In this bonus episode, Hannah Garrett shares practical advice for students, career changers, and professionals hoping to enter the fast-growing data center industry. She explains why emerging leaders should embrace AI, learn by experimenting, and focus on simplifying complex systems. Hannah and Orion also discuss why speed may replace complexity as a competitive advantage, how AI could reshape traditional corporate structures, and why this period of disruption presents an extraordinary opportunity for the next generation of leaders.

About half of all US data centers scheduled to open this year are delayed or canceled. Hannah Garrett isn't surprised. She's been watching tech and construction try to figure each other out for a decade, and says the real problem isn't energy, equipment, or even AI. It's that nobody fixed their operational structure before the boom hit.

Hannah Garrett has 10 years across both sides of data center delivery - five on the GC side at Hensel Phelps and Clark, and five more on the owner side at Meta, Aligned, Microsoft, and Oracle. She's a recognized voice in the industry, known for her LinkedIn post "You Can't Automate Chaos", and for saying out loud what most people in the room are thinking but won't say. https://www.linkedin.com/in/hannahegarrett/

What You'll Learn

1. The Symptom-Root Cause Gap

Delays, burnout, and cost overruns in data center delivery are symptoms - not the disease. Hannah makes the case that most operational pain points trace directly back to systems and structures that were never built for the scale being demanded of them. Until leadership treats the root cause, adding technology only makes the chaos faster.

2. The Amplification Principle

AI doesn't fix broken systems. It accelerates them. Hannah's framework: understand your operations end-to-end, map out the full complexity across 40-plus stakeholders, establish structure and only then let AI scale what's already working. Applied too early, it amplifies every gap you haven't dealt with yet.

3. The Simplicity Paradox

The smartest people in complex industries tend to build the most complex tools, but complexity degrades data quality, because people stop updating systems they find painful to use. Hannah argues that simpler, centralized platforms (she points to Asana and Monday as examples) produce far better information than the highly engineered tools leadership tends to prefer.

4. The Change Management Translation Problem

"Change order" is a career-defining term on a job site. In software, it barely registers. Hannah breaks down the language and cultural gap between tech and construction teams and why the absence of a shared vocabulary means billion-dollar decisions are routinely being made in Slack channels, with no one raising the downstream impacts until it's too late.

Timestamps

[00:00:00] Introduction: Hannah's 10 years spanning GC and owner sides of data centers

[00:02:00] What the boom felt like: "a meteor overnight" — and why the industry wasn't ready

[00:04:00] What five years on the GC side taught her about change management

[00:06:00] Tech vs. Construction: two different organisms forced to work together

[00:09:00] Why projects are delayed: the leadership-to-delivery disconnect

[00:15:00] Ford's automation lesson: why structure has to come before AI

[00:20:00] PM as "the domino for AI": challenging Jack Dorsey's hierarchy quote

[00:22:00] "Chaos is a report card": what happens when you scale without systems

[00:29:00] The burned-out PM problem and the doctor/EHR parallel

[00:33:00] Dashboard overload: why qualitative metrics often beat KPI tracking

[00:37:00] How Hannah takes over a portfolio: her framework for finding the gaps

[00:43:00] The case for a central source of truth (and why no one has built it yet)

[00:49:00] Final challenge to leadership: bold plans must look nothing like the last 10 years

Episode Resources

• Connect with Hannah Garrett on LinkedIn https://www.linkedin.com/in/hannahegarrett/
• Referenced: Ford's quality automation and rehiring case
• Referenced: Jack Dorsey — "Hierarchy is an obsolete information routing protocol"

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Bruno Caldas didn't take a traditional path into the world of billion-dollar projects - he started building computers at 14, earned a mechatronics engineering degree, and landed on a $20 billion iron ore project in the jungles of Guinea within two years of graduating. In this bonus segment, Bruno shares what he'd tell his younger self: get comfortable with discomfort, learn the tools that nobody else wants to learn, and never underestimate the power of a clean dataset. Whether you're a student considering project controls or an early-career professional wondering how to stand out, Bruno's story is proof that the combination of technical curiosity and hands-on hustle is still the fastest path to the rooms where the biggest decisions get made.

Bruno Caldas has built dashboards on a laptop in the African jungle, trained 300 people on SAP, and is now building AI agent teams for one of the world's largest mining companies. The throughline across 18 years in the industry is always the same: the data foundation comes first.

Bruno Caldas is a project controls and business intelligence professional at Rio Tinto, sitting at the intersection of capital projects, finance, systems, and AI. With 16 years in mining across Guinea, Brazil, and Canada - and roles spanning site engineering, FP&A, and PMO leadership at Vale and Rio Tinto - he has built the reporting infrastructure behind some of the industry's most complex billion-dollar portfolios. He also teaches business intelligence in Northwestern University's MBA program.

Bruno Caldas is a project controls and business intelligence professional at Rio Tinto with 18 years of experience, 16 in mining. Having built PMOs for iron ore, copper, and nickel portfolios at Vale and Rio Tinto - across Africa, Brazil, and Canada - he now sits at the frontier of AI-driven portfolio management. He teaches BI in Northwestern University's MBA program.

https://www.linkedin.com/in/brunodcaldas/

1. Start with your most mature data source - and earn every layer from there

Every PMO Bruno built began the same way: find the data that's already clean (usually SAP), build dashboards people actually want to see, and use that success to earn sponsors for the next layer. He didn't start with governance frameworks or org design. He started with what worked and let the wins spread organically. His rule: prove value with what's mature, then go to the piece that needs fixing. Bottom-up, always - even when top-down funding is available.

2. Two reports, not one: the 3-page executive version changes everything

On every major project Bruno worked, there were two deliverables: a 200-page full report and a 3-page visual executive summary. Leadership wanted fast, clear, and visual. That discipline - ruthlessly separating what the full team needs from what the boardroom needs - built trust with executives faster than any comprehensive report would have. The 3-page version was how Bruno got sponsors. The 200-page version was how the project stayed on track.

3. Mining operations are five years ahead of corporate on AI - and the math explains why

In iron ore, cutting unit cost by just $1 generates $400 million in EBITDA. That return on technology is why operations have been running AI teams, autonomous trucks, and sensor-driven predictive maintenance for years. The S11D project Bruno worked on is entirely truckless - conveyor belts run directly from the pit to the processing plant, no diesel, no CO2. Corporate PMOs are a year or two behind. The gap is real, and closing it is where the opportunity sits.

4. AI agents are only as useful as the data beneath them

Bruno is building a team of AI agents - one for risk, one for HSE, one for community relations - on a medallion architecture: raw data piped into a processed layer for agents, then a gold layer for Power BI dashboards. The Microsoft CEO said it plainly: your AI strategy and your data strategy are the same strategy. Bruno's been living that for a decade. His corporate training program teaches everyone up to the markdown level. The agent-building stays with the people who want to go further.

• 00:00 — Introduction
• 02:00 — Building computers at 14 to mechatronics engineering: Bruno's tech-first origin story
• 08:00 — The Simandou Project, Guinea: $20B iron ore, a railroad through 50% of a country
• 15:00 — S11D, North Brazil: drone photography, walking 1,500km of railroad, performance at scale
• 19:00 — FP&A at Vale: seeing billion-dollar projects through the finance lens
• 26:00 — Power BI, SAP, and the CFO meeting that moved Bruno to Canada
• 35:00 — Building a PMO from scratch: start with what's mature, earn sponsors, scale up
• 44:00 — Operations vs. corporate: why mining AI is years ahead - and the truckless mine
• 55:00 — AI agents, medallion architecture, and the one-stop-shop PMO control tower
• 1:00:00 — Teaching AI inside the company: level 1 chatbots to level 8 VS Code
• 1:10:00 — What PMO teams look like in five years - and why data is the only moat

• Primavera P6 / MS Project (scheduling tools)
• Power BI - Microsoft (launched 2017)
• SAP (PS, FM, MM modules)
• S11D - Vale truckless iron ore mine, North Brazil
• Simandou Project - Guinea, West Africa
• Medallion architecture (data engineering framework)
• Northwestern University MBA program (Bruno teaches BI)

Omer Iqbal returns for a bonus episode focused on career advice for project controls professionals - from how to actually get noticed in an organization, to why doing everything by the book might be holding you back. He shares his go-to books, the two habits he says can transform any career, and why staying curious is more than just good advice. If you're early in your career or feeling stuck, this one's for you.

Most project teams are exceptionally good at delivering a project the wrong way. Omer Iqbal has spent 20 years learning to fix that - from the portfolio level.

Omer Iqbal is Senior Portfolio Manager in the Investment PMO at Sydney Water, where he oversees a $30 billion capital program serving 6 million people. His career has run from site engineering on a $20M oil and gas job to board service, MBA, and portfolio leadership across some of Australia's most complex infrastructure. In this episode, he shares the frameworks he developed to help executives actually understand what's happening inside a billion-dollar portfolio - and make better decisions because of it.

Guest Bio

Omer Iqbal is Senior Portfolio Manager in the Investment PMO at Sydney Water, managing a $30 billion capital portfolio serving 6 million people. With 20 years across oil and gas, mining, defense, and major infrastructure - and former president of PMI Sydney chapter - Omer bridges project delivery and board-level investment strategy.

https://www.linkedin.com/in/moigoheer/

What You'll Learn

1. The shift from "are we delivering right" to "are we delivering the right thing"

At the project level, success means managing scope, schedule, and budget. At the portfolio level, those metrics don't tell you whether the project should exist at all. Omer describes the moment this clicked - simultaneously managing a complex COVID-era project at Transport for NSW, earning an MBA, and serving on a board. The canvas of thinking, as he puts it, completely expanded. Zooming out that far is disorienting at first. Eventually, it's the only view that makes sense.

2. "The most expensive meeting is where everybody agrees"

When everyone in a room nods along, no one is doing their job. Omer's counter is psychological safety - which he calls 100% a leadership responsibility, non-negotiable. His personal rule with his team: "Your failure is mine, 100%. If we succeed, that success is your title, 100%." That one principle removes the fear that keeps people quiet in rooms where silence is expensive.

3. The difference between a dashboard and executive intelligence: What, So What, Now What

Dashboards tell you what is happening. Executive intelligence goes further: So what does this mean for our regulatory exposure, our asset condition, our risk appetite? And then: Now what action is required - and from whom? Omer's team built custom portfolio indicators (including a portfolio cost index that flags hidden cost blowouts before they surface) specifically to make what's invisible visible - and to frame it in a way that triggers decisions, not just awareness.

4. You cannot outsource accountability - including to AI

AI can run Monte Carlo simulations in minutes. It can draft schedules, surface trends, and produce beautifully formatted reports. What it cannot do is be held accountable when a decision goes wrong. Omer's governance rule for his team: whenever you use AI to produce an artifact, save the prompt too. The prompt is the scope of work for the AI - and tracing it back is how you keep humans in the loop where they belong.

Episode Timestamps

00:00 — Introduction

02:00 — From a $20M oil and gas job to billion-dollar infrastructure

05:00 — The portfolio mindset shift: board service, MBA, and COVID

08:00 — Full circle: what it actually means to be the project sponsor

13:00 — Sydney Water: 1.5 billion liters/day, $30B in the pipeline, 80 investment drivers

19:00 — Why earned value management breaks down at portfolio scale

25:00 — What executives should actually be asking before signing a business case

32:00 — "The most expensive meeting is where everybody agrees" — building psychological safety

40:00 — Portfolio Cost Index: the single number that surfaces hidden cost blowouts

49:00 — Dashboard vs. executive intelligence: What, So What, Now What

1:04:00 — Governance and AI: why you cannot outsource accountability

Resources Mentioned

• Atomic Habits — James Clear
• Rapid Transformation — Catriona Wallace
• Toby Ord — AI risk research (referenced in Rapid Transformation)
• PMI Sydney Chapter — pmi.org.au
• NEC Suite (contract framework used at Sydney Water)
• Tools referenced: SAP, Primavera P6, Maximo, Coupler

In this bonus segment, Iwona Wilson shares her advice for the next generation of project leaders. She makes the case for developing critical thinking above all else, explains how AI is reshaping the skills students need to stay relevant, and offers practical guidance on where to find the right experiences early in your career. Iwona also walks through her book, her decision gate training program, and where to connect with her online.