AI at Work

Matt Graham, Kevin Williams
  • 5.0（21則評分）
  • 創業

AI at Work is hosted by Matt Graham (CEO of Rapid Dev) and Kevin Williams (CEO of Ascend Labs). Each week delivers actionable insights on how artificial intelligence is reshaping jobs today, and how you can use it to advance your career. We unpack real-world tools, automation workflows, and emerging roles so you can stop chasing hype and start using AI to get things done. Whether you’re an individual contributor, team lead, or business owner, we show you what to build, what to ask for, and what to look for in a workplace moving at machine-speed.

  1. 8月6日

    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: https://www.google.com/search?q=https... – Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the https://resources.ascendlabs.ai/opena... Book a Call: https://www.google.com/search?q=https... 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

    Why Your AI Pilot Is Just a New Steam Engine

  2. 7月28日

    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 itMain quests vs. side quests: how to tell which AI work actually mattersThe flight risk hiding inside organizations that won't let curious talent experimentA detailed breakdown of an AI-powered phishing attack and how to protect yourselfPractical AI model cost management across Claude, GPT Work, Codex, and FableWork 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: https://www.google.com/search?q=https... – Free Tool: Take the https://assessment.ascendlabs.ai/ Deep Dive: Read the https://resources.ascendlabs.ai/opena... Book a Call: https://www.google.com/search?q=https... 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

    When Your Curiosity Becomes Your Biggest Business Risk

  3. 7月22日

    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: Ascend LabsLinkedIn: Follow Kevin on LinkedIn Free Tool: Take the AI Readiness AssessmentDeep Dive: Read the GPT Teams vs. Anthropic Teams comparisonBook a Call: Talk to Kevin on TidyCal Check out Matt’s stuff: LinkedIn: Follow Matt on LinkedInCompany: Rapid Dev on LinkedIn Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

    Your AI Tools Are Leaking and Nobody Told You

  4. 7月16日

    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-teamsCheck out Kevin’s stuff:Website: Ascend Labs LinkedIn: Follow Kevin on LinkedIn – Free Tool: Take the AI Readiness Assessment Deep Dive: Read the GPT Teams vs. Anthropic Teams comparisonBook a Call: Talk to Kevin on TidyCalCheck out Matt’s stuff:LinkedIn: Follow Matt on LinkedIn Company: Rapid Dev on LinkedIn –Direct Email: Reach out to Matt at mgram@rapiddevelopers.com

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

  5. 7月7日

    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 → Ascend Labs: 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/

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

  6. 6月24日

    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: → Ascend Labs: 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

    Why Claude Code Has Nothing to Do With Code

  7. 6月16日

    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: → Ascend Labs: 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/

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

  8. 6月9日

    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: Ascend Labs: 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

    The One Percent Problem That Creates 68% Productivity Gains
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簡介

AI at Work is hosted by Matt Graham (CEO of Rapid Dev) and Kevin Williams (CEO of Ascend Labs). Each week delivers actionable insights on how artificial intelligence is reshaping jobs today, and how you can use it to advance your career. We unpack real-world tools, automation workflows, and emerging roles so you can stop chasing hype and start using AI to get things done. Whether you’re an individual contributor, team lead, or business owner, we show you what to build, what to ask for, and what to look for in a workplace moving at machine-speed.

資訊

  • 創作者
    Matt Graham, Kevin Williams
  • 活躍年代
    2025年 - 2026年
  • 集數
    37
  • 年齡分級
    兒少不宜
  • 版權
    © 2025 Matt Graham, Kevin Williams
  • 節目網站
    AI at Work

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