Engineering Evolved

The Trio Model: Breaking Down Business-IT Walls for Better Engineering Collaboration

Engineering leaders learn how the Trio model can eliminate the blame game between business and IT teams. Discover practical strategies for cross-functional collaboration that actually work. The Trio Model: Breaking Down Business-IT Walls Key Topics Covered The Business-IT Dysfunction Problem * Why blame games develop between business and IT teams * The 'technical purgatory' of mid-sized companies (200-1000 employees) * Common symptoms: endless backlogs, shadow IT solutions, demoralized engineers Why Traditional Fixes Fail * Hiring more managers: Adds abstraction without context * Adding more engineers: Brooks' Law in action * Better ticketing systems: Makes misalignment visible but doesn't fix it * More meetings: Creates 'status theater' without decisions The Trio Model Explained * Three core roles: Business owner, technical lead, designer/analyst/ops lead * Co-ownership of outcomes, not just task handoffs * Clear decision rights to prevent gridlock * Not a committee: Explicit authority assignment Implementation Strategy * Which problems warrant a trio (high ambiguity, cross-functional dependencies) * Decision rights framework * Shared metrics and accountability * Starting with 1-2 pilot areas Leadership Requirements * Stop bypassing trio processes with 'urgent' requests * Protect trio time and focus * Hold business owners accountable for outcomes * Accept timeline realities Key Quotes * "If every request is urgent, there's no way for IT to prioritize" * "Shared ownership of the outcome doesn't mean you can point at someone else when your part goes wrong" * "The trio owns it can quickly become no one owns it" Action Items * Identify 1-2 high-friction problem areas * Form pilot trios with clear problem definitions * Establish shared success metrics * Review and iterate after one quarter Chapters * 0:00 - The Business-IT Blame Game Problem * 1:56 - Life in Technical Purgatory * 5:29 - Why Traditional Fixes Don't Work * 10:09 - Introducing the Trio Model * 15:51 - Implementation and Decision Rights * 23:42 - Measuring Success with Shared Metrics * 24:50 - Leadership Changes Required * 29:25 - Getting Started: A Practical Approach

Why Your Team Rituals Are Optimized for the Wrong Thing

How many meetings moved your team forward last week? Tom explores why most team rituals fail at building trust and alignment, sharing lessons from NASA JPL and startups on creating ceremonies that actually work. Why Your Team Rituals Are Optimized for the Wrong Thing Key Topics Covered The Missing Middle Challenge * Why mid-sized companies (200-1000 employees) face unique coordination challenges * Too big for startup osmosis, too small for enterprise playbooks * The need for distributed decision-making without dedicated alignment teams Two Contrasting Standup Experiences * NASA JPL: Nightly standups across three time zones that built trust and enabled handoffs * Medical Startup: Transactional daily standups that created artificial harmony * What made the difference: optimization for relationship building vs. status updates The Five Dysfunctions of a Team Framework 1. Absence of Trust - Vulnerability-based trust, not competence trust 2. Fear of Conflict - Artificial harmony vs. productive disagreement 3. Lack of Commitment - What happens when people don't feel heard 4. Avoidance of Accountability - When standards become suggestions 5. Inattention to Results - Individual ego over team success Three Practical Shifts for Better Rituals Shift 1: Surface Vulnerability * Leadership modeling uncertainty first * Structured moments for admitting what you don't know * Moving from posturing to problem exploration Shift 2: Practice Disagreement * Red team rotations in roadmap reviews * Making challenge a role, not a personality trait * Ensuring friction happens constructively in the room Shift 3: Build Shared Context (Not Just Information) * The difference between "here's the roadmap" and "here's the trade-off I struggled with" * Smaller cross-functional context sessions vs. large all-hands presentations * Enabling distributed decision-making through understanding reasoning Key Questions for Diagnosis * How much time was spent on information transfer vs. relationship building? * Did anyone admit uncertainty without it being a problem? * Was there constructive disagreement that led to better outcomes? * Do people understand the reasoning behind decisions, not just the decisions themselves? Resources Mentioned * Patrick Lencioni's "The Five Dysfunctions of a Team" (2002) * Concept of vulnerability-based trust * Red team methodology for productive conflict Next Episode Preview Episode 14: The Product Trio Model - Making it Actually Work in Engineering-Heavy Organizations Chapters * 0:00 - The Meeting Problem: Status Theater vs. Real Progress * 2:20 - The Missing Middle: Mid-Sized Company Challenges * 4:21 - Tale of Two Standups: NASA vs. Startup * 11:15 - The Five Dysfunctions Framework * 16:13 - Three Practical Shifts for Better Rituals * 23:55 - The Compounding Effect of Trust * 28:39 - Diagnostic Questions and Next Steps

Why Kubernetes Is Probably Wrong for Your Mid-Sized Company

Engineering leader Tom Barber challenges the default adoption of Kubernetes, sharing why simpler alternatives often serve mid-sized companies better and how to make pragmatic infrastructure decisions. Episode 12: Why Kubernetes Is Probably Wrong for Your Mid-Sized Company Key Topics Covered The Kubernetes Reality Check * Why most mid-sized companies don't need Kubernetes complexity * The hidden costs: maintenance, YAML management, and developer experience * Real-world example from NASA: when impressive engineering doesn't solve business problems Understanding Kubernetes Context * Origins from Google's Borg system designed for massive scale * Core benefits: fault tolerance, auto-scaling, declarative infrastructure * Why these benefits require significant investment to realize The Real Downsides 1. Complexity: Even cloud vendors are building products to hide Kubernetes 2. YAML Everything: Config management becomes a people and process problem 3. Cost at Scale: Engineering hours, infrastructure, and mental health costs 4. Developer Experience: High barrier to entry and friction in feedback loops 5. Portability Mirage: Cross-cloud deployment still requires deep vendor knowledge When Kubernetes Makes Sense * Genuine scale requirements (dozens/hundreds of services) * Multiple teams with dedicated platform engineering capacity * Complex deployment patterns that serve real business needs Practical Alternatives * VMs with Docker: Boring is good, boring is maintainable * Managed Container Services: ECS/Fargate, Cloud Run, Azure Container Apps * Serverless: Lambda, Cloud Functions for event-driven workloads * Simple Deployment Scripts: Often cheaper than cluster management Decision Framework: Do You Actually Need Kubernetes? 1. What specific problem are you solving? 2. Do you have dedicated team capacity? 3. What's your actual scale (services, teams, traffic)? 4. How frequently do you deploy? 5. Have you exhausted simpler options? Resources Mentioned * Free Download: "You Actually Need Kubernetes" Checklist (available in show notes) * Consulting: Concept Cloud - Pragmatic infrastructure decisions for mid-sized companies * Website: www.conceptcloud.com [http://www.conceptcloud.com] * Contact: tom@conceptcloud.com [tom@conceptcloud.com] Next Episode Preview Episode 13: "Why Your Engineers and Product Managers Still Don't Talk to Each Other (And How to Actually Fix It)" Engineering Evolved is the podcast for engineering leaders at mid-sized companies who are tired of getting advice that only works for startups or enterprises. Chapters * 0:00 - Introduction: The Kubernetes Controversy * 3:00 - A Personal Story: Getting It Wrong at NASA * 4:58 - Understanding Kubernetes: Context and Core Benefits * 7:07 - The Real Downsides: Complexity, Cost, and Developer Experience * 10:49 - When Kubernetes Actually Makes Sense * 13:39 - Practical Alternatives to Kubernetes * 15:51 - Decision Framework: Do You Actually Need It? * 18:36 - Wrap-up and Next Episode Preview

You Don't Need Kubernetes: Right-Sizing Platform Engineering for Mid-Size Companies

In this episode of Engineering Evolved, Tom Barber discusses the pitfalls of over-engineering platform infrastructure, particularly for mid-sized companies. He shares insights from his experience at NASA's Jet Propulsion Laboratory, emphasizing the importance of right-sizing infrastructure to match team needs and capacity. The episode covers the build versus buy framework, the challenges of internal tooling, and the significance of documentation and automation in maintaining efficient operations.

How to Sunset a Legacy System Without Destroying Team Morale

Summary In this conversation, Tom Barber discusses the challenges organizations face when dealing with legacy systems and the importance of recognizing the human element in system migration. He emphasizes that migration is not just a technical project but a transition that impacts people's identities and roles within the organization. Takeaways * Think about your current environment for a second. * Do you have systems running that are older than some of your engineers? * Maybe it's that monolithic application written in a language nobody wants to touch. * Maybe it's hardware that needs special handling. * Or maybe it's just tribal knowledge locked in the heads of three people. * Not if, but when, that time comes. * You can treat it like a purely technical project. * It's a transition that affects people's identities. * A transition that affects people's identities, their expertise. * Their sense of value to the organization. * (00:00) - Intro * (00:32) - Title * (01:16) - The Challenge of Sunsetting Legacy Systems * (06:11) - Principals for Successful Legacy Migration * (12:04) - Creating a Culture of Evolution