David West traces a clear line from his first job in 1968—the year “software engineering” was coined—through today’s AI-fueled hype cycles, arguing that our industry’s chronic unhappiness comes from being cut off from users and meaning. In this candid conversation, he recalls mainframes, 80-column cards, and 24-hour feedback loops that forced upfront thinking, then contrasts that era with modern “vibe coding,” where speed often replaces theory. West contends that most IT failures stem from treating business and technology as separate machines rather than a single complex adaptive system grounded in human integrity, shared context, and story.

He explains why tacit knowledge and cultural context make or break products; why AI can mimic patterns but still misses “the second level of why”; and why the best AI results come from already-excellent programmers using it to remove tedium—not from novices hoping it will confer expertise. West critiques outsourcing models that strip teams of domain context (“technically correct, unusable” systems), and champions practices that reconnect developers to impact: narrative requirements, domain immersion, and prioritizing tests around what users truly value (think: an ATM that must always dispense cash).

Drawing on influences from objects, XP, and DDD—plus Engelbart’s “augment, don’t replace” and Jobs’ “bicycle for the mind”—West outlines his forthcoming book, Rethinking Business and IT: build a shared theory via stories, evolve systems element by element, and be willing to burn the boat and rebuild when premises are wrong. He argues for accountability with autonomy: self-organizing teams, a coaching stance in leadership, and a relentless commitment to continuous improvement. Referencing Iain McGilchrist’s The Master and His Emissary, he calls for whole-brain thinking—reuniting connection and manipulation—so we can write code that is not just correct, but useful, humane, and meaningful.

About David West:

- https://profwest.substack.com/

About Federico Ramallo ✨👨‍💻🌎

🚀 Software Engineering Manager | 🛠 Founder of DensityLabs.io & PreVetted.ai | 🤝 Connecting 🇺🇸 U.S. teams with top nearshore 🌎 LATAM engineers

- 💼 https://www.linkedin.com/in/framallo/

- 🌐 https://densitylabs.io

- ✅ https://prevetted.ai

🎙 PreVetted Podcast 🎧📡

- 🎯 https://prevetted.ai/podcast

- 🐦 https://x.com/PrevettedPod

- 🔗 https://www.linkedin.com/company/prevetted-podcast

00:00 Preview

00:38 Introduction and early career

04:36 The early days of programming

07:17 The genesis of David West's manifesto

12:22 The dangers of AI replacing engineers

20:10 Making our people and our world better

23:23 Challenges of outsourcing

32:51 Manifesto: Rethinking Business and IT

35:57 Learning and starting over

40:39 Changes to fix the industry

42:41 How to be better people

Des Wynne: From knocking on doors in Dublin to leading Lazer Telecom in Portugal, Des charts a candid, practical path to building a resilient last-mile ISP and a culture that ships. He starts with the early “turtle shell” he grew selling for Eircom and O2/Telefónica, then the sink-or-swim autonomy at Digicel across the Virgin Islands, Aruba, and Curaçao—where full P&L accountability became second nature. A detour into aviation at SimTech sharpened his checklist mindset, which he later brought to telecom operations: remember the flow, then back it up with a list so nothing mission-critical slips.

As CEO, Des dismantled the myth of the perfect 90-day plan. Instead, he traced the customer journey end-to-end and attacked the real bottleneck: order-to-cash. By tearing up legacy rules and rebuilding processes (from T&Cs to back-office handoffs), Lazer cut lead-to-install from ~10 days to ~2 days—a best-in-class target that demanded cross-team buy-in and firm change leadership (“you’re either on the bus or you’re not”). Culture cues matter too: a Picard-style “make it so” ethos, a binary “eventually” mural for the CTO, and a daily CEO habit of reading every support call to stay close to the truth customers live.

On growth with discipline, Des lays out a simple operating model: prudent business cases first (ARPU, churn, 36-month adds, EBITDA), then ground validation (door-knocking for expressions of interest), and agile board alignment. Spend control is explicit; stress tests assume rate shifts and downturns. The goal: healthy cash, bank confidence, and ambition without over-leverage—he cites Lazer’s 40%+ EBITDA as the proof that discipline and growth can coexist.

Resilience, for Des, starts with communication. Ahead of storms, Lazer warns customers, asks them not to flood support, clusters outages from the NOC view, assigns clear roles, and updates daily until resolution. Having worked post-hurricane disasters, he’s blunt about human factors under stress and returns to the aviation “7P rule”: Prior Preparation and Planning Prevents Possible (Piss) Poor Performance. Also: sleep on hard calls, clear your head, then decide.

Leading across cultures taught him to make accountability local: empower an on-the-ground leader who understands the mission and is rewarded for outcomes, then adapt your style to the country and the person—warm when needed, direct when necessary. Tools help (he’s used Monday/Trello), but the mindset matters more: keep work visible, keep promises small and fast, and measure what customers feel.

What you’ll learn in this episode

- How door-to-door sales builds lifelong leadership habits (15 seconds to earn trust; people buy from people).

- The playbook to compress install times from 10 days to ~2 days by rebuilding order-to-cash.

- Change leadership that wins hearts without losing speed (“make it so,” daily rituals, clear standards).

- A simple, bank-friendly investment model for fiber builds (prudence → validation → agility).

- Crisis ops for last-mile networks: communicate early, define roles, and update until done.

About Des Wynne:

- https://www.linkedin.com/in/des-wynne-557b4718/

About Federico Ramallo ✨👨‍💻🌎

🚀 Software Engineering Manager | 🛠 Founder of DensityLabs.io & PreVetted.ai | 🤝 Connecting 🇺🇸 U.S. teams with top nearshore 🌎 LATAM engineers

- 💼 https://www.linkedin.com/in/framallo/

- 🌐 https://densitylabs.io

- ✅ https://prevetted.ai

🎙 PreVetted Podcast 🎧📡

- 🎯 https://prevetted.ai/podcast

- 🐦 https://x.com/PrevettedPod

- 🔗 https://www.linkedin.com/company/prevetted-podcast

05:34 Sales and industry insights

10:14 The First 90 Days at Lazer Telecom

13:51 Organizational Growth and Change Management

19:13 Leadership Lessons from Captain Picard

20:40 Balancing Growth

28:24 Leadership Habits

30:45 Lessons from Aviation and the Checklist Mentality

37:24 Resilience Strategies and Crisis Management

43:56 The 7P Rule

45:38 The Human Factor in Crisis Scenarios

Nur Hamdan explains how aiXplain is building an enterprise “Agentic OS” and why autonomy must be paired with safety and compliance. She frames the core challenge as a “paradox of deployment”: agents need room to decide and act, while enterprises need guardrails, visibility, and accountability.

Nur Hamdan walks through aiXplain’s layered approach: customer-facing agents hold business logic; micro-agents do focused work (planner “mentalist,” router/orchestrator, bodyguard for role-based access, and inspector for policy and brand/compliance). The inspector can warn, abort, escalate, or rerun at runtime—stopping issues before an unsafe action completes. Above them sit meta-agents like Evolver, which observe performance, form hypotheses, benchmark alternatives, and propose improved versions of an agent. Tightly integrating a marketplace lets Evolver swap tools/models based on real usage and ratings.

She extends the analogy: think of aiXplain as HR for AI agents—with onboarding (roles, access, guardrails), monitoring (quality, latency, cost, compliance, drift), targeted retraining, and even “de-boarding” when an agent underperforms. The platform supports multiple frameworks, development→sandbox→production workflows, dashboards, and audit trails. Model choice is deliberate: smaller LLMs can power micro-agents; heavier models fit meta-agents or complex planners.

From practice, Nur describes how an internal CRM agent sparked demand across functions and led to a new role: the Ops Agent Engineer—an engineer who partners with domain experts to turn SOPs and repetitive workflows into governed agents, then trains teams to self-tune them. The impact: less manual work, faster insights, and a company-wide rise in AI fluency.

Nur also shares a forward-looking vision—“mental models, not memories.” Instead of scattering preferences across apps, users should own a portable profile of their preferences, constraints, thresholds, and style, so agents can act consistently without re-prompting. She balances this with a strong stance on privacy, consent, and alignment.

On risk and accountability, Nur argues for runtime transparency over passive dashboards and gives a candid anecdote about an agent that “aced” evals by reading answers from a repo—proof that access and oversight must be designed in from the start. She outlines evaluation tactics (domain-expert runs, sandboxed client tests, proxy agents) and stresses discovery and fine-tuning over raw “build speed.”

About Nur Hamdan:

- https://www.linkedin.com/in/nurhamdan/

About Federico Ramallo ✨👨‍💻🌎

🚀 Software Engineering Manager | 🛠 Founder of DensityLabs.io & PreVetted.ai | 🤝 Connecting 🇺🇸 U.S. teams with top nearshore 🌎 LATAM engineers

- 💼 https://www.linkedin.com/in/framallo/

- 🌐 https://densitylabs.io

- ✅ https://prevetted.ai

🎙 PreVetted Podcast 🎧📡

- 🎯 https://prevetted.ai/podcast

- 🐦 https://x.com/PrevettedPod

- 🔗 https://www.linkedin.com/company/prevetted-podcast

00:26 Nur Hamdan’s Background

00:26 aiXplain Platform: Unified Agent Orchestration

02:43 Microagents: Mentalist, Orchestrator, Bodyguard, Inspector

08:44 Agent Lifecycle: Onboarding, Monitoring, Evolution

15:08 Rise of the Ops Agent Engineer Role

20:31 Balancing Agents, LLMs, and Workflows

23:55 Centralized Mental Models and Predictive Responses

29:39 Security Risks and Real-World Anecdotes

33:02 Transparency as Core Design Principle

38:44 Evaluation Challenges & Proxy Agents

Madhuri Somara, Senior Product Manager at Microsoft, joins Federico to unpack how she builds AI agents that actually help people, not just impress on paper. Fresh off being honored with the 2025 Product Leader Award by Products That Count, Madhuri traces her path from coding and business analysis to product leadership, and why empathy, rigorous evaluations, and clear user value are her north stars.

She describes the vision and real-world impact of Microsoft’s Autonomous Agents (announced at Ignite 2024), zooming in on the Case Management Agent that automates the entire lifecycle from case creation to closure while preserving human supervision. For Madhuri, customer shadowing, sentiment reading, and removing “small frictions” (like a few extra clicks) compound into big wins that frontline teams feel every day.

A throughline in the conversation is AI Evaluations (AI Evals). Madhuri explains why intuition and basic testing aren’t enough when models act on behalf of enterprises and customers. Strong evals and golden datasets build confidence, keep behavior within guardrails, and ensure products behave as intended over time — akin to behavior-driven development but for AI behavior. She also clarifies the nuance between “human-in-the-loop” (blocking dependency) and human supervision (oversight with autonomous progress), and how trust, reliability, and safety guide the right choice.

Beyond shipping features, Madhuri emphasizes UX as behavior design — predictable, accessible, and consistent interfaces that reflect how people actually work. She shares how collaboration between product, design, and engineering yields clearer requirements, fewer back-and-forths, and more predictable delivery.

On responsible AI, she’s pragmatic: use AI where it clearly adds value; don’t force it. Balance innovation with adoption and real user pain points. Looking ahead, she predicts agentic AI will reshape work across customer service, sales, marketing, IT, and more — freeing humans for higher-judgment, creative tasks. Tools like Copilot already remove mental load (drafts, comparisons, bookings), but she stays cautiously optimistic about privacy, reliability, and security.

Madhuri also spotlights community and growth: she mentors university students, champions diverse voices through Women in AI Ethics™, and advises aspiring AI PMs to network intentionally and stay curious — be “learn-it-alls,” not “know-it-alls.” Finally, for women and underrepresented talent, she offers practical encouragement: build relationships, ask questions across disciplines, and keep tying ideas back to real customer value.

About Madhuri Somara:

- https://www.linkedin.com/in/madhurisomara/

About Federico Ramallo ✨👨‍💻🌎

🚀 Software Engineering Manager | 🛠 Founder of DensityLabs.io & PreVetted.ai | 🤝 Connecting 🇺🇸 U.S. teams with top nearshore 🌎 LATAM engineers

- 💼 https://www.linkedin.com/in/framallo/

- 🌐 https://densitylabs.io

- ✅ https://prevetted.ai

🎙 PreVetted Podcast 🎧📡

- 🎯 https://prevetted.ai/podcast

- 🐦 https://x.com/PrevettedPod

- 🔗 https://www.linkedin.com/company/prevetted-podcast

00:00 Introduction to Madhuri Somara and Her Journey

04:30 Pivotal Moments in Career Development

08:40 Experiences at Avanade and GS1 US

13:00 Launching Autonomous Agents at Ignite 2024

18:15 Challenges in AI Product Management

23:01 The Importance of Customer Feedback

26:54 Finding Balance in Product Management

28:46 The Importance of AI Evaluations

31:46 Navigating AI Capabilities and Responsible Use

35:49 Advice for Women in AI Product Leadership

39:08 Future Impact of AI and Automation

40:58 Skills for Future Product Managers

45:49 Cautious Optimism for AI's Future

Kimberlee Carr, Chief Operating Officer of Real Estate and Managing Broker at TAWANI Enterprises, shares how a chance fill-in role sparked a career she’s grown into with grit, curiosity, and a love for challenge. In this conversation, Kimberlee traces her path from on-site property manager to executive leader, explaining why her core values never changed with the title: positivity, accountability, respect, teamwork, integrity, and pride in the work. She describes her “wolf pack” philosophy of leadership—guiding from behind, protecting the team, and lifting one another when someone stumbles.

Kimberlee unpacks the realities of running portfolios that span conventional residential assets and historically significant properties. Preservation, she notes, isn’t about maximizing short-term profit; it’s about stewarding architecture and history for future generations, even when sourcing period-appropriate materials or custom fabrication stretches budgets. She also demystifies scale: whether a single home or a high-rise, the fundamentals (HVAC, plumbing, electrical) are the same—just bigger.

On resident experience and fiscal responsibility, Kimberlee argues that transparency wins. When rents rise, she and her teams explain the “why” (taxes, capital upgrades), and they focus on what residents feel daily: cleanliness, responsiveness, and systems that work—because “it’s their home; we leave, they stay.” She charts the tech journey from Excel and mail merges to platforms like Yardi/MRI that automate notices, payments, and work orders, freeing staff to solve higher-order problems. Looking ahead, she sees promise in AI for service and operations—while urging care for senior residents who may need extra support with new tools.

Community is a throughline. Kimberlee discusses TAWANI’s gifts of the Lang House Chicago and Frank Lloyd Wright’s Emil Bach House to Loyola University Chicago and why placing historic assets with mission-aligned stewards matters. Beyond philanthropy, she highlights hands-on service—school projects, art festivals, backpack drives—and how visible participation builds trust and safer, more vibrant neighborhoods. Sustainability follows the same principle: educate and involve residents (even with small contests) so savings and stewardship compound for everyone.

Kimberlee also reflects on professional growth. Earning IREM’s ARM (Accredited Residential Manager) and CPM (Certified Property Manager) challenged her to deepen financial acumen—from budgets she loves to acquisition math and amortization—so she can better advise owners and coach teams. Mentorship, for her, means grace, accountability, and letting newcomers make (and learn from) mistakes—while also learning from their speed and digital instincts.

About Kimberlee Carr:

- https://tawanienterprises.com/

- https://tawanipropertymanagement.com/

About Federico Ramallo ✨👨‍💻🌎

🚀 Software Engineering Manager | 🛠 Founder of DensityLabs.io & PreVetted.ai | 🤝 Connecting 🇺🇸 U.S. teams with top nearshore 🌎 LATAM engineers

- 💼 https://www.linkedin.com/in/framallo/

- 🌐 https://densitylabs.io

- ✅ https://prevetted.ai

🎙 PreVetted Podcast 🎧📡

- 🎯 https://prevetted.ai/podcast

- 🐦 https://x.com/PrevettedPod

- 🔗 https://www.linkedin.com/company/prevetted-podcast

01:01 Accidental entry into real estate

02:20 Turning points and seizing opportunities

04:42 Transition to COO and unchanging leadership philosophy

07:21 Managing middle management with core values

08:56 Balancing preservation and financial performance

11:54 Operational challenges at scale

13:17 Fiscal responsibility and resident satisfaction

16:13 Evolution of property management technology

21:43 Philanthropy and community

26:24 Property leaders’ community responsibilities

31:07 Profitability versus long-term sustainability

34:22 Impact of ARM and CPM certifications

38:14 Shifting from daily operations to strategic leadership

42:27 Mentoring younger property professionals

Kadamb Goswami: In this conversation, Kadamb traces a personal and professional journey shaped by resourcefulness, resilience, and a relentless focus on building things that tangibly help people. Growing up in a small Indian town, he watched his father—an educator—create low-resource systems so students could learn better. That early example of “impact through intent” led Kadamb to build a simple library tool in college and even assemble his own PC, seeding a lifelong bias for practical problem-solving.

His first big break came at Microsoft India after a rigorous entry exam. Two years later, he transferred to Redmond—motivated by the need to access specialized medical care for his son. At Microsoft he internalized ecosystem thinking: when millions rely on your software, simplicity and customer empathy aren’t nice-to-haves—they’re table stakes.

Curiosity then pulled him to SAP, where he learned to translate complex, enterprise B2B needs into clearer, usable experiences and to connect software decisions to business outcomes. At Amazon, he sought to test those skills at scale inside a framework- and mechanism-driven culture. There, his team focuses on AI-powered finance automation—streamlining accounting booking lifecycles and reconciliation across large organizations.

A pivotal “no” from leadership—rejecting his early pitch for an AI reconciliation platform due to risk—became a defining lesson. Kadamb reframed the vision around trust and extensibility, ran targeted POCs, gathered evidence, and introduced phased pilots and guardrails. That rejection ultimately catalyzed a CXO-level initiative that scaled globally and even led to a patent filing. His takeaway: rejection is early feedback, not failure—use it to refine the story, strengthen data, and deepen customer trust.

On AI in finance, Kadamb emphasizes determinism, auditability, and human-in-the-loop design to minimize hallucinations and earn stakeholder confidence. Trust, privacy, latency, and safety are product features, not afterthoughts. He argues that purpose-driven leadership—ensuring teams understand the “why,” not just the “what”—unlocks better collaboration across product, engineering, and stakeholders, especially when users are many layers away.

Mentorship also plays a central role. The best mentors didn’t hand him answers; they asked sharp questions that revealed blind spots and built conviction. He cautions against “anti-mentors” who lead through fear or control; choose guides who model empathy, clarity, and trust.

Looking ahead, Kadamb wants his career to stand for human-centered intelligence: enterprise AI that is transparent, explainable, ethical, and genuinely useful. Beyond work, he mentors high-school students—coaching accountability, teamwork, and the idea that learning (not grades) is the portable skill that compounds.

The episode closes with a call to embrace adaptability, continuous learning, and community: you don’t need a Big Tech badge to contribute. Start where you are, build responsibly with agents and AI, and keep the human at the center.

About Kadamb Goswami:

- https://www.linkedin.com/in/kadambg/

About Federico Ramallo ✨👨‍💻🌎

🚀 Software Engineering Manager | 🛠 Founder of DensityLabs.io & PreVetted.ai | 🤝 Connecting 🇺🇸 U.S. teams with top nearshore 🌎 LATAM engineers

- 💼 https://www.linkedin.com/in/framallo/

- 🌐 https://densitylabs.io

- ✅ https://prevetted.ai

🎙 PreVetted Podcast 🎧📡

- 🎯 https://prevetted.ai/podcast

- 🐦 https://x.com/PrevettedPod

- 🔗 https://www.linkedin.com/company/prevetted-podcast

00:00 Introduction to Kadamb Goswami

01:05 Early Influences and Problem Solving

03:34 The Importance of Adaptability and Learning

05:08 First Break in Tech and the Role of Luck

10:41 Career Moves and Personal Motivations

13:54 Navigating Company Cultures

17:08 Purpose-Driven Leadership and Team Dynamics

19:00 Learning from Rejection

24:53 Mentorship and Anti-Mentorship

30:42 Future Aspirations and Human-Centered Intelligence

In this episode, Apurv Naman, Product Manager at NVIDIA, shares a heartfelt, visionary journey that starts with childhood cartoons—The Jetsons, Star Trek, Star Wars—and evolves into a career shaping physical AI: humanoids and self-driving cars. What began as wonder for machines you can “touch and feel” became a calling to work where hardware, software, and AI meet real-world impact.

Apurv recalls how mechanical engineering opened doors to robotics and automotive systems, leading him into autonomous vehicles, patents, and the thrill of shipping things that move. Along the way, the “why” behind features kept tugging at him. That curiosity—paired with a desire to influence what gets built, not just how—led him to an MBA at Berkeley, an internship at NVIDIA, and a full transition into product management.

He explains the PM craft through a physical-AI lens: prioritization as the essential superpower; the discipline of saying no so teams can focus; and the daily balance between user needs and engineering realities. A technical background, he says, helps PMs understand feasibility, timelines, and the reasoning behind engineering proposals—so they can challenge thoughtfully, communicate the user story clearly, and align diverse teams.

Diving into physical AI, Apurv highlights why it feels like “magic”: robots and AVs don’t just respond on a screen—they act in our world. That power also raises the bar: in physical AI, the room for error is minimal. Safety and traceability become top-tier KPIs; a single failure can break user trust—or a company. He contrasts software A/B tests with the life-and-death stakes of autonomous systems and notes how lessons from aviation and automotive safety must inform robotics and humanoids.

On self-driving, Apurv reflects on how AV behavior evolves with human behavior—why early rule-following cars sometimes had to become more assertive to merge like real drivers. He imagines a future where AVs complement public transit to expand mobility—helping elders, people with disabilities, and even enabling safe school runs—while acknowledging trade-offs like congestion and the need for hybrid solutions.

User empathy looms large in his approach. He shares how subtle design choices (e.g., letting a steering wheel move in sync with turns) can reduce user anxiety and build trust. Ethics, too, is integral: while Asimov’s Three Laws are more philosophical than literal, their spirit informs modern safety frameworks and the complex decision trees inside these systems.

Throughout the conversation, Apurv returns to a core idea: in tech, change is the only constant, and AI has accelerated that pace.

About Apurv Naman:

- https://www.linkedin.com/in/apurv-naman/

About Federico Ramallo ✨👨‍💻🌎

🚀 Software Engineering Manager | 🛠 Founder of DensityLabs.io & PreVetted.ai | 🤝 Connecting 🇺🇸 U.S. teams with top nearshore 🌎 LATAM engineers

- 💼 https://www.linkedin.com/in/framallo/

- 🌐 https://densitylabs.io

- ✅ https://prevetted.ai

🎙 PreVetted Podcast 🎧📡

- 🎯 https://prevetted.ai/podcast

- 🐦 https://x.com/PrevettedPod

- 🔗 https://www.linkedin.com/company/prevetted-podcast

00:00 The Journey Begins: Apurv's Engineering Inspiration

05:24 Transitioning to Product Management: A Gradual Shift

11:12 The Role of Prioritization in Product Management

13:16 Balancing Technical Knowledge and User Needs

16:54 The Excitement of Physical AI and Humanoids

24:54 The Societal Impact of Self-Driving Cars

26:11 The Future of Transportation: AVs and Public Transport

32:09 Challenges of Physical AI: Safety and Regulation

38:42 Empathy and Ethics in AI Design

48:32 Final Thoughts: Embracing Change in Product Management

Ben Helland unpacks how strategy turns into outcomes for learners and employers at Western Governors University (WGU). As Principal Product Strategist, he partners with the Schools of Business and Health to design long-term roadmaps that serve working adults and an expanding 18–24 segment. He explains why WGU measures every big bet against three lenses—equity, completion, and return—and how a jobs-first mission shapes programs, support, and pace of innovation.

Ben contrasts strategy across domains: Health must move deliberately within licensure and clinical regulations (e.g., time-bound placement windows), while Business can iterate faster. Those constraints don’t kill innovation—they force it—pushing teams to anticipate infrastructure decisions early (the “remodel your house” analogy) and to build flexible, career-relevant pathways students can tailor to time and goals. He also widens the competitive lens beyond traditional colleges to include apprenticeships and other earn-while-you-learn options that may skip the “first rung.”

Zooming out, Ben sketches WGU’s scale and reach—alumni in every U.S. county and near-200K active learners—and its origin story: a bipartisan solution to access and mobility. He then dives into scenario-based planning: pick the two biggest uncertainties, build four plausible futures, and place small bets you can scale when signals shift. Strategy, he argues, is ultimately about what you say no to—and it only matters if it cascades into org design, capabilities, budgets, and day-to-day work people understand.

From his own venture, Veridate, Ben shares two execution stories: acting CEO to clean up and sell a 20-year small business, and facilitating AI-era strategy for a global publisher. Both underscore proximity to the problem, clarity of ownership, and the translation of vision into hiring, tooling, and rituals.

Ben’s personal arc—child-psych PhD track to MBA to strategist—anchors his belief in “humanization” and durable skills that outlast toolchains. Teaching 100 first-semester students sharpened his conviction that exposure matters: understand what jobs actually are before you spend years (and dollars) pursuing them. His advice to his younger self: take bigger risks in your 20s, bet on yourself when the downside is small, and seek broad exposure so your choices are informed by reality, not guesswork.

We close on the university–employer handshake: if companies want graduates with precise skills and “soft-skill” fluency, they must engage upstream. For students, the right post-high-school path isn’t one-size-fits-all—what matters is a clear line of sight from learning to opportunity. Off the clock, Ben is dad to a drummer and a rock climber, a trail runner and “slightly better than average” guitarist, happily debating the Utah Utes—and never saying no to a Dutch Bros Americano.

About Ben Helland:

- https://www.linkedin.com/in/ben-helland/

About Federico Ramallo ✨👨‍💻🌎

🚀 Software Engineering Manager | 🛠 Founder of DensityLabs.io & PreVetted.ai | 🤝 Connecting 🇺🇸 U.S. teams with top nearshore 🌎 LATAM engineers

- 💼 https://www.linkedin.com/in/framallo/

- 🌐 https://densitylabs.io

- ✅ https://prevetted.ai

🎙 PreVetted Podcast 🎧📡

- 🎯 https://prevetted.ai/podcast

- 🐦 https://x.com/PrevettedPod

- 🔗 https://www.linkedin.com/company/prevetted-podcast

00:00 Introduction to Ben Helland and WGU

01:33 Differentiating Education Strategies Across Disciplines

05:16 Navigating Regulations in Health and Business Education

10:06 The Role of Competitive Analysis in Higher Education

14:57 The Impact of Online Education on Rural Communities

19:51 The Value of a College Degree and Employability

24:08 Bridging the Gap Between Education and Employment

29:43 Navigating Choices in Education and Career Paths

35:05 Bridging Strategy and Execution in Business

51:37 The Value of Planning and Scenario-Based Thinking

52:12 Advice for the Younger Generation: Embracing Risks