AI at Work

Are You Ready to Let the Agent Make the Call?

How much should you trust AI agents to make decisions? Kevin Williams explains why human-in-the-loop reviewers make bad bot sitters, and Matt runs Codex with full autonomy. Kevin Williams and Matt talk through the agentic tools they use every day, from Dot in Slack to a dial-in number Kevin uses to talk through his workday. They argue about guardrails, YOLO mode, and when it makes sense for a team. In this episode: - Why a human reviewing fragments of an automation can't give a meaningful thumbs-up - Matt's setup that tunnels Dot directly to Codex, credit cards included - Kevin's advice on virtual credit cards for agents - Running an hour a day by voice, including sending NDAs - A solo Harvard MBA who coordinated 11 external labs with Claude, and why Anthropic bought him - The risk of restructuring around a small AI-built SaaS vendor Thanks to our Sponsors! AscendAI: https://ascendlabs.ai RapidDev: https://rapidevelopers.com/ LiberNovo: https://libernovo.com/ Try Muse, get a billion tokens! https://muse.ai/join (use code RHYQ60 in settings) CHECK OUT KEVIN’S STUFF: Website: https://ascendlabs.ai/ LinkedIn: https://www.linkedin.com/in/kevinguywilliams/ Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the https://resources.ascendlabs.ai/openai-vs-anthropic-for-teams... Book a Call: Book a call... CHECK OUT MATT’S STUFF: LinkedIn: https://www.linkedin.com/in/matt-graham-nocode/ Company: https://www.linkedin.com/company/rapid-dev/ Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

• Transcript

When Your AI Workflow Is Just Automating the Mess

How to fix your business before you automate it with AI. Sabir Semerkant exited three brands from his program for skipping that step. Kevin Williams sits down with Sabir Semerkant, founder and CEO of Growth by Sabir, who has worked in direct-to-consumer ecommerce since the field was new. They get into why AI scales bad processes and bad data, the multi-model audit workflow Sabir runs in Claude Code, and how to test new models without breaking production. In this episode: - Why Sabir exited about three brands from his Rapid2X program - Garbage in, garbage out, and why wrong attribution data gets dangerous - An orchestrator, Haiku workers, and two read-only auditors scoring work over three rounds - Why Sabir pays monthly for his $100 plans and skips the annual discount - The Meta and Gemini tests that failed in his dev environment - Kevin's 600 hard-coded references to Sonnet 4.6 and the config file fix Thanks to our Sponsors! AscendAI: https://ascendlabs.ai RapidDev: https://rapidevelopers.com/ LiberNovo: https://libernovo.com/ Try Muse, get a billion tokens! https://muse.ai/join (use code RHYQ60 in settings) CHECK OUT KEVIN’S STUFF: Website: https://ascendlabs.ai/ LinkedIn: LinkedIn... – Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the https://resources.ascendlabs.ai/openai-vs-anthropic-for-teams... Book a Call: Book a call... CHECK OUT SABIR’S STUFF: Website: https://growthbysabir.com/

• Transcript

The CEOs Who Said AI Wasn't Their Problem Just Changed Their Minds

How to start using AI agents in your business, and why taste matters more than tools. Plus the Charleston room where all 17 CEOs leaned in. Kevin Williams and Matt compare notes on agent setups, why two people automating the same job get wildly different results, and what business owners in paving and HVAC are finally doing about AI. Kevin also shares where he tells every company to start. In this episode: - Why an agent built by someone with taste beats one built by a beginner - Who to pair with your taste people, and why they rarely have the technical skills too - Why large organizations shouldn't let everyone build their own AI solutions - 17 CEOs in Charleston, all engaged with AI for the first time - Kevin's two starting points: expensive human mistakes and misused talent - Living with ChatGPT's Dots, long-tail tasks, and 2FA headaches Thanks to our Sponsors! AscendAI: https://ascendlabs.ai RapidDev: https://rapidevelopers.com/ LiberNovo: https://libernovo.com/ Try Muse, get a billion tokens! https://muse.ai/join (use code RHYQ60 in settings) CHECK OUT KEVIN’S STUFF: Website: https://ascendlabs.ai/ LinkedIn: LinkedIn... – Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the https://resources.ascendlabs.ai/openai-vs-anthropic-for-teams... Book a Call: Book a call... CHECK OUT MATT’S STUFF: LinkedIn: https://www.linkedin.com/in/matt-graham-nocode/ Company: https://www.linkedin.com/company/rapid-dev/ Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

• Transcript

How a Dev Devs with Dots (ft. Vlad Larin)

How to build with AI when you're not a full-time developer, plus OpenAI's Dot agent doing a month of work in a day. Kevin Williams and AI developer Vlad Larin. Vlad Larin went from managing a 250-person delivery team to building with AI himself, and he argues the skill that separates good AI builders from bad vibe coders is the same one that separated good developers from bad ones: vision, architecture, and knowing what the product is supposed to do. Kevin Williams and Vlad compare build setups, test OpenAI's Dot, and talk about what AI subscriptions are likely to cost. In this episode: - Why a decade of untangling client requirements translates to building with AI - Vlad's setup: Codex plan mode, GitHub, Supabase, and Vercel - Gaslighting Codex as an "unofficial turbo mode" (and when it backfires) - Dot catching a missing meeting invite and bills due, unprompted - Kevin's 100-ad Meta campaign run hands-off with computer use - Why $500 a month is justifiable and $5,000 would stunt the market Thanks to our new Sponsor LiberNovo and their insanely supportive Omni Chair: https://libernovo.com/ To try out Muse and get a BILLION tokens use code: RHYQ60 https://muse.ai/join (full disclosure, we will get a billion tokens too… but aren’t sure how we will use them) Ready to find out where your organization actually stands on AI readiness? https://assessment.ascendlabs.ai/ Want to talk through your AI tool decisions before you commit? tidycal.com/kevinwilliams CHECK OUT KEVIN’S STUFF: Website: https://ascendlabs.ai/ LinkedIn: LinkedIn... – Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the https://resources.ascendlabs.ai/openai-vs-anthropic-for-teams... Book a Call: Book a call... VLAD LARIN: LinkedIn: https://www.linkedin.com/in/vlad-larin/

• Transcript

Is the Cost Apocalypse Already Over?

AI token costs in 2026: why Luna 6 at 40x cheaper than Fable may end the cost panic, and what Codex computer use actually did in four hours. Kevin Williams and Matt talk through the state of agentic AI right now: the jump from OpenClaw and Hermes to Grokbot and computer-use models, what Meta's Muse is actually for, and why Google paid $10 million for a dead airline's Slack messages. In this episode: - Kevin runs out of Codex tokens for three days and explains the $100 vs $200 plan trap - Luna 6 ships with computer controls at 40x less per token than Anthropic's Fable - Codex logs into Tag Manager, Analytics, Search Console, AdWords, Slack and HubSpot and finishes a week of campaign setup in four hours - Why Kevin refused to give Muse his Amex login, and what it did to his kids' Canvas account - Google buying Spirit Airlines' operating data to build a sandbox digital airline - Whether Anthropic's inference demand in early 2026 cost it the training race Thanks to our new Sponsor LiberNovo and their insanely supportive Omni Chair: https://libernovo.com/ To try out Muse and get a BILLION tokens use code: RHYQ60 https://muse.ai/join (full disclosure, we will get a billion tokens too… but aren’t sure how we will use them) Ready to find out where your organization actually stands on AI readiness? https://assessment.ascendlabs.ai/ Want to talk through your AI tool decisions before you commit? tidycal.com/kevinwilliams CHECK OUT KEVIN’S STUFF: Website: https://ascendlabs.ai/ LinkedIn: LinkedIn... – Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the https://resources.ascendlabs.ai/openai-vs-anthropic-for-teams... Book a Call: Book a call... CHECK OUT MATT’S STUFF: LinkedIn: https://www.linkedin.com/in/matt-graham-nocode/ Company: https://www.linkedin.com/company/rapid-dev/ Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

• Transcript

Recursive Self-Improvement? End of the World? Or an Opportunity...

An Anthropic researcher went public with a 10% chance that AI does away with humanity, implied it's a common feeling inside the company, and other researchers backed him up. Dario Amodei followed with an essay saying it's time to talk seriously about slowing down. Sam Altman chimed in, Bernie Sanders wants it banned outright, the administration is calling it a hoax, and there's an election in a few weeks. Kevin Williams and Matt skip the politics and go after the technology behind the panic: recursive self-improvement. The slope is the part nobody is planning around. Once a model can pull its own levers, improvement stops being a steady climb and becomes a rock tipping from potential energy to kinetic. Astra 6 to Astra 20 to Astra 2000 in hours, days, minutes. The 2015 prisoner's dilemma argument holds that the first lab there wins the whole game. Then they get practical. What an RSI-style loop looks like inside a business today, why constantly shifting models make solutions hard to build against, treating context as code, sharing reusable skills, and Kevin's cost work: a resources tool that ran $40 per update until he rebuilt it around an MCP, and thumbnail images at seven and a half cents each. Full episode: https://ascendlabs.ai/podcast/ep-42-recursive-self-improvement-end-of-the-world-or-an-opportunity/ In this episode: - The 10% claim, who made it, and why the regulatory capture read is tempting - Why RSI improvement is exponential and what tipping over looks like - The national security version: what if China's model goes to Astra 2000 overnight - Building solutions on a model that quietly becomes Opus 17 - Self-improvement loops applied to your own processes, not just the model - Why Kevin downgraded Claude Max from $200 to $100 Ready to find out where your organization actually stands on AI readiness? https://assessment.ascendlabs.ai/ Want to talk through your AI tool decisions before you commit? tidycal.com/kevinwilliams CHECK OUT KEVIN’S STUFF: Website: https://ascendlabs.ai/ LinkedIn: LinkedIn... – Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the OpenAI vs. Anthropic comparison... Book a Call: Book a call... CHECK OUT MATT’S STUFF: LinkedIn: https://www.linkedin.com/in/matt-graham-nocode/ Company: https://www.linkedin.com/company/rapid-dev/ Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

• Transcript

Is Your Company AI-Assisted or Actually AI-Native?

Kevin Williams and Matt open Alex Lieberman's 30 Features of an AI Native Company and get through the first handful of items, starting with the one most organizations get wrong. Blueprinting your processes is the right first move. Replicating every existing step inside an AI system is not, because a model like Astra will happily reproduce a five-step handoff that was designed around people and tools that predate it. Before that, Kevin walks through what he actually built with Astra last week: a 45-page presentation deck assembled from client research, downloaded imagery and past decks; a technical SEO project that produced a new page, four updates and seven draft articles in about 45 minutes; and a part-based 3D printable model of a cabin he used to own in West Virginia, generated from two photos and optimized for multi-color printing. They also get into why the intelligence layer has no good off-the-shelf answer, why AI-first organizations that are smaller and founder-led can move when ISO-certified companies can't, and whether the sunk cost fallacy still applies to systems you built nine months ago. Topics covered: - The caveat on blueprinting processes: input and output, not five steps - Why every person in the organization needs a daily driver, plus a literacy layer - Building an intelligence layer across email, Slack, transcripts and documents - What Astra did with a deck, an SEO campaign and a 3D print - Why security-mature organizations struggle to move at all here - When to rebuild a working system and when to leave it alone Ready to find out where your organization actually stands on AI readiness? https://assessment.ascendlabs.ai/ Want to talk through your AI tool decisions before you commit? tidycal.com/kevinwilliams CHECK OUT KEVIN’S STUFF: Website: https://ascendlabs.ai/ LinkedIn: LinkedIn... – Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the https://resources.ascendlabs.ai/openai-vs-anthropic-for-teams... Book a Call: Book a call... CHECK OUT MATT’S STUFF: LinkedIn: https://www.linkedin.com/in/matt-graham-nocode/ Company: https://www.linkedin.com/company/rapid-dev/ Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

• Transcript

The Two-Billion-Token Weekend That Cost $125 (For Now)

Kevin spent a rainy weekend running up to 10 simultaneous Codex agents across three internal builds and burned two billion tokens. On a consumer plan, propped up by repeated usage resets, that cost him about $125. At retail API rates on GPT 5.6 high, the same weekend runs north of $8,000 to $10,000 and enterprise teams building in Codex fall outside the consumer plan entirely. Matt and Kevin dig into what that gap means for anyone standing up internal AI infrastructure today. Matt's team built an internal system that captures every call, Slack message, and email on a client project and flags when something drifts. It runs affordably now. His concern isn't the build cost it's what happens if the run cost triples. They also cover why switching between Claude Code and Codex costs you almost nothing if your code lives in GitHub, why that undercuts the case for price increases, and what happened when Kevin turned a swarm loose on 45 repositories to fix a favicon. Topics: - Why AI avatars still fail for self-cloning after three years of trying - The 82/18 split between deterministic and agentic workflow steps - LinkedIn bans, bot-detectable IPs, and 200 profile lookups in five minutes - Codex sidebar chats, work trees, and browser control versus Claude Code - Two billion tokens, $125, and the $8,000 enterprise equivalent - The runaway agent that logged into an abandoned Lovable account Ready to find out where your organization actually stands on AI readiness? https://assessment.ascendlabs.ai/ Want to talk through your AI tool decisions before you commit? tidycal.com/kevinwilliams CHECK OUT KEVIN’S STUFF: Website: https://ascendlabs.ai/ LinkedIn: LinkedIn... – Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the https://resources.ascendlabs.ai/openai-vs-anthropic-for-teams... Book a Call: Book a call... CHECK OUT MATT’S STUFF: LinkedIn: https://www.linkedin.com/in/matt-graham-nocode/ Company: https://www.linkedin.com/company/rapid-dev/ Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

• Transcript

How to Stay Visible When Everyone's Filtering You Out

LinkedIn is losing patience with AI slop and it's not subtle about it anymore. There's 20-25% more AI-generated content on the platform right now, engagement is down 17%, and LinkedIn just added a complaint button that sends a negative signal straight to the algorithm when users flag a post. If your team has an automated content flow, this episode is for you. Kevin Williams and Matt Graham dig into what the AI content arms race actually looks like from the inside: the outbound personalization that stopped working, the media briefs that CMOs clearly never read before sending, the watermarking technology Anthropic just deployed to comply with the EU AI Act, and why the hyper-personalized cold email had a window that is now closed. The conversation also covers what's still working targeting the right person at the right moment, keeping a human in the review loop, and building the kind of differentiated content that doesn't get mistaken for something an agent generated in 30 seconds. Key topics covered: ✅ LinkedIn's new AI complaint functionality and what it means for automated content ✅ The 20-25% content increase and 17% engagement drop — and why it's getting worse ✅ Anthropic's watermarking rollout and the cat-and-mouse arms race with humanizer tools ✅ Why hyper-personalized outbound backfired and what actually converts now ✅ The CMO problem: AI-generated briefs that no human reviewed before going out ✅ How to stay visible when every channel is filling up with noise Ready to find out where your organization actually stands on AI readiness? https://assessment.ascendlabs.ai/ Want to talk through your AI tool decisions before you commit? tidycal.com/kevinwilliams CHECK OUT KEVIN’S STUFF: Website: https://ascendlabs.ai/ LinkedIn: LinkedIn... – Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the https://resources.ascendlabs.ai/openai-vs-anthropic-for-teams... Book a Call: Book a call... CHECK OUT MATT’S STUFF: LinkedIn: https://www.linkedin.com/in/matt-graham-nocode/ Company: https://www.linkedin.com/company/rapid-dev/ Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

• Transcript

To Lovable or not To Lovable

Most organizations pick AI tools by asking the wrong question. They benchmark capability, compare feature lists, and choose the most powerful option then wonder why adoption stalls at 10-15% six months later. Kevin and Matt Graham dig into the real selection criteria leaders should be using, and why usability almost always beats raw capability when it comes to organizational ROI. This episode started as a debate about Lovable the vibe coding platform that just raised $400M at a $13B valuation and turned into a broader conversation about what it actually takes to get AI working across an entire organization, not just in the hands of your most technical people. Kevin and Matt cover the Lovable debate from both sides (Kevin's been burned, Matt's a believer), the emerging governance risks of agentic AI tools like Grokbot, why vendor lock-in is a real concern that organizations need to plan for, and where Google, XAI, and the competitive model landscape are actually headed. Key topics covered: ✅ Why usability beats capability as an AI tool selection criterion ✅ Lovable's enterprise evolution what's changed and what hasn't ✅ Vendor lock-in: how to preserve optionality without abandoning a useful tool ✅ Grokbot and agentic AI the governance risks organizations aren't ready for ✅ The competitive model landscape: XAI's rise, Google's pivot, and what it means for token costs ✅ Why spreading AI licenses without organizational context produces nothing Ready to find out where your organization actually stands on AI readiness? https://assessment.ascendlabs.ai/ Want to talk through your AI tool decisions before you commit? tidycal.com/kevinwilliams CHECK OUT KEVIN’S STUFF: Website: https://ascendlabs.ai/ LinkedIn: LinkedIn... – Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the https://resources.ascendlabs.ai/openai-vs-anthropic-for-teams... Book a Call: Book a call... CHECK OUT MATT’S STUFF: LinkedIn: https://www.linkedin.com/in/matt-graham-nocode/ Company: https://www.linkedin.com/company/rapid-dev/ Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

• Transcript

Why Your AI Pilot Is Just a New Steam Engine

Most companies are repeating a 100-year-old mistake with AI and the history of factory electrification explains exactly why. In this conversation, Kevin Williams and Matt Graham trace the parallel between the factories that plugged in electric motors without redesigning their floors and the organizations today that are adding AI tools without touching the structures underneath them. The gains didn't come from the new engine. They came from tearing the building down. Kevin and Matt cover what that actually means for leaders making AI decisions right now including when rebuilding makes sense, when it doesn't, and what the companies pulling ahead have in common that has nothing to do with their tech stack. They also get into the week's AI security news (sandbox escapes, autonomous agents creating their own email accounts and attempting to generate revenue to fund their tasks), the real switching costs between Claude and GPT Codex, what changed in Claude 5.0 that broke Kevin's custom build system, and why the "agent orchestrator" is a role your organization will need before it knows it needs one. What this conversation covers: ✅ Why plugging AI into existing processes produces higher costs and identical outputs and what the electrification era teaches us about the actual path to gains ✅ The three options every leader faces: do nothing, rebuild from scratch, or rip down what's working and the honest tradeoffs of each ✅ Sandbox escape incidents across multiple AI labs this week, what autonomous agents actually did when they hit a wall, and what it means for enterprise security ✅ What changed in Claude Opus 5.0 and GPT 5.6 that required Kevin to completely rebuild his custom development system and what that means for anyone using AI in production ✅ The "agent orchestrator" role, why it doesn't really exist yet, and why the companies who started experimenting three years ago are already ahead in ways that can't be quickly closed CHECK OUT KEVIN’S STUFF: Website: https://ascendlabs.ai/ LinkedIn: LinkedIn... – Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the https://resources.ascendlabs.ai/openai-vs-anthropic-for-teams... Book a Call: Book a call... CHECK OUT MATT’S STUFF: LinkedIn: https://www.linkedin.com/in/matt-graham-nocode/ Company: https://www.linkedin.com/company/rapid-dev/ Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

• Transcript

When Your Curiosity Becomes Your Biggest Business Risk

Everyone is using AI. Almost nobody is making more money from it. Kevin Williams and Matt Graham get into why that gap exists, and it has nothing to do with which tools you're using. This conversation starts with a simple observation: AI is going to business backlogs and wish lists instead of the two or three highest-leverage constraints that actually drive growth. The tools are working. The focus is off. Kevin and Matt explore why this pattern is so common among curious, tech-savvy leaders, what it costs organizations that can't create space for experimentation, and why the most dangerous AI risk right now might not be the one making headlines. Kevin also shares a real-world AI-enabled phishing attack that nearly caught him one that was so well-constructed it passed every visual check. The practical security guidance in this conversation is worth the listen on its own. Key topics covered in this episode: Why AI productivity gains aren't producing top-line growth and what to do about it Main quests vs. side quests: how to tell which AI work actually matters The flight risk hiding inside organizations that won't let curious talent experiment A detailed breakdown of an AI-powered phishing attack and how to protect yourself Practical AI model cost management across Claude, GPT Work, Codex, and Fable Work breakdown structures as a living log for vibe coders and citizen developers Resources mentioned: Workflow: https://podprocess.ascendlabs.ai/podcast/workflow Assess where AI should be pointed in your business: https://assessment.ascendlabs.ai/ Book a conversation with Kevin: https://tidycal.com/kevinwilliams CHECK OUT KEVIN’S STUFF: Website: https://ascendlabs.ai/ LinkedIn: LinkedIn... – Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the https://resources.ascendlabs.ai/openai-vs-anthropic-for-teams... Book a Call: Book a call... CHECK OUT MATT’S STUFF: LinkedIn: https://www.linkedin.com/in/matt-graham-nocode/ Company: https://www.linkedin.com/company/rapid-dev/ Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

• Transcript

Your AI Tools Are Leaking and Nobody Told You

Every organization with 50 or more people probably has someone quietly building AI tools right now. The question isn't whether it's happening it's whether there are any guardrails around it. Kevin Williams and Matt Graham get into the governance gap that almost nobody in the 'just start building' conversation is talking about honestly. Matt runs a security firm and watches the dark web. What he's seeing in terms of exposed API keys, hard-coded credentials, and applications built without basic security hygiene has reached a level he's never seen before. This episode is the conversation business owners and executives need to have before the next thing gets built. The conversation covers the full picture: why citizen development concentrates key-man risk instead of reducing it, how to think about deterministic versus probabilistic workflows, what the Anthropic copyright settlement means for companies plugging their data into frontier models, and the practical governance steps any organization can take right now. ✅ Why vibe coding without documentation creates key-man risk ✅ How API keys get exposed and why it doesn't require a hacker ✅ The five-minute cost cap task most organizations haven't done ✅ Deterministic vs. probabilistic workflows: why the distinction matters for accuracy, liability, and cost ✅ What the $1.5B Anthropic copyright settlement signals for SMBs ✅ The Basecamp framework for governing citizen developers before things get complex Resources & Links: https://isclaudedumb.today/ resources.ascendlabs.ai https://ascendlabs.ai/basecamp/ https://assessment.ascendlabs.ai/ Check out Kevin’s stuff: Website: AscendAI LinkedIn: LinkedIn Free Tool: Take the AI Readiness Assessment Deep Dive: Read the GPT Teams vs. Anthropic Teams comparison Book a Call: Book a call Check out Matt’s stuff: LinkedIn: Follow Matt on LinkedIn Company: Rapid Dev on LinkedIn Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

• Transcript

When Your Vibe Coder Doesn't Know What They Don't Know

Anthropic and OpenAI aren't embedding engineers at major firms because they want to do IT consulting they need to drive massive token consumption to pay for a trillion dollars in AI infrastructure. But while McKinsey guides the Fortune 500 through this shift, mid-market and SMB companies are being left completely behind. In this episode, Kevin Williams and Matt Graham break down the "forward-deployed engineer" land grab, what it means for mid-market businesses, and the hidden cost of letting internal teams build fast without governance. They also dive into the technical realities of building agentic systems with precision, shifting from probabilistic outputs to deterministic reliability, and the true switching costs between major AI platforms. Key Topics Covered: The Token Economics Play: Why tech giants are embedding engineers it's a race for volume, not a consulting play. The Mid-Market Gap: The structural divide leaving mid-sized companies without access to embedded AI expertise. Vibe Coding vs. Governance: What happens when internal teams build fast without rails, and the hidden costs of cleaning up undocumented pipelines. Deterministic AI: How to configure agentic systems to deliver reliable outputs for sensitive financial and operational workflows. Platform Switching Costs: The real impact of committing to team-level platforms (GPT Teams vs. Anthropic Teams). 2026 Strategy: Why this is the official year organizations must stop piloting and start activating. Resources & Links: https://www.linkedin.com/posts/pneppalli_agentic-ai-adoption-is-on-fire-at-uber-and-share-7480367288781746176-Ji7t/ https://resources.ascendlabs.ai/openai-vs-anthropic-for-teams Check out Kevin’s stuff: Website: AscendAI LinkedIn: Follow Kevin on LinkedIn – Free Tool: Take the AI Readiness Assessment Deep Dive: Read the GPT Teams vs. Anthropic Teams comparison Book a Call: Talk to Kevin on TidyCal Check out Matt’s stuff: LinkedIn: Follow Matt on LinkedIn Company: Rapid Dev on LinkedIn – Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

• Transcript

The Head of AI Role Everyone Wants Doesn't Report to IT

Most leaders assume they need to hire technical talent before their organization can move seriously on AI. Wyatt Barnett runs AI at an 80-person trade association with no engineering staff and no CTO and he's built more working AI capacity than most companies twice his size. The model is simpler and more replicable than you'd expect. Wyatt Barnett is Head of AI (Technology Enablement) at the NCTA, the Internet and Television Association in Washington, D.C. In this conversation, Kevin and Wyatt get into the Tiger Team model Wyatt built from scratch ten cross-functional people embedded across departments, authorized to catch problems early, run experiments, and start solving things before they become formal requests. They also cover tool selection for mid-market orgs, token cost management, why the AI engineering community is shifting focus from frontier models to the surrounding tooling ecosystem, and what Wyatt would tell a CEO who wants to build this kind of capacity with a blank slate. Key topics covered: ✅ The Tiger Team model: how to build AI capacity without hiring engineers ✅ Why forward-deployed problem-catchers outperform centralized IT approaches ✅ Tool stack for mid-market orgs: Notion, Airtable, Claude, and what's actually working ✅ Token cost management and the real budgetary risks of AI at scale ✅ What Wyatt observed at the AI Engineer World's Fair and what it signals about where the industry is heading ✅ How to structure AI experimentation so you're watering the right flowers Check out Kevin’s stuff: → See where your organization stands on AI readiness: launchpad.ascendlabs.ai → Talk with Kevin about building this in your org: tidycal.com/kevinwilliams → AscendAI: https://ascendlabs.ai/ → Follow Kevin on LinkedIn: https://www.linkedin.com/in/kevinguywilliams/ Check out Wyatt’s Stuff: → Follow Wyatt on LinkedIn: https://www.linkedin.com/in/wyattbarnett/ → The Zeitgeist Distilled https://news.zeitgeistdistilled.com/

• Transcript

Why Claude Code Has Nothing to Do With Code

Most people heard "Claude Code" and assumed it was a developer tool. Kevin Williams and Matt Graham from Rapid Dev are here to correct that assumption and explain why the goal-oriented loop logic at the core of Claude Code might be the most underused productivity feature available to business leaders right now. This conversation started with a weekend of building and a realization: the same recursive, self-correcting loop that hardens software can harden a marketing plan, a strategic brief, or a financial analysis. The name was always the problem, not the tool. Kevin and Matt also get into the hacker house model how Rapid Dev gets more done in two focused weeks than two unfocused months and what happened when Kevin spent two days at a Los Angeles dining room table taking a high-end fashion brand from zero AI literacy to a functioning chief-of-staff agent. The episode covers the awkward middle most organizations are stuck in: past individual AI use, not yet at production-grade systems, and not quite sure how to close the gap. And with recent regulatory pressure on AI providers and real questions about vendor stability, they get practical about fallback architectures and what it actually means to build on a foundation that might shift. ✅ Why Claude Code is not a coding tool and what it actually does ✅ How /goal changes the quality and depth of any AI output ✅ The hacker house model: structure, composition, and expected outcomes ✅ The journey from individual AI use to organizational AI systems ✅ Vendor risk, provider instability, and the case for multi-model fallback ✅ Why organizational friction outlasts every technical solution Check out Kevin’s stuff: → AscendAI: https://ascendlabs.ai/ → Follow Kevin on LinkedIn: / kevinguywilliams → Get practical AI guidance: https://assessment.ascendlabs.ai/ → Book a consultation: http://tidycal.com/kevinwilliams Check out Matt’s stuff: → mailto:mgram@rapiddevelopers.com → / rapid-dev

• Transcript

Is Your Brain Worth Building or Should You Just Buy Glean?

The economics of building versus buying software just fundamentally changed. In this conversation with Matt Graham, CEO of Rapid Developers, we explore how the cost of custom development has dropped 90% and what that means for business strategy. Matt brings a unique perspective, having lived through the no-code revolution and now seeing the AI-native development wave. His company works with CEOs of $20-500M revenue businesses, and the patterns he's seeing are remarkable. From his 10-year-old son building a profitable e-commerce site over a weekend to enterprise clients rebuilding their ERPs from scratch, the landscape is shifting faster than most people realize. ✅ Key topics covered: • The evolution from no-code to AI-native development • Framework for build vs. buy decisions in the AI era • Why SaaS platforms walling off data changes the equation • Real cost breakdowns and ROI considerations • Job displacement concerns and the changing labor market • Personal tech stacks and tools that actually work Approximate timestamps: 00:00 — Intro and Matt's background 05:25 — No-code evolution and the AI transition 12:30 — Workflow problems vs. AI problems 18:45 — Build vs. buy framework 28:15 — SaaS disruption and data access issues 36:00 — Pricing model evolution and output-based work 45:30 — Job displacement and labor market impacts 50:45 — The 10-year-old entrepreneur story 53:20 — Personal tech stacks and tools Check out Kevin’s stuff: → AscendAI: https://ascendlabs.ai/ → Follow Kevin on LinkedIn: https://www.linkedin.com/in/kevinguywilliams/ → Get practical AI guidance: https://assessment.ascendlabs.ai/ → Book a consultation: tidycal.com/kevinwilliams Check out Matt’s stuff: → mgram@rapiddevelopers.com → https://www.linkedin.com/company/rapid-dev/

The One Percent Problem That Creates 68% Productivity Gains

95% of AI pilots fail to reach production, but it's not because of the technology. Brett Schklar, CEO of AI First Leadership and author of "AI Without the BS," has tracked AI adoption across 1,800 companies over two years and discovered the real bottleneck: the "frozen middle." In this conversation, Brett reveals why senior managers and directors represent both the highest resistance and highest potential impact for AI adoption. We explore his data showing marketing teams achieving 2.3x productivity gains while others fall behind, and his practical approach to building AI capacity through 1% weekly improvements that compound to 68% productivity gains. Key topics covered: ✅ Why the "frozen middle" blocks AI adoption ✅ How intelligence becomes a commodity but wisdom remains human ✅ The K-shaped productivity curve emerging in organizations ✅ Department-by-department ROI data from 1,800 companies ✅ Why focusing on 1% problems beats transformation strategies ✅ Building internal AI champions and centers of excellence ✅ The identity crisis driving AI resistance ✅ Practical tactics for mid-market AI implementation Timestamps: 00:00 — Intro and Brett's background 05:30 — From AI resistance to AI mandates: two-year evolution 12:00 — The model selection dilemma and governance concerns 18:45 — Scaling AI education beyond workshops 25:30 — The "frozen middle" problem explained 32:15 — ROI data across departments and functions 38:00 — Marketing productivity vs. content quality concerns 45:20 — Bringing marketing and sales together with AI 52:00 — Weekend project recommendations 57:00 — Brett's essential tools and where to connect Check out Kevin’s stuff: AscendAI: https://ascendlabs.ai/ Follow Kevin on LinkedIn: https://www.linkedin.com/in/kevinguywilliams/ Get practical AI guidance: launchpad.ascendlabs.ai Schedule a conversation with Kevin: tidycal.com/kevinwilliams Connect with Brett: AI First Leadership on LinkedIn: https://linkedin.com/in/bschklar Website: brettschklar.com Book: https://bit.ly/AIWithoutBS

When Models Lie and You're Still Paying for the Tokens

When AI models hallucinate confidently while burning through your token budget, you need more than better prompts you need better processes. In this episode, Kevin and Eli explore the reality of working with AI that lies while you pay, the evolution from saved prompts to voice-triggered workflows, and why validation loops matter more than model updates. From enterprise governance requirements to tech stack consolidation, this conversation cuts through the hype to reveal what actually works when deploying AI in real business contexts. Key topics covered: ✅ Why model reliability requires systematic validation, not perfect AI ✅ The shift from skills to snippets and voice-triggered workflows ✅ Enterprise governance requirements when litigation risk is involved ✅ Tech stack consolidation as AI tools mature beyond experimentation ✅ Cost economics driving procurement strategy changes ✅ Building quality control loops that catch hallucinations before implementation TIMESTAMPS: 00:00 — Intro and Sora commercial viability discussion 05:30 — Video generation landscape: Veo, SeeDance, Higgs Field 15:00 — Model quality regression and hallucination experiences 25:00 — Skills vs snippets: workflow evolution deep dive 35:00 — Enterprise governance and validation requirements 45:00 — Tech stack consolidation and platform comparisons 53:00 — Eli's transition and mental health focus Show Notes & Links: https://www.spark6.com/podcast Submit listener questions: elijah@spark6.com kevin@ascendlabs.ai Check out Kevin’s stuff: AscendAI: https://ascendlabs.ai/ Follow Kevin on LinkedIn: https://www.linkedin.com/in/kevinguywilliams/ Check out Eli’s Stuff: SPARK6 Agency: https://www.spark6.com/ Sign up for FREE AI Framework Friday Newsletter: https://www.spark6.com/newsletter Follow Elijah on LinkedIn: https://www.linkedin.com/in/elijahszasz/

Why Your AI Productivity Wins Are Making You Miserable

Kevin and Eli dive deep into the hidden costs of AI productivity gains, exploring how cognitive overload and social isolation are creating a new form of workplace burnout that organizations aren't prepared to address. In this candid conversation, they share their personal experiences with AI work density accomplishing 80-100x more work daily while feeling more exhausted than ever. The discussion reveals why the promise of AI efficiency is backfiring without proper human-centered implementation. Key topics covered: ✅ AI work density and the cognitive load crisis ✅ Why context switching between AI tasks creates decision fatigue ✅ The importance of pacing in AI-forward organizations ✅ How to identify what should (and shouldn't) be automated ✅ The role of human connection in an AI-augmented workplace ✅ Platform comparison: OpenAI vs Claude vs Gemini for team adoption ✅ The hidden costs of AI agent proliferation ✅ Why most organizations miss the pedestrian productivity wins Timestamps: 00:00 — Platform switching and AI adoption decisions 08:00 — Microsoft integration advantages and limitations 15:00 — Team adoption and accessibility considerations 25:00 — AI work density and cognitive load crisis 35:00 — Human connection vs AI interaction 42:00 — What to automate vs what to preserve 48:00 — Organizational capture of AI innovations 55:00 — Enterprise data integration challenges Explore practical AI implementation: https://assessment.ascendlabs.ai/ Book a conversation with Kevin: tidycal.com/kevinwilliams Show Notes & Links: https://www.spark6.com/podcast Submit listener questions: elijah@spark6.com kevin@ascendlabs.ai Check out Kevin’s stuff: AscendAI: https://ascendlabs.ai/ Follow Kevin on LinkedIn: https://www.linkedin.com/in/kevinguywilliams/ Check out Eli’s Stuff: SPARK6 Agency: https://www.spark6.com/ Sign up for FREE AI Framework Friday Newsletter: https://www.spark6.com/newsletter Follow Elijah on LinkedIn: https://www.linkedin.com/in/elijahszasz/