Unlocked Professional: AI and the Future of Hiring

Jeff Midland | AI & Future of Work Enthusiast
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How great leaders hire, build, and keep teams, and which AI tools will actually help. Most companies are stuck in "experimentation theater". Buying AI tools that go nowhere while their teams are exhausted by the hype. Welcome to The Unlocked Professional, where we stop playing with AI and start running it like a business operation. Hosted by Jeff Midland, we interview the visionaries from Chief AI Officers to Workforce Futurists. We give you the "Cheat Code" for staying relevant. Learn to move from being just a worker to an Architect of the future. We dive deep into Human-Centric AI, Agentic workflows, and the ADOPT method to ensure you remain irreplaceable. Stop the social grinding and start building a real strategy that works with AI, not against it.

  1. 1d ago

    Impact Per Hour: The Metric Replacing Headcount in AI Hiring | Henrik Järleskog

    AI adoption stalls when leaders put off decisions and teams don't know where to start. In this episode, we sit down with Henrik Jarleskog, co-founder of Lead with AI and former strategy leader at Sodexo. Henrik shares how he automated his own job with AI agents, how to measure AI adoption, and why hiring should favor agency over past performance. Learn how teams can build AI fluency with a little daily practice and why redeploying people beats cutting them. Key Topics Automating your own job with AI agents Why leadership teams put off AI strategy decisions Measuring AI adoption and building AI fluency Hiring for agency and adaptability over CVs Critical thinking and the human side of recruiting Redeploying people instead of doing more with less Episode Timestamps 00:00 Introduction to Henrik Jarleskog and his path from Sodexo to Lead with AI 02:45 Running corporate strategy at Sodexo during the pandemic 06:07 How AI is changing the way people work 09:02 How Henrik taught himself to build AI agents and automate his own job 11:53 Showing his AI agents to leadership 14:49 Why AI adoption stalls inside organizations 18:04 Redefining productivity with AI 21:01 The skills and traits to hire for now 26:38 Why human interaction still matters in recruiting 28:59 Using AI tools to improve collaboration across teams 30:50 Why companies put off AI strategy decisions 32:31 Measuring AI adoption and building AI fluency in three weeks 36:22 Hiring for agency and adaptability over past performance 38:01 Why critical thinking matters more as AI spreads 41:36 The triple threat of competition companies now face 43:50 Why companies regret doing more with less Guest Links Website: https://www.leadwithai.co/about-us LinkedIn: https://www.linkedin.com/in/henrik-jarleskog-246294/ Keywords: AI Transformation, Future of Hiring, AI Fluency, AI Adoption, AI Agents, Recruitment, Hiring for Agency, Critical Thinking, Lead with AI, Sodexo, Henrik Jarleskog

  2. Oct 28

    Turning Relationships Into Filled Reqs With Artificial Intelligence | Harrison Franke

    Most agency recruiters spend the week on candidate calls, then panic prospect on Friday. In this episode, we sit down with Harrison Franke, co-founder and CEO of Recruitcha and Recruit GTM. Harrison explains how Recruitcha reads public hiring signals and pooled team networks to rank who to contact first. He also shares why he believes recruiters stay central when AI is only as good as the data behind it. Learn how better timing and cleaner data help recruiters reach the hiring manager most likely to respond. Key Topics Why business development is harder than sourcing for agencies Go-to-market engineering for recruiters Using hiring signals to rank outreach opportunities Why older job postings make a better outreach window Pooled networks and warm intro paths Why AI can't replace recruiter judgment Episode Timestamps 00:00 Introduction to Harrison Franke and the recruiter BD hamster wheel 00:58 Harrison's background in South Africa and early interest in building things 03:51 The real cost of running recruiting and BD at the same time 07:33 Why they pivoted from sourcing to business development 10:48 What go-to-market engineering means for recruiting 12:17 How the platform ranks hiring opportunities by signal strength 15:10 Judging opportunity quality, niche fit, and company signals 18:27 Early traction with 27 agencies and the time it saved 19:27 Why older job postings are often the best outreach window 20:54 Pooled networks and team-level warm intro paths 22:11 Why Recruitcha avoids LinkedIn automation 23:11 What testing different BD channels taught them 25:04 Integrations with CRM and sequencing tools 27:25 Why relevance beats creepy multi-platform outreach 29:17 Why AI can't replace recruiter judgment 32:37 What job data shows about role consolidation and AI-era hiring 34:03 How they test whether candidates can actually use AI tools 36:25 Why existing networks matter more once they're easier to use 37:33 Recruiters as the human filter in the AI era 39:26 The time audit that helped the agency build systems 41:08 Where to connect with Harrison and learn more about his work Guest Links Website: https://www.recruitcha.ai LinkedIn: https://www.linkedin.com/in/harrison-franke/ Keywords: Recruitment Agency, Recruiter Business Development, Go-To-Market Engineering, Hiring Signals, AI in Recruiting, Recruiting Technology, Warm Outreach, Pooled Networks, Recruitcha, Recruit GTM, Future of Hiring, Harrison Franke

  3. Oct 21

    What a Talent Engineer at Zapier Builds Instead of Another AI Sourcing Tool | Dan McCarthy

    Most AI recruiting tools get built the wrong way, and the fix starts with thinking like an engineer. In this episode, we sit down with Dan McCarthy, senior talent engineer at Zapier and builder of Shopify's talent engineering function. Dan shares how a path through jazz, bartending, and CrossFit shaped his approach to talent engineering, internal tooling, AI screening, and talent intelligence. Discover when a recruiting tool is worth building, how to count its true cost, and why learning speed may matter more than a resume. Key Topics Nonlinear career paths as an edge in AI-driven recruiting What a talent engineer does at Shopify and Zapier The hidden costs of building internal recruiting tools Building a talent intelligence MCP from public data sources How AI screening can expand candidate signal Why resumes may matter less than learning speed Episode Timestamps 00:00 Introduction to Dan McCarthy and why most AI recruiting tools are built the wrong way 00:53 Dan's path from jazz vibraphonist in Toronto to talent engineer 03:05 The books that shaped Dan's thinking and how Range reframed imposter syndrome 04:42 Why cross-pollinating skills matters in HR and recruiting 07:27 What a talent engineer does and Shopify's Life Story interview 09:19 Learning from a culture that encourages experimentation 10:10 From CrossFit gym owner to teaching himself front-end development and SQL 12:57 Why nontraditional practitioners are changing talent work 14:09 Dan's day-to-day at Zapier, from small utility builds to greenfield projects 16:10 Thinking like an engineer and why most builds fail the maintenance test 20:27 Running the numbers on total cost of ownership 22:26 When a sourcing tool is worth building and where surgical tools make sense 24:02 The false confidence of easy AI apps and why tech should free up candidate time 26:52 How Dan built the talent intelligence MCP from structured data sources 29:35 Using the system for dashboards, Q&A, skills, and intake briefs 31:40 Using data to improve closing calls and candidate conversations 34:21 Why resumes are losing value and learning speed matters more 37:33 Shopify's seven out of ten idea and why thinking outlasts tool familiarity 40:31 How AI screening expands signal and what a 15-minute conversation reveals 43:03 Rethinking interview design and the fear versus opportunity of AI screening 47:48 Hiring without resumes, senior roles, and reducing application friction 53:38 Where to connect with Dan and learn more about his work Guest Links LinkedIn: https://www.linkedin.com/in/iamdanmccarthy/ Keywords: AI Recruiting, Talent Engineering, Talent Acquisition, Recruiting Operations, Talent Intelligence, AI Screening, Skills-Based Hiring, Learning Agility, Future of Work, Zapier, Shopify, Dan McCarthy

  4. Oct 14

    He Built a Text Message Hiring Tool That Cut Hiring From 17 Days to 48 Hours | Jonathan Duarte

    Resumes used to tell recruiters who was worth calling, but AI has made them an unreliable signal. In this episode, we sit down with Jonathan Duarte, founder of GoHire and a 33-year HR technology veteran who helped build one of the first job boards. Jonathan shares his expertise on frontline hiring, text-based screening, SMS compliance, and the risks of opaque AI matching tools. Learn why recruiting leaders may need to add friction back into hiring to protect quality and compliance. Key Topics Why AI-written resumes undermined traditional screening Text-based screening and self-scheduling for frontline hiring The legal, bias, and compliance risks of AI hiring tools Skill validation and the return of friction in future hiring Episode Timestamps 00:00 Introduction to Jonathan Duarte and why AI resumes broke traditional recruiting 00:28 From AOL discs and early job boards to conversational AI in regulated enterprises 02:18 Jonathan's lifelong focus on process automation and lessons from Gateway 2000 05:38 Systems thinking, automation vs. AI, and why outputs must be defined 07:20 Moving to Tahoe and rebuilding life around movement 12:03 Referral hires vs. job boards 13:50 Selling the job distribution platform and seeing the recession coming 16:08 Why recruiting is an early economic signal 17:36 Why Jonathan stepped away and what happened next 18:30 Innovation in the AI era and why HR remains a people-centered field 20:22 What GoHire does for frontline hiring 22:42 Why many candidates respond and interview after work hours 23:38 Cutting time to fill from 14 days to 24–48 hours 26:26 Engaging career-site visitors more effectively 27:56 Why candidate data belongs to the client 30:08 Why SMS is more complex than simply sending a text 33:32 The risks of AI resume matching and the need for governance and validation 37:27 Where friction may return and how to right-size AI pre-screens 43:11 Human verification and skill validation 45:06 A four-level AI skills rubric 47:29 How roles are being redefined and why job seekers need a new strategy Guest Links Company Website: https://gohire.com/author-jduarte/ Personal Website: https://jonathanduarte.com/ LinkedIn: https://www.linkedin.com/in/bestlinkedinprofile/ Keywords: AI in Recruiting, Talent Acquisition, HR Technology, AI-Generated Resumes, Frontline Hiring, Text Recruiting, SMS Compliance, AI Governance, Skills-Based Hiring, Future of Work, GoHire, Jonathan Duarte

  5. Oct 7

    Most CEOs Know Less About Their Employees Than LinkedIn Does | Jason Averbook

    AI won't replace people, but it will replace the jobs and workflows we know today. In this episode, we sit down with Jason Averbook, a longtime HR technology leader and the entrepreneur behind the voice AI platform Savo. Jason shares his expertise on employee listening, durable skills, workforce planning, and the real barriers to AI adoption. Discover why 1990s processes won't survive in 2026 and how to own your relevance in an always-on era of change. Key Topics Why AI will replace jobs, not people Listening and other durable skills in an AI-first world Using voice AI to replace broken employee surveys Redesigning outdated processes, hiring, and workforce planning Episode Timestamps 00:00 Introduction to Jason Averbook and why the AI adoption question is wrong 02:19 Jason's early lessons from a teacher mom, a sales-driven dad, and tech tinkering 03:33 Managing hotels, experience design, and listening as a durable skill 04:59 Why the Bay Area still matters as a hub for innovation 06:29 What Leapgen stood for and why energy, audacity, and proof matter 07:53 Quitting at 23 and the cost of burning bridges 09:22 How AI makes it easier to pivot, take risks, and start something new 11:38 Why AI will change jobs, not replace people 14:18 Owning your syllabus and taking responsibility for your relevance 15:17 How Now to Next uses software to improve services and human outcomes 16:41 Why surveys are broken and voice captures richer employee sentiment 18:40 Using voice AI for culture, maturity, flight feedback, and customer experience 20:55 Why tools only matter if leaders act on what they learn 22:40 How Jason spots signals, handles uncertainty, and pivots quickly 26:17 Durable skills: critical thinking, curiosity, wisdom, and agency 27:46 Big company inertia and workforce planning with stale data 30:07 Resetting hiring around strengths, weaknesses, and role matching 32:32 Why faster broken systems aren't real innovation 35:11 Why the AI shift is always on, not an A-to-B technology swap 38:30 Transforming while keeping the lights on as cycles compress to months 43:27 Treating change as strategy and building a learning habit now 46:28 Closing thoughts on creating value, jobs, and knowledge Guest Links Website: https://www.nowtonext.ai/ LinkedIn: https://www.linkedin.com/in/jasonaverbook/ Instagram: https://www.instagram.com/jasonaverbook/ Substack: https://jasonaverbook.substack.com/ Keywords: Future of Work, AI Adoption, HR Technology, Employee Listening, Voice AI, Survey Fatigue, Durable Skills, Workforce Planning, Skills-Based Hiring, Now to Next, Savo, Jason Averbook

  6. Sep 30

    He's Not Selling Recruiting Tools. He's Teaching Recruiters to Build Their Own with AI | Jamie Lyons

    Struggling to keep up with the fast-moving AI landscape in talent acquisition? Jamie Lyons, Founder of The Rec Lab, joins Jeff to share how recruiters can transition from passive users to active AI builders. In this episode, he breaks down his leap from finance into AI-driven recruitment, how self-built tools and automation scale candidate workflows, and why non-technical professionals can build impactful AI systems without writing traditional code. Key Topics Jamie's career transition from accounting to AI-driven recruitment Scaling candidate capacity through automated workflows and custom tools Building DIY recruiting tools without a developer background Establishing controlled AI adoption and standardization across teams Deploying Claude, GitHub, Vercel, and MCPs for recruitment ecosystems Creating interactive, dynamic candidate information packets Change management and position yourself as the AI go-to in your company Episode Timestamps 0:00 Jamie's transition from finance into AI-driven recruitment 2:25 Overcoming early career constraints through creative AI experimentation 5:13 How artificial intelligence empowers recruiters with unprecedented scale 6:11 Why organizations need controlled AI adoption and governance standards 8:53 Shifting from traditional recruitment to tech-heavy, high-volume operations 15:18 Developing self-taught AI tools without a traditional software background 22:25 How automation transforms recruiting roles without replacing human judgment 24:42 Connecting tools via MCPs for unified data and workflow cohesion 29:03 Building dynamic candidate packets and interactive interview guides 42:20 Leveraging GitHub and Vercel to host shareable recruitment assets 61:34 Strategic value of building internal AI solutions for career growth 64:02 Where to follow Jamie and get involved with The Rec Lab Guest Links Website: https://www.thereclab.ai/ LinkedIn: https://www.linkedin.com/in/jamiejaylyons/ Keywords: Jamie Lyons, The Rec Lab, AI in recruitment, talent acquisition automation, recruiter enablement, non-technical AI tools, Model Context Protocol, recruitment technology, candidate experience, future of recruiting

  7. Sep 23

    Banana Bread Recipes, AI, and the Future of Hiring Talent | Brady Green

    Struggling with slow startup hiring, unrealistic candidate profiles, and low offer acceptance rates? Brady Green, Co-founder of Voyager Talent Solutions and former recruiting leader at Amazon, Twitter, and Square, joins Jeff to break down why most early-stage searches fail long before the first resume is submitted. In this episode, he explains how to calibrate founder expectations, why outbound sourcing habits from agency recruiting create corporate edges, and why AI can handle sourcing volume but human trust is required to close top candidates. Key Topics Why startup recruiting searches fail due to poor calibration rather than candidate scarcity Brady's transition from agency recruiting at Aerotek to scaling teams at Amazon, Twitter, and Square The pivotal moment at Amazon that forced a transition to data-driven, input-focused recruiting Contrasting enterprise talent systems with rapid, scrappy startup growth environments The Voyager model: calibrating expectations, hiring founding engineers, and building internal talent capability Overcoming the "purple squirrel" problem and helping founders define realistic hiring requirements Why technical talent uses filters to block automated AI outreach and how to stand out Balancing automation efficiency with human closing, relationship building, and candidate advocacy Episode Timestamps 0:00 Why startup searches fail before resumes ever arrive 0:24 Brady Green's recruiting leadership background at Amazon, Twitter, and Square 9:37 The Amazon data meeting that transformed Brady's approach to talent analytics 11:23 Building outbound sourcing capabilities inside enterprise recruiting teams 17:31 Key differences in recruiting culture when moving from Amazon to Twitter 19:23 Launching Voyager Talent Solutions to support seed through Series D founders 28:21 The "purple squirrel" problem and calibrating founder expectations 36:48 AI sourcing tools, automated candidate outreach, and message fatigue 43:50 Why effective talent acquisition requires a balance of automation and human connection 54:02 Where to find Voyager Talent Solutions and connect with Brady Green Guest Links Website: https://voyagertalent.com/ LinkedIn: http://linkedin.com/in/brady-green-2304b7b/ Keywords: Brady Green, Voyager Talent Solutions, startup recruiting, talent acquisition, recruiting strategy, outbound sourcing, technical recruiting, hiring calibration, Amazon recruiting, Twitter recruiting, candidate experience, AI sourcing, talent strategy

  8. Sep 16

    She Built AI Automations for Army HR — 1.4 Million People, Zero Jobs Lost | Kris Saling

    Struggling to navigate the complexities of enterprise AI adoption and workforce transformation? Kris Saling, Director of Workforce Transformation and former Chief Technology Advisor for the Assistant Secretary of the Army, joins Jeff to share how she approaches large-scale talent management. In this episode, she breaks down her "AI Driver's Ed" framework for executive leadership, why traditional resumes are breaking in an AI-heavy hiring environment, and how organizations can eliminate millions in operational overhead without removing human judgment. Key Topics Kris Saling’s 25-year U.S. Army career and transition into enterprise workforce transformation The "AI Driver's Ed" framework: guiding leaders to use AI safely, effectively, and responsibly Why resumes fail in modern talent acquisition and how performance-based assessments replace them Military-scale talent matching lessons: navigating data quality, job analysis, and change management The Durable Core, Middleware, and Disposable Edge mental model for skills and system architecture Eliminating transactional administrative friction to create space for high-impact strategic work Evaluating AI tools and candidates by focusing on the core decision rather than the technology Building custom internal agents for research, contract review, budgeting, and institutional memory Episode Timestamps 0:00 Kris Saling's tech background and talent management approaches 0:28 Why executive leadership requires AI "Driver's Ed" over basic adoption hype 4:33 How AI application volume is breaking traditional resume screening 6:00 Lessons from military record briefs and direct commissioning pipelines 13:32 Overcoming data quality and adoption hurdles in large-scale modernization 17:20 The Durable Core, Middleware, and Disposable Edge skills architecture 22:24 Identifying genuine AI capability versus polished buzzword fluency 25:42 Starting with human decisions to design effective AI workflows 28:22 Developing custom internal agents for research, contracts, and budgeting 33:29 Using AI calendar audits to reduce executive meeting overload 42:41 Where to follow Kris and track her workforce transformation work Guest Links Website: https://kristinsaling.com/ LinkedIn: https://www.linkedin.com/in/kris-saling Instagram: https://www.instagram.com/kcsaling Keywords: Kris Saling, workforce transformation, AI in talent management, defense innovation, executive leadership, AI adoption, skills-based hiring, agentic workflows, change management, operational efficiency

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How great leaders hire, build, and keep teams, and which AI tools will actually help. Most companies are stuck in "experimentation theater". Buying AI tools that go nowhere while their teams are exhausted by the hype. Welcome to The Unlocked Professional, where we stop playing with AI and start running it like a business operation. Hosted by Jeff Midland, we interview the visionaries from Chief AI Officers to Workforce Futurists. We give you the "Cheat Code" for staying relevant. Learn to move from being just a worker to an Architect of the future. We dive deep into Human-Centric AI, Agentic workflows, and the ADOPT method to ensure you remain irreplaceable. Stop the social grinding and start building a real strategy that works with AI, not against it.

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