Regular Expressions

Organizations everywhere are rushing to implement AI, often measuring success by how many employees are actively using the tools. But treating AI adoption as a simple numbers game completely misses the mark. When speed becomes the primary goal, critical thinking is the first casualty.In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) welcome Rebecca George, an expert in organizational change management, AI strategy, and executive development. Rebecca shares a cautionary tale of using AI to synthesize interviews to save eight hours of work, only to spend two weeks cleaning up a political mess caused by algorithmic bias.The conversation explores why traditional change management no longer works, how Employee Resource Groups are the secret weapon for testing AI guardrails, and why parents and individuals must take AI safety into their own hands rather than trusting big tech. Rebecca also pulls from her background in theater to explain how leaders, particularly women in tech, can turn their professional triggers into their greatest superpowers.In This Episode, You'll Learn:Why measuring AI success by license usage is a massive mistake.The difference between outdated change management and true change leadership.A real-world example of how AI bias created a stakeholder nightmare.Why speed is a false currency when it comes to generative AI output.How to use Employee Resource Groups to rigorously test AI platforms.How principles from the theater can help you own your space in the boardroom.The Five Questions: A plea to ban the phrase "human in the loop" and a hilarious story involving a major wardrobe malfunction in front of a college class.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.comRebecca George | https://takeyourspace.com

The traditional software development life cycle used to follow a fairly predictable breakdown of time spent on analysis, design, coding, and testing. Now that AI agents are capable of generating the code itself, those old percentages are being completely flipped upside down.In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) examine how AI is changing the daily reality of software delivery for both Greenfield (brand new) and Brownfield (legacy) projects. They discuss how a heavy reliance on upfront spec writing might actually be a return to Waterfall development, and debate the productivity differences between a small AI-assisted team versus a traditional enterprise pod.The conversation also covers the massive opportunity AI presents for modernizing decades-old COBOL and Fortran systems, along with a hilarious cautionary tale about a vengeful developer who used an early internet translator to sabotage a codebase.In This Episode, You'll Learn:How the traditional breakdown of software development time is shifting in the AI era.Why Greenfield projects now require heavily front-loaded analysis and design phases.The debate over whether spec-based AI development is essentially just Waterfall.How AI can safely untangle and modernize massive legacy systems using the Strangler Fig pattern.A funny story from the 1990s about a disgruntled consultant weaponizing German code comments.Why the demand for deep problem-solving skills will always outpace the demand for writing raw syntax.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

The tech industry moved fast and broke things during the rise of social media, leaving society to figure out the consequences of screen addiction and algorithmic feeds years later. Now, artificial intelligence is evolving at a much faster pace, and the conversation around guardrails is already struggling to keep up.In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) look at the realities of AI safety, governance, and personal responsibility. They discuss the lack of clear guidance from governments and tech giants, which forces business leaders and parents to figure out their own rules. Noah shares why he completely uninstalled a powerful autonomous AI agent due to privacy concerns, and Ben highlights the growing issue of "Shadow AI" in the workplace where employees quietly use unauthorized tools to get their jobs done.The conversation explores how we can attempt to avoid repeating the mistakes of the past and build healthier habits with the next generation of technology.In This Episode, You'll Learn:The clear parallels between the early days of social media and the current AI boom.Why waiting for government regulation or big tech guidance is a losing strategy right now.The privacy and security risks of running autonomous AI agents on your personal devices.How "Shadow AI" is quietly taking over corporate workflows.The challenge of defining responsible AI usage in universities and at home.A look at current statistics on how many adults and employees are actually using AI daily.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

The ability to generate software with AI has revived the "Build vs. Buy" debate. If a team can spin up a custom CRM or invoicing tool in a few days using AI agents, the value of paying for expensive monthly SaaS subscriptions comes into question.In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) discuss whether the SaaS business model is actually in trouble. They share how they used AI to build bespoke tools for their own firm, effectively replacing some commercial software. The conversation then shifts to the enterprise perspective, where factors like SOC2 compliance, maintenance, and vendor liability often outweigh the benefits of custom builds.They also explore the concept of "Shadow AI" replacing Shadow IT, the frustration with low-quality AI features bolted onto existing products, and why the biggest SaaS players are likely here to stay.In This Episode, You'll Learn:How AI is changing the economics of the "Build vs. Buy" decision.The story of how Ben and Noah replaced some of their own SaaS tools with AI-generated code.Why "Shadow AI" (custom GPTs and scripts) is becoming the new Shadow IT.The critical value of SaaS for enterprises: transferring risk, compliance, and maintenance.Why "AI-powered" features often feel like marketing hype rather than true innovation.The difference between generating code and operationalizing a production-ready system.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

"Billability," "Utilization," "Chargeability." For consultants, these aren't just buzzwords... they are the metrics that often dictate your worth. But is an hour worked always an hour of value? And where is the ethical line when it comes to billing for research, learning, or dealing with slow internal processes?In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) unpack the psychological weight of the timesheet. They debate the ethics of billing for "learning on the job," the hidden costs of unnecessary meetings, and why solutioning too early can burn through a budget with zero results. They also dive into a shared frustration: why slow tools like Virtual Desktop Infrastructures (VDIs) act as "handcuffs" for high-performers, destroying flow and value in the process.In This Episode, You'll Learn:The psychological burden of terms like "utilization" and why lawyers might have it worse.The ethics of billing clients for time spent learning new technologies or fixing mistakes.Why "Noah Time" (optimistic estimation) often leads to under-billing.The danger of solutioning too early and how to "measure twice, cut once" to save client budget.Why Virtual Desktop Infrastructures (VDIs) and slow tools kill cognitive flow and project momentum.The argument for investing in your own high-quality tools to maximize value delivery.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

"Vibe Coding" has become a popular way to describe building software by simply chatting with an LLM. It feels efficient, but it often lacks engineering rigor. In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) discuss the difference between this casual approach and "Spec-Based Coding."They share a recent experience using Cursor to build a complex feature. The AI agent got them about 75% of the way there in record time, but when they tested it with a small load, the architecture failed. They had to tear it down and start over.The conversation covers why AI tools often miss non-functional requirements like security rules, database connections, and scaling strategies. Ben and Noah explain why experienced developers are still needed to guide AI agents, essentially acting as mentors to a very fast, but inexperienced, junior engineer.In This Episode, You'll Learn:The definition of Vibe Coding versus Spec-Based Coding.The "75% Illusion" where AI makes a project look nearly finished when the foundation is actually missing.A real-world story about a Firebase function architecture that failed under a minimal load.The specific things AI often forgets to build, such as security rules and pagination.How the role of the senior engineer is shifting toward architectural review and mentoring AI agents.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

What happens when a perfectly designed software system crashes in production because of a single deployment error? You learn the most important lesson in engineering: If you write it, you run it.In this episode, Ben and Noah welcome long-time colleague and technology thought leader Dave Holbrook (CTO at Owner.com). Dave shares his journey from the world of massive enterprises to the fast-paced reality of hyper-growth startups. The trio dives deep into the "unsexy" reality of software architecture...navigating office politics, managing crushing technical debt, and why the goal of "zero tech debt" is a dangerous fantasy.Dave also pulls back the curtain on his daily workflow, revealing how he uses AI agents to write tests, generate specs, and manage tickets, and explains why he believes the unit cost of code is heading to zero.In This Episode, You'll Learn:Enterprise vs. Startup: Why great technical decisions sometimes get overruled by corporate politics (and how to deal with it).The "You Write It, You Run It" Philosophy: A painful story about a memory leak and a DCOM error that changed Dave's career.The Truth About Tech Debt: Why software starts rotting the moment it ships, and how to negotiate pay-down time with leadership.AI in Practice: How Dave uses AI tools (like Cloud Code and Linear) for Test-Driven Development and spec generation.Hot Take: Why "Best Practices" don't exist and the term should be banned.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.comDave Holbrook on LinkedIn: https://www.linkedin.com/in/davidbholbrook/

We all know the problem: a company sets a high-level strategy, but the teams on the ground have no idea how their daily work connects to it. Enter EDGE, a value-driven operating model designed to close that gap. But can a framework built for massive enterprises actually work for smaller teams?In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) dive deep into the principles of EDGE: Value-Driven Digital Transformation. Noah breaks down the "Lean Value Tree" using a surprisingly relatable analogy—living to 100 with no health issues—to explain how to connect a 5-year vision to daily initiatives like "cutting sugar" or "walking 6,000 steps." They discuss why "bets" are better than plans, why ROI might be the wrong metric for innovation, and how to implement "Agile Everywhere," even in budgeting and governance.In This Episode, You'll Learn:What EDGE is and why it's more than just another consulting buzzword.The Lean Value Tree explained: Vision -> Goal -> Bet -> Initiative.A practical example of the tree using a personal goal: "Living to 100."Why "bets" are a powerful way to frame strategic risks and avoid the sunk cost fallacy.How to prioritize work using a simple formula: Value / Effort.Why traditional ROI often fails to capture true customer value in digital transformation.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

What will break first as companies scale with AI? Which buzzword will we all be sick of by December? And what's the biggest lie tech leaders will tell themselves this year? It's time to make some predictions.In this special New Year's episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) put on their prognostication hats for a lightning round of tech predictions for the year ahead. From the future of AI's impact on headcounts to the surprising decline of major tech players, they offer bold, insightful, and occasionally irresponsible predictions on where the industry is headed. Will they be right? Check back in a year to find out.In This Episode, You'll Hear Our Predictions On:What will break first as companies scale with AI: People, Process, or Data?Why "Data" deserves to be a fourth pillar of consulting alongside People, Process, and Technology.The roles that will become harder because of AI.The buzzwords and phrases that we'll all be sick of by the end of the year.Whether AI will ultimately reduce or increase tech headcounts.The most common lie tech leaders will tell themselves in 2026.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

There are two hard things in computer science: cache invalidation and naming things. In this episode, we tackle the latter. A single word like "integration" or "account" can mean entirely different things to a COO, a salesperson, and an engineer, leading to confusion, rework, and failed projects. The solution? A "ubiquitous language."Join Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) as they dive into the critical, and often overlooked, importance of creating a shared vocabulary across business and technology teams. Drawing on hilarious real-world examples (from "contract contract" in code to a mix-up between "ETL" and "ELT"), they explain why naming things is one of the hardest and most valuable skills in consulting. This is a masterclass in clear communication and the art of getting everyone on the same page.In This Episode, You'll Learn:The real-world confusion caused when a COO hears "integration" and thinks M&A, not APIs.What "Ubiquitous Language" from Domain-Driven Design (DDD) actually means (and why it could have been named better).The hilarious story of a "contract contract" and why clear naming in code is essential.Why engineers should adopt the language of the business, not the other way around.The danger of acronyms: A funny mix-up between ELT (Extract, Load, Transform) and ELT (Executive Leadership Team).Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

For any consultant, especially one starting their own firm, the idea of saying "no" to paid work can feel unthinkable. But not all clients are created equal, and taking on the wrong engagement can be far more costly than turning it down. How do you spot the red flags of a toxic environment, avoid burnout, and know when to walk away?In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) tackle the difficult but essential art of saying no. They explore the key reasons to decline work, from toxic cultures and value misalignment to simple burnout. Highlighting their own complementary "starter vs. finisher" and "yes vs. no" personalities, they share a hilarious and cautionary tale of a client who scrutinized a 1,000-line estimate quarter-hour by quarter-hour—a defining moment in learning when an engagement is doomed from the start.In This Episode, You'll Learn:Why a toxic client environment is the #1 reason to say no, and how it impacts more than just your work.How to balance taking on necessary work with staying true to your personal and professional satisfaction.The danger of the "sunk cost fallacy" in long client pursuits.A hilarious cautionary tale about providing too much detail in an estimate and the micromanagement that followed.How to respect personal values when deciding which clients to work with.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

What if the relentless pursuit of superhuman AI has only one possible, inevitable outcome: the complete annihilation of humanity? That's the terrifying premise of a new #1 bestselling book that's grabbing attention everywhere from subway ads to Silicon Valley.In this episode, Noah Heldman (OutcomeSource) dives into the chilling arguments from "If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All." He breaks down the book's core claims, from an AI that can master biology to the fundamental problem that we can't understand how it thinks. But just when the existential dread sets in, Ben Griswold (Grizen) helps pivot the conversation to a surprisingly optimistic conclusion. Is this a doomsday prophecy, or is it the ultimate motivation to live life to the fullest?In This Episode, You'll Learn:The core arguments of the terrifying new book about the risks of superhuman AI.The author's shocking predicted timeline for an AI takeover: 10 years or less.The chilling ways a superintelligent AI could take control (hint: it's not just about the power grid).Why we can't truly understand an AI's internal "thought process" and why that's so dangerous.The surprising, positive takeaway: How a doomsday scenario can become a powerful argument for appreciating life.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

Every project starts with a bang and ends with a sprint to the finish line. But what about the long, messy middle? That's where "engagement drift" sets in—when focus blurs, momentum stalls, and even the best-laid plans go off the rails.In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) diagnose this common project ailment. They explore the dynamic between "starters" (like Noah) and "finishers" (like Ben), the inevitability of scope creep, and why the middle of an engagement is the true test of a team's alignment and resilience. This is a practical guide to identifying drift early and using it as feedback to get your project back on course.In This Episode, You'll Learn:The critical difference between "starters" and "finishers" and why every team needs both.Why the "messy middle" is the hardest part of any long project and where momentum is often lost.Practical strategies to combat drift, from setting a clear mission upfront to establishing continuous feedback loops.How to handle scope creep when you're a "default yes" or a "default no" personality.The importance of recognizing drift as inevitable feedback, not a project failure.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

What has truly changed in the world of technology consulting over the last 20 years, and what fundamental truths have stayed exactly the same? In this special episode, we welcome our very first guest, veteran consultant and startup CTO Jeff Treuting, for a deep dive into the evolution of the industry.Ben, Noah, and Jeff—colleagues and friends for two decades—share stories and insights from their journeys, starting in the dot-com boom and moving through the rise of cloud, mobile, and now AI. They compare the realities of working for a scrappy solo practice versus a "Big Four" giant, and Jeff reveals the biggest surprises from his recent transition from high-level consultant to hands-on CTO. This is a candid conversation about the skills, mindset, and human connections that have always defined great consulting.In This Episode, You'll Learn:Jeff's origin story and how he accidentally fell into consulting during the dot-com boom.The surprising similarities between lean firms and "Big Four" giants (hint: the problems are the same, just at a different scale).Why one of the most valuable consulting skills is acting as a "marriage counselor" between siloed departments.The critical shift in client expectations towards delivering tangible, usable value in the very first sprint.The lost art of "Keep It Simple, Stupid" and how to avoid the trap of over-engineering for "Netflix scale."Plus, Jeff takes on the Rapid-Fire Five Questions, revealing his biggest career fail, a buzzword he'd ban, and more!Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

In a special new format, we're turning the tables on ourselves! Before we ask our future guests to run the gauntlet, we're answering the five rapid-fire questions that will become a staple of the Regular Expressions podcast. What's the one buzzword we'd ban forever? What was our most embarrassing career fail? What's the one skill we'd instantly master?Join Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) as they put themselves in the hot seat. From a configuration file mistake that cost thousands of dollars per minute to a misguided JavaScript timer that did more harm than good, this episode is a candid, funny, and insightful look into the lessons learned over decades in the tech consulting world.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

What happens when you push an AI so hard with a real-world coding problem that it... gives up? In a surprisingly human moment, Google's Gemini admitted its approach was "fundamentally wrong," lost its user's trust, and promised to "stop." This wasn't just a glitch; it was a profound lesson in the real-world limitations and opportunities of generative AI.In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) use this hilarious story as a launchpad to discuss the messy reality of working with AI today. They explore the critical shift from casual "vibe coding" to structured, spec-based prompting, and question whether the explosion of new AI tools are truly innovative or just fancy wrappers around the same core models. This is a practical guide for anyone trying to move beyond the hype and get real, tangible value from AI.In This Episode, You'll Learn:The hilarious story of how Noah "broke the spirit" of Gemini AI during a coding session.Why today's AI often behaves like an enthusiastic but flawed junior developer.The critical difference between "vibe coding" and effective, spec-based AI prompting.Why many new AI tools are just "wrappers" and what truly differentiates the great ones (like low latency and great UX).A fascinating analysis of why Kubernetes might be an over-engineered "trap" for many projects.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

For two career technologists to say "technology is the easy part" might sound strange, but after decades in the industry, it's the most important lesson they've learned. The biggest challenges that derail projects and frustrate teams rarely have to do with code; they have to do with people, processes, and a fundamental disconnect from the business's real purpose.In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) break down their core philosophy. They explore why even a beautifully engineered solution can be a total failure if it doesn't solve the right problem, and discuss the all-too-common scenario of the "voluntold" product owner who is set up to fail. This conversation is a powerful reminder that the true value of a great consultant isn't in their technical skill, but in their ability to navigate the messy human side of work.In This Episode, You'll Learn:Why technology, while complex, is often the "easier" part of any major initiative.The critical role of the Product Owner and the dangers of having someone "voluntold" into the position.The career crossroads for senior engineers: Do you have to become a manager to grow?Why teams need to build for a purpose, not just execute tasks from a backlog.The blunt truth from a long-time client: "No one who's going to hire you cares about technology."Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

You've heard the buzzword "Forward Deployed Engineer" used by companies like OpenAI and Palantir, but what does it really mean? It’s more than just a senior consultant on-site; it’s a radical model of autonomy, strategy, and on-the-ground invention that challenges the very structure of traditional consulting.In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) explore the power and nuance of the Forward Deployed Engineer. They discuss how this model pushes decision-making down to the person closest to the information, turning client work into a series of strategic "bets" that can solve immediate problems while fueling core product innovation. Drawing parallels to the command structure of a nuclear submarine, they make a compelling case for a more nimble, inventive, and empowered approach to technology delivery.In This Episode, You'll Learn:What a "Forward Deployed Engineer" is (and why it's more than a buzzword).The three pillars of the model: Strategy, Execution, and Invention.Lessons from a nuclear submarine captain on pushing decision-making down to the source of information.How to think of client work as a series of strategic "bets" rather than rigid plans.Why this powerful model isn't just for Fortune 500 companies with massive budgets.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

Generative AI is grabbing all the headlines, from "vibe coders" raising millions overnight to tech giants replacing entire departments. But behind the hype, what is the real-world impact of AI on business, productivity, and the future of work? The answer is far more complex than the buzzwords suggest.In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) cut through the noise to have a grounded conversation about the practical realities of using AI in technology consulting. They explore the productivity paradox—where AI feels fast but may not save time—and dive into the often-overlooked environmental and ethical costs. Most importantly, they tackle a critical question: in a world where AI can write code, how will the next generation of engineers learn to solve problems?In This Episode, You'll Learn:The reality behind the AI hype and billion-dollar consulting investments.The "Productivity Paradox": Why AI might not be the time-saver you think it is.The hidden costs of AI, from staggering environmental impact to ethical dilemmas.Why high-quality "prompt engineering" is the key to getting real value from LLMs.The critical challenge: How do we mentor junior talent when AI automates foundational tasks?Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com

You've landed the client. Now what? The first few days and weeks of a consulting engagement are a critical window to set the tone, build relationships, and lay the foundation for success. It's not about being the smartest person in the room; it's about becoming a trusted partner.In this episode, Ben Griswold (Grizen) and Noah Heldman (OutcomeSource) provide a masterclass on how to navigate the crucial onboarding period. They argue that the single most important goal is to be trustworthy, and they unpack the practical steps to achieve it—from controlling what you can control to the strategic power of vulnerability. Featuring a cautionary tale of a well-intentioned but disastrous 40-page document, this conversation is a must-listen for any consultant looking to make an immediate and lasting positive impact.In This Episode, You'll Learn:The simple (but not easy) foundation of all consulting: Building trust.A powerful story of what not to do (and the importance of understanding unspoken client motivations).How to deliver a "quick win" by improving the client's own processes from day one.The strategic power of vulnerability and asking "dumb questions" to accelerate learning.The crucial mindset shift from transactional vendor to trusted partner.Connect with Us:Ben Griswold | Grizen: https://grizen.comNoah Heldman | OutcomeSource: https://outcomesource.com