing at bugs. Once he added one, nightly pharmacy scans dropped from four hours to under 90 seconds.It's also a candid take on the risks — vendor lock-in, the coming wave of "AI-slop software," and why vibe-coding your own CRM might be shortsighted if you ever need to hire or train for it. And underneath it all runs an encouraging message: there has never been a better moment to learn this, especially if you've just been laid off and finally have the runway to dig in.About Aaron VanStoneAaron VanStone leads three companies at the intersection of payments, fintech, and healthcare compliance, drawing on more than 20 years in the payments ecosystem. He founded Processing Brokerage in 2008, a pay-for-performance consulting firm that audits credit card processing fees for merchants across the U.S., Canada, and the U.K. Most recently, he launched ScriptSafe, an AI-powered pharmacy accreditation platform designed to eliminate regulatory bottlenecks for online pharmacies. He's built ScriptSafe's technology stack using AI coding tools, a workflow he discusses in depth on topics ranging from Claude Code to brand systems in web development.Key TakeawaysPrep beats prompts — Aaron spends 90 minutes to two hours building a working planning document (with the model interviewing him) before writing any code. The richer the plan, the better the build.Run a second model as a reviewer — He has Codex continuously review Claude/Fable's output; when the two models agree, the code is far more trustworthy.Build a brand system first — Define your colors, logo, fonts, and overall look up front, then tell the builder to follow those rules so everything stays consistent.You can't fix what you can't see — Adding an observability layer turned guess-and-check debugging into real analysis and took nightly pharmacy scans from 4 hours to under 90 seconds.The starter stack is cheap and learnable — Vercel (hosting) + GitHub (code) + Supabase (database), roughly under $30/month, is enough to "do anything."Chapter Markers0:00 — Cold open0:29 — Meet Aaron & ScriptSafe1:56 — From payments consulting to a new problem3:42 — Divine intervention: finding AI at the right moment6:07 — Fable 5 vs. Opus — you feel the upgrade11:29 — The "building a house" analogy for model progress12:59 — Prep beats prompts: plan before you build15:18 — Running Claude and Codex against each other18:35 — Vendor lock-in and the coming software shakeout20:56 — The "vibe-code your CRM" debate26:47 — The observability fix: 4 hours to 90 seconds29:23 — Starting from zero coding experience31:23 — "If you don't know where to start, ask it" + the hotel scanner34:03 — Why now is the time to learn — even if you've been laid off39:16 — The starter stack: Vercel, GitHub, Supabase40:52 — Design: Manus, Claude Design & brand systems42:04 — Two big tips to finishResources & Links MentionedTools & platforms:...
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    46 分
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