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You know the phrase. Everyone knows the phrase. The meeting wraps early, and someone delivers the line with total sincerity: "Great, I'll give you all 20 minutes back." It's a little silly if you think about it; nobody actually owned those 20 minutes, but somehow it never stops feeling good to hear. It means the meeting is over. You got your calendar back. Now imagine hearing that feeling not once a week, but for half your meetings because you weren't even in them. Corporate culture coined the phrase to celebrate a happy accident. Employees are now building the tools to make it the default. The Rise of the Meeting Proxy A growing number of employees are training AI agents to sit in on meetings on their behalf. Not "sit in" in some passive, transcribe-and-forget way. They actually attend, listen for specific triggers, and report back only when something needs a human. Think of it less like a recording and more like a very attentive intern who never gets bored, never checks their phone, and knows exactly what you care about. You tell the agent: Flag it if budget numbers come up. Flag it if my name is mentioned in a way that suggests a follow-up is headed my way. Flag it if the timeline shifts. Flag it if someone disagrees with the plan we already signed off on. Otherwise, let it ride. The agent watches for those conditions like a smoke detector, silent 99% of the time, loud the moment it matters. Why This Isn't Just "Skipping Meetings" There's an obvious skeptical read here: this is just employees ducking out of work. But that misses what's actually happening. Skipping a meeting with no coverage means information gaps, missed decisions, and someone pinging you later, pointing out that you weren’t there. An AI agent attending on your behalf is different. It's not absence, it's delegated presence. The meeting still gets a stakeholder in the room. You just outsource the "sit and wait for the thirty seconds that matter" part, which, if we're honest, is most meetings. The real unlock isn't the time saved during the meeting. It's what happens after: instead of scrolling back through 45 minutes of transcript, wondering what you missed, you get a short, concise summary: what triggered it, what it means, and what's being asked of you. Actionable next steps, not a wall of notes. What "Giving Time Back" Actually Looks Like Now The corporate ritual of the early meeting-end has always been about reclaiming control of your day. AI meeting agents extend that same instinct further upstream — before the meeting even starts. The old version: A meeting ends 10 minutes early. Someone gives you 10 minutes back. The new version: An agent sits through a 30-minute status update so you don't have to, flags the one moment your project got mentioned, and gives you back the entire 30 minutes, with a two-line summary of what you actually need to act on. It's the same dopamine hit, just scaled up. Instead of getting some time back at the margins, employees are engineering their calendars to get most of their time back by design. How Employees Are Actually Setting This Up The pattern that's emerging looks less like "AI replaces me in meetings" and more like a light configuration layer employees build once and reuse constantly: Define the trigger list. Budget mentions, deadline changes, direct questions to you, competitor names, specific client accounts — whatever actually requires your judgment. Set the threshold for escalation. Some employees want a nudge for anything even loosely related to their work; others only want to be pulled in for decisions, not discussion. Decide the report format. A short summary with a "Needs Your Input" section tends to work better than a full transcript. The goal is a decision-ready brief, not homework. Review async. Instead of live attention, you get a five-minute read afterward — with the option to jump into the recording if a flagged moment needs more context. The employees who get the most value out of this aren't trying to disappear from every meeting. They're being deliberate about which meetings genuinely need their live judgment, and which ones just need a well-briefed report. The Trade-Off Worth Naming This isn't free efficiency. Agents can miss nuances like tone, hesitation, the moment someone chooses their words carefully because they're not sure how the room will react. Triggers have to be tuned, sometimes repeatedly, before they catch the right things without becoming noisy. And there's a cultural question teams are still working out: how do you feel about presenting to a room where some of the "attendees" are agents relaying to humans who'll read about it later? The organizations doing this well tend to treat it as a spectrum rather than a switch. High-stakes strategy sessions still get a human in the room. Recurring status updates, broad-audience syncs, and FYI-style meetings are where agents earn their keep fastest. The Bottom Line "I'll give you time back" used to be a nice thing someone said when a meeting ran short. Now it's becoming something employees say to themselves. A deliberate design choice, built meeting by meeting, trigger by trigger. The time isn't just being given back. It's being engineered back, on purpose, one well-configured AI agent at a time.

Work is changing faster than ever. Technology evolves overnight. Clients need to shift in real time. Teams adapt constantly. For a firm that has spent more than two decades helping organizations turn bold ideas into tangible outcomes — from our humble Pacific Northwest beginnings with software companies, to fintech to health systems to agencies across the Public Sector — this is not new. Through all of it, one thing stays steady for RedCloud. We believe in building teams with intention, clarity, and long-term thinking. This is not a glossy hiring announcement. It is a look at how RedCloud thinks about talent in a world where stability is earned, not assumed. It is a philosophy shaped by real client engagements, real challenges, and real people — across our offices in Bellevue, London, and Singapore, serving as hubs to our global team. The Reality of Modern Work The truth is simple. Work today is unpredictable. A Retail client reworks its supply chain strategy mid-engagement. A Utilities client shifts its modernization roadmap after a regulatory change. A Public Sector agency's priorities move with a new budget cycle. Technology advances whether we are ready or not — Copilot, Azure AI Studio, and whatever platform comes after them. That means the people who thrive at RedCloud are the ones who can navigate change with confidence and curiosity, across nine practice areas and client industries as different as Enterprise Tech and Utilities. We are not looking for perfection. We are looking for people who understand the real world of consulting work. People who bring skill, maturity, and adaptability to the table. People who can grow with us as Data & AI, Strategy & Transformation, and Physical Security continue to evolve. What We Look For in Talent Here is what matters most to our RedCloud team. Not the buzzwords. The real qualities that make our teams strong. People who stay current with technology. Modern work requires modern skills. We look for individuals who keep up with new tools, platforms, and workflows — whether that's Azure AI Studio, Copilot, Power Platform, or our own ChangeFlow platform. People who understand cloud environments across AWS, Azure, and Google Cloud, and the AI-assisted processes that keep our Data & AI and Technical Solutions teams moving. Staying current is not optional anymore. It is part of the job. People who are agile in how they work. Agile is not a certification. It is a mindset. It is the ability to move quickly, adjust without friction, and deliver value even when the plan changes — whether that means standing up a Power BI dashboard for a Finance client or replanning a Delivery Excellence engagement for a Healthcare system mid-stream. We look for people who can iterate, collaborate, and stay steady when things shift. People who know their craft deeply. Skill depth matters. We want people who understand their discipline at a professional level across our nine practice areas: Data & AI, Delivery Excellence, Marketing & Sales, Physical Security, Privacy, Security, Strategy & Transformation, Technical Solutions, and Business Transformation Services. Whether it's strategy, engineering, security, or delivery, expertise is attractive. Curiosity is essential. Growth is expected. People who communicate clearly. Clear communication is one of the most underrated skills in the workplace — especially when a project spans a Bellevue-based delivery team, a London-based client stakeholder, and a Singapore engagement lead working three time zones apart. We look for people who can explain their thinking, break down complexity, and collaborate without confusion. Structured thinking helps teams move faster and avoid unnecessary friction. People who work well with humans. Collaboration is not optional. We want people who make work easier for others — people who listen, who share knowledge in our monthly lunch-and-learns, and who understand that great teams are built on trust, not ego. It's the same people-centric approach we bring to every client engagement. People who understand how work actually gets done. Operational maturity matters. We want people who understand process, delivery, and the realities of modern consulting work — people who know how to navigate ambiguity across sectors as different as Real Estate and Public Sector, and who can take a project from idea to execution using the platforms our clients rely on, from ERP systems and Power Automate to Salesforce and Dynamics 365. Responsible Hiring in a Volatile Market The industry has experienced real shifts. We have felt those shifts too. When client demand changes across Consumer, Enterprise Tech, or Retail, our teams change with it. These moments reinforce why responsible hiring matters to us. We want to grow in ways that protect our people and support long-term stability, whether that growth happens in Bellevue, London, or Singapore. Responsible hiring means being thoughtful about timing, capacity, and the skills that will matter as our Data & AI and Security practices continue to expand. It means choosing sustainability over speed. It means building teams that can thrive in any environment, not just the easy ones — and it means bringing the same integrity we put into every client engagement to how we treat our own people. Investing in People Beyond Headcount Even as hiring ebbs and flows, our commitment to talent does not. We invest in: Skill development, through mentorship and monthly lunch-and-learns Strong leadership practices built on trust and transparency Modern delivery models across our nine practice areas Cross-team collaboration that spans Bellevue, London, and Singapore Building a great team is not only about adding new people. It is about supporting the people who are already here — and about how we show up outside client work, too. It is about creating an environment where growth is possible, even during periods of change. Looking Ahead The future of work will continue to evolve. So will we. Our recruitment philosophy is simple. Hire thoughtfully. Support consistently. Build teams that can thrive in any environment — from our roots in the Seattle tech corridor to our teams in Europe and Asia. We are preparing for the next decade, not just the next project. And whether you're drawn to Data & AI, Security, Strategy & Transformation, or one of our other practice areas, we are looking for people who want to grow with us.

Bryan Lim leads RedCloud’s APAC delivery operations with a steady mix of technical expertise and people‑first leadership, guiding datacentre projects across the region with his team of Security Project Engineers. In this 10 Minutes With interview, Bryan opens up about the mindset that keeps him effective in a fast‑moving environment, the habits that keep him grounded, and the experiences that shaped who he is today. It’s a quick look into the person behind the role — with the rest best discovered in his own words. Describe your role and what you do in a nutshell. I am the Area Delivery Manager for the APAC region, overseeing project delivery for our client’s datacentres. Alongside me is a team of professional Security Project Engineers who work hard to accomplish our mission. What do you consider the most important skill for someone in your role and why? In my opinion, this role requires strong fundamentals in technical knowledge as well as solid interpersonal skills. Communication is the key to ensuring mission success. When in doubt, always dare to ask — you will be given the answers you need. What are you most proud of in your career so far? I’m proud to be part of the RedCloud team and to be working for our client. Imagine a few years down the road, seeing the results of the seeds we’re planting today. How do you maintain a healthy work-life balance in your role? I make sure to go for an evening run or play a game of pickleball whenever I’ve had a long day at work. The endorphins — the “happy hormones” — help clear my mind and allow me to focus better on what’s ahead. What's a piece of obsolete technology you still have a soft spot for? Gameboy Advance! Oh man, the first color portable handheld device from Nintendo. It brings back so many memories. Now there’s a Gameboy Advance emulator you can download on any mobile device, which really shows how technology has evolved from past to present. What’s one thing people don’t know about you that they’d be surprised to discover? When I was much younger, I was the “young and dangerous” type. But as the years went by, I became more settled and learned to be more patient. I like this quote by Mark Twain: “Twenty years from now you will be more disappointed by the things that you didn't do than by the ones you did do. So throw off the bowlines. Sail away from the safe harbor. Catch the trade winds in your sails. Explore. Dream. Discover.” What are you passionate about or enjoy outside of work? I love my family. As a father of two boys, I enjoy spending quality time with them and watching them grow up. As both a father and a friend, I aim to be their role model, leading by example throughout their journey. Recently, I’ve become fascinated by HYROX and have been training hard for it.

RedCloud has been recognized as the Management Consulting Business of the Year (United States) at the Global 100 – 2026 awards, and we couldn’t be more proud of what this moment represents. It’s a celebration of the values we’ve carried since our early days in the Pacific Northwest and the trust clients place in us as they navigate modernization, security, and emerging technologies. As our global presence grows, we’re excited to continue strengthening our people‑first consulting model and delivering the practical guidance leaders rely on in fast‑moving environments. This award reflects the momentum behind RedCloud’s expansion across business and technology transformation, physical security, and data and AI enablement. We’re building a consulting model rooted in long‑term partnerships, measurable outcomes, and a belief that doing the right thing is the strongest foundation for growth.Read the full GPMG article.

Garrett Garcia leads Security System Design and Delivery across the Americas, guiding a team of TPMs who keep data center construction projects moving smoothly. He’s known for cutting through ambiguity, aligning teams, and keeping complex security work on track across dozens of sites. With experience in 15 countries and more than 300 data centers, he brings a practical, real‑world lens to every project. Outside of work, Garrett stays grounded through family life, road trips, karaoke nights, and a long‑running passion for RF and wireless security. He’s equal parts technical, curious, and down‑to‑earth. Get to know him better in his full 10‑minute feature. Describe your role and what you do in a nutshell. I am the North and South America Regional Lead for the Security System Design and Delivery team. In a nutshell, I lead the day-to-day operational work of a team of Security System Design and Delivery TPMs who manage active data center construction projects across the Americas. Our work focuses on data center security systems, including access control, CCTV, and perimeter security detection. My role is to help keep complex projects moving by aligning teams, removing blockers, managing priorities, and ensuring security system delivery remains coordinated across sites, vendors, and partner teams. What do you consider the most important skill for someone in your role, and why? The most important skill is the ability to turn ambiguity into execution. Data center construction and security systems delivery involve many moving parts: technical requirements, construction schedules, site conditions, vendors, partner teams, and regional differences. There is rarely a perfect amount of information, but the work still has to move forward. For me, the key is aligning people around the details, making decisions with the best information available, and keeping programs moving despite uncertainty. I try to stay grounded by sticking close to day-to-day details, because the facts behind how things get done are often covered in nuance. At the same time, “trust but verify” is important in this role. You have to build trust with people, but you also need enough discipline and follow-through to ensure the work is actually moving as everyone expects. What are you most proud of in your career so far? I am most proud of the scale of my data center security work and the perspective it has given me. Since moving into data center security in 2018, I have had the opportunity to work in 15 countries and visit more than 300 data centers. That kind of field experience changes how you think about security. You learn quickly that good design has to work in the real world, not just on paper. Every site has its own constraints, priorities, construction realities, and operational needs. I am proud to have built a career around helping teams deliver security systems in those complex environments, at a scale where consistency, adaptability, and follow-through really matter. How do you maintain a healthy work-life balance in your role? For me, work-life balance starts with being intentional about where my time and attention go. In a role with many meetings, shifting priorities, and a large team to manage, it’s easy for the day to become completely reactive. I try to stay focused on what actually needs my involvement, where I can help unblock the team, and where a better process can prevent the same problems from repeating. Outside of work, my family keeps me grounded. I grew up the oldest of 10 kids, so I had lots of practice with chaos, competing priorities, and people asking me where things were before I was even old enough to have a job. Now I’ve got three young kids of my own who make sure and remind me to take time and focus on life outside of work. What is a piece of obsolete technology you still have a soft spot for? I have a soft spot for vinyl records because they are true physical media. There is something that makes music seem more soulful when it’s played from a needle running through grooves of wax. Today, music is convenient, but I think you experience listening to an old record more intentionally. It takes a few minutes to set it up correctly and enjoy it, like using a French press to make coffee vs. pressing a button on a Keurig. What is one thing people do not know about you that they would be surprised to discover? People might be surprised to learn that I have a passionate interest in radio frequency technology and wireless security. That interest started a little over 20 years ago when I worked for Verizon installing fiber internet service. I would often run into interference from multiple wireless networks in the same area, so I started scanning for neighboring networks to make sure I was setting up wireless service on the cleanest available Wi-Fi channel. That curiosity eventually grew into a broader interest in RF as an attack surface, including Wi-Fi, Bluetooth, LR-WPANs, drone detection…I’ve gotten to use lots of cool spectrum analyzers! I was able to apply those interests early in my career, building and scaling a global Wireless Intrusion Detection & Response program across hundreds of data centers worldwide. A fun byproduct of that work was that I got to attend the DEFCON30 hacker convention, and the Wireless CTF team I competed with won the competition! What are you passionate about or enjoy outside of work? Outside of work, when I’m not just spending time with my family, I love singing karaoke in packed bars or doing pub trivia. In the summer, I really enjoy road trips with my kids because I’ve flown so much for work. Now, even stepping on a flight to Disneyland makes me feel like I’m clocking in, and I think taking the extra time to travel offers a great opportunity to create lasting memories for my family.

As organizations accelerate AI adoption, executive pressure to move faster while cutting costs is creating an unintended consequence: a growing pinch in the middle of the organization. This pressure is often described as a productivity issue, but that framing misses the point. What looks like slop is not laziness. It is the predictable outcome of asking high performers to do more with less in an environment where AI fundamentally changes how work is produced. This article clarifies what that slop really is, why it creates real organizational risk, and what leaders need to do next. The Productivity Paradox For most of modern work, our minds work faster than our hands. AI removes that constraint. Individuals can now generate strategies, papers, applications, and even systems almost instantly. At the individual level, the problem is easy to recognize. A long document produced by AI is not fully owned by the person who requested it, and its quality or accuracy cannot be taken for granted. At the organizational level, the same dynamic applies, but the consequences are much larger. When AI tools are turned on or piloted without the usual rigor around tool selection, business justification, usage clarity, or operational capacity, organizations begin producing work faster than they can validate, govern, or sustain. This is where slop appears. Not because people care less, but because production speed has outpaced organizational readiness. From Slop to Risk Unchecked AI adoption introduces compounding risk. Forward-looking organizations may already have, or soon will, thousands of AI agents operating simultaneously. Users can now generate applications for themselves, leading to rapid growth in loosely governed tools. At the same time, high performers who have succeeded under constraint assume they can do so again, even though the nature of the constraint has fundamentally changed. Without clear governance and some form of AI resource management (tokens), these dynamics create organizational slop at scale. Work exists, but it cannot be confidently trusted, maintained, or explained. Over time, this will erode credibility rather than create an advantage. It also introduces a longer‑term financial risk: token consumption becomes a black box, and future costs can spike without warning. The Leadership Constraint The hardest challenge for leaders is not technical. It is behavioral. In an environment that feels increasingly fast, the instinct is to move faster still. Run Faster! is all our brains hear. Often, the right response is the opposite. Slowing down does not mean resisting AI. It means reapplying discipline. That includes making conscious, informed decisions, establishing clear ownership and governance, integrating AI into real workflows, and ensuring the capacity to maintain, iterate, and scale what is built. These practices create reliable returns and protect organizational credibility, something AI alone cannot provide. A Warning Signal Leaders Should Not Ignore The tension between operational capacity and intellectual capacity is now a leading indicator of organizational risk. If individuals feel this mismatch in their daily work, it is almost certainly present at the enterprise level as well. When conversations about AI risk, current use, and future use are not coordinated and structured, organizations are effectively outsourcing judgment to systems they do not yet fully understand or control. AI does not fail organizations. Unexamined speed does. The path forward is full of intentional pauses that allow leaders to assess, decide, and build scalable capability. If your organization has not yet had a structured conversation about AI risk, governance, and long-term use, the signal is clear. Start that conversation now. This is how credibility and durable value are built, and how you protect the most important asset of your organization: critical thinking and the ability to generate genuine ideas. Catch up on the first two parts of the AI learning series.

AI‑assisted development unlocks extraordinary speed — but speed without discipline creates risk. The organizations that win in this new era aren’t the ones who adopt AI the fastest. They’re the ones who adopt it responsibly. This part of the series focuses on the realities: where AI falls short, what still requires human judgment, and what we’ve learned from building real solutions with clients. Where AI-Assisted Development Falls Short (For Now) Honest take from the trenches: AI is extraordinary at writing code and unreliable at almost everything around the code. Watch for: Scale. AI handles a function brilliantly, and a 200-file feature competently. It still struggles to reason about distributed systems, performance under load, and architectural decisions whose consequences play out months later. Infrastructure. Provisioning, networking, identity, data residency, the unsexy plumbing that makes software actually work in an enterprise, remains heavily human-led. Security. Generated code can introduce subtle vulnerabilities, SQL injection, XSS, leaked secrets, and compromised dependencies. AI is also a powerful tool for finding security issues, but unsupervised generation without a security review is a liability waiting to happen. Test quality. AI can write a lot of tests quickly. It’s much harder to get tests that meaningfully exercise edge cases, fail loudly when something real breaks, and don’t just pad coverage metrics. Support and operations. When something breaks at 2 a.m., the person paged needs to understand the system. Code they didn’t write and don’t understand is a runbook problem waiting to happen. Throwaway vs. production. Maybe the single most important distinction. A vibe-coded prototype is brilliant for validating an idea and dangerous if it slips into production unchecked. Knowing which is which is a discipline, not an instinct. The pattern is clear: AI compresses the building phase. The phases on either side, readiness and operations, are still mostly human work, and skipping them is how AI projects go sideways. What We’ve Built With AI-Assisted Development We don’t just talk about this, we live it. A few examples from our own bench: Coding Change Management Platform. A full change-request platform application, data model, analytics, and workflows built using AI coding agents alongside Power Platform Maker. The result: a scalable, user-friendly system delivered with significantly less developer time. This is agentic engineering in practice. Data Engineering Query Automation. Monthly and quarterly dataflow queries used to take weeks to update in response to revised metrics. We built an AI agent that interprets business rules and automatically updates queries. Development time dropped from weeks to hours, with fewer errors and faster adaptation when requirements shift. RedCloud Project Management Agent. An autonomous agent that emails consultants for status updates, interprets the responses, and updates the project management system on its own. Status collection went from hours to minutes, and project visibility went up not down. Self-Service Governance Agent. Governance, security, compliance, and privacy policies were scattered across teams, sites, and documents. We built an AI agent that consolidates the answers in one place. Adoption hit more than 50% of the organization, and the volume of governance questions flooding email and Teams dropped sharply. The throughline: AI didn’t replace the build; it changed the economics of building. The companies that thrive in this new era won’t be the ones who simply “add AI.” They’ll be the ones who redesign how they build — combining AI acceleration with human judgment, governance, and operational rigor. 2026 is the year organizations experiment. 2027 is the year the gap becomes obvious.

Sean Dettloff brings a builder’s mindset and a calm command of complexity to RedCloud’s growing Physical Security Practice. As the leader shaping this new capability, he’s focused on standing up an embedded team that supports a Fortune 500‑scale data center program—from early‑stage design to on‑the‑ground delivery of physical security systems. His work sits at the intersection of construction, compliance, and client partnership, ensuring every project meets rigorous standards while moving at hyperscale speed. In this edition of 10 Minutes With, Sean shares what energizes him about the role, how he approaches balance in a fast‑moving environment, and the experiences that shaped the way he leads. Describe your role and what you do in a nutshell. I’ve joined RedCloud to lead and support the development of our physical security practice area. At the moment, I’m focusing on building our embedded physical security design-and-delivery team that supports client data centers. We are in the early days of recruiting and developing a security practitioner team to support physical security design and the delivery of physical security hardware and systems in the data center environment. Much of our work supports new data center construction projects, but we are also embedded in other efforts, including retrofits and special projects. We are the spider in the web who helps manage on-time, in-scope security project execution while also ensuring projects comply with client expectations and standards. What do you enjoy most or find especially interesting about your current project/role? What’s not to like about supporting a globally relevant, Fortune 10 client?! The scope and scale of the work are awe-inspiring, the problem set is professionally challenging, and best of all, doing it with a team of stakeholders and vendors that are best in class at what they do. I’d like to think the work we are doing is important and meaningful in enabling the future of AI and future tech advancements, and we get to do it in a great environment with great people who help hold us accountable for excellence. How do you maintain a healthy work-life balance in your role? I’m new enough in the role that I’m still working towards work-life balance at the moment. If I look back on past experiences, I’ve found the most success with triaging priorities between what must happen now that only I can do, identifying where I can deputize others to help to carry the water, and also remembering that not everything can/needs to be accomplished right now. Also important to me is protecting time for both family and personal activities, like exercise. I find that I’m a lot more at ease working outside of core work hours as long as I’ve also engaged in core family activities and got my workout in. Tell us about something interesting you've learned recently. I recently read that scientists estimate there are significantly more trees on Earth than stars in the sky. Apparently, calculations are for over 3 trillion trees on Earth, compared to roughly “only” 300 billion stars in our galaxy. Besides struggling to comprehend any of these numbers, I am fascinated with the idea that there could be 10x as many trees on Earth as there are stars in the sky! If you could suggest a book for the entire team to read, what would it be and why? I think specifically for this audience, I’d suggest “Extreme Ownership” by Jocko Willink and Leif Babin. While the book is set against the backdrop of US Navy SEAL team operations, the core message that an effective leader leans into the problem and “owns everything” is very relevant to the multi-disciplinary client/vendor team environments we work in. It is too easy to blame missing a project milestone or deliverable on another dependency that didn’t meet its deadline. The book emphasizes that the best leaders don’t just take responsibility for their tasks or projects; they take an interest in and an ownership stake in everything that impacts their environment and their ability to succeed in the overall mission. I’d argue that the willingness to think outside your scope at core dependencies, and to anticipate and solve potential problems before they have an impact, brings tremendous value to our work and gets us invited back to the table as the problem solvers we want to be seen as. What's a piece of obsolete technology you still have a soft spot for? Not sure if this counts, but in a world where I walk into most meetings with 2 laptops and a smartphone, I still default to handwriting notes and tracking deliverables in my notebook. Additionally, I’m guilty of having multiple sticky notes on my laptop, helping me keep tabs on various action items or “great ideas” to follow up on at any given time. What's one thing people don't know about you that they would be surprised to discover? I have a great interest in wilderness adventure, including extended backpack treks, motorcycle road trips, and overlanding expeditions. As examples, I’ve traveled the AlCan highway and backcountry roads from Seattle to Alaska and the Arctic Ocean twice over the past several years. The first time was a solo motorcycle adventure from Seattle to Seward, AK. The second time was an overland expedition with my son from Seattle to Tuktoyaktuk, Northwest Territories, where we drove as far as we could in North America and dipped our toes in the Arctic Ocean. This was a 5000-mile road trip, over half of which was over dirt roads. What are you passionate about or enjoy outside of work? I am an active member of the King County Sheriff’s Search and Rescue Association, a 100% volunteer organization dedicated to locating and assisting individuals who are lost, injured, or in distress in wilderness, urban, and disaster environments. I participate in both the 4x4 unit and the Regional Specialty Vehicle Unit (RSVU), which includes ATV and SxS use in missions. It's my outlet to give back to the community while also getting me outdoors in the PNW with a fantastic group of dedicated, like-minded individuals.

Software development isn’t just evolving — the entire way organizations build solutions is being rewritten in real time. A year ago, “AI in development” meant faster autocomplete. Today, business managers can turn an idea into a working prototype before lunch, providing a clear blueprint for engineering to then fold into the final production code. For leaders, the shift isn’t about code. It’s about capability, speed, and who gets to build. Understanding this new landscape is now a strategic advantage. The Three Modes of AI-Assisted Development Vibe coding: software development by intuition and natural language. Describe what you want, the AI writes the code, and iterate by feel. Pro code: professional engineers using AI as a force multiplier inside coding software: completion, review, test generation, refactoring. Agentic engineering: AI doesn’t just suggest, it acts. Agents read the repo, plan changes, run tests, and open pull requests; humans manage and review. Why It Matters Beyond the Engineering Org This isn’t just an IT story, and the most underrated impact isn’t on engineers at all. It’s on everyone next to engineering. Take the Product Manager role. The PM job used to be write a spec, debate it, hand it to engineering, wait. The new PM job looks more like prompt an AI agent, get a working prototype in an hour, put it in front of a customer, refine, and then loop in engineering for the production build. The PM is no longer writing requirements; they’re orchestrating AI agents and validating with real artifacts. The implications ripple outward: The build/buy/wait calculus has changed. Custom internal tools that used to take a quarter and a six-figure budget can now ship in a week. That changes what’s worth building. Software fluency is becoming a core competency. Not “learn to code” but “learn to direct code.” The people who can clearly describe a problem and iterate with an AI will outpace those who can’t. Backlogs are getting unstuck. Every company has a list of “we should automate that someday.” Someday is now. The talent equation is shifting. Smaller teams are shipping more. Senior engineers are getting more leverage. PMs, analysts, designers, and ops folks are stepping into building roles that didn’t exist for them before. From “Wait” to “Create”: The New Workflow The traditional cycle — Idea → Plan → Design → Build → Test → Deploy is being replaced by something much tighter: Idea & Prompt. Brainstorm with the AI. Use it as a thinking partner, not just a builder. Vibe-Code a Prototype. Stand up a working version in hours using tools like Cursor, Replit, Google AI Studio, or Claude Code. Validate by Experience. Let stakeholders click through it rather than read about it. Refine & Deploy. Iterate with AI; harden the parts that need to live in production. The strategic shift is subtle but profound: alignment now happens around working artifacts, not documents. A clickable prototype kills more bad ideas and proves more good ones than any 12-page requirement document ever did. The Tooling Landscape A non-exhaustive snapshot of what’s worth knowing: GitHub Copilot — the default in coding app assistant for most professional developers. Strong at code completion, in-line chat, and increasingly at multi-file edits. Claude Code — Anthropic’s terminal-native agent that can read, edit, and execute across an entire codebase. Strong fit for agentic workflows and complex refactors. Cursor, Windsurf, Replit Agent — AI-native editors blurring the line between “vibe coding” and professional development. Google AI Studio, Gemini Code Assist, v0, Lovable, Bolt — fast prototyping environments aimed at non-engineers and PMs who want to skip the in-coding app entirely. Microsoft AI Studio / Azure AI Foundry — the enterprise platform for building, evaluating, and deploying custom AI agents and applications, with the governance and identity controls enterprise IT actually requires. The right answer is rarely one tool. It’s a stack, and it's changing every week. The New Skills That Actually Matter For everyone now in the building seat, not just engineers, a few capabilities are quickly becoming non-negotiable: Prompt craft. Precise, context-rich instruction is the new technical writing. Systems thinking. AI writes the code. Humans still need to understand data flow, system boundaries, and integration points; otherwise, you get fast spaghetti instead of slow spaghetti. Setting constraints, not just features. Telling the AI what not to do, what file structure to follow, and what architecture to honor matters as much as describing the feature itself. Knowing when not to use AI. Some problems still need human creativity, taste, or domain judgment. The most effective practitioners can tell the difference. The shift is bigger than faster coding. It’s a new operating model for how ideas become software — and who gets to participate. But opportunity is only half the story. The other half is the discipline required to build safely, securely, and sustainably in this new world. Part 2 of this series digs into the realities: where AI accelerates, where it breaks, and what leaders need to get right.

AI has reached an inflection point. The excitement hasn’t disappeared, but the novelty has. Leaders are no longer rewarded for experimenting; they’re expected to show outcomes. And as it shifts from “shiny new thing” to standard part of the workflow, we’re reminded of an age-old truth: technology alone won’t move your organization forward. What matters now is whether your AI investments are anchored to purpose, values, and the real work your teams are responsible for. That’s where change discipline becomes the differentiator. AI Is a Tool. Purpose Is the Point. Change principle: Investments must advance mission, values, and goals, or they will be rejected or ignored. AI has moved rapidly from shiny to standard, and that shift is healthy. Once the novelty fades, we can treat AI the way we treat every other transformative tool. Commercialized planes, electricity, and the internet changed what was possible, but none of them was a strategy in itself. The real question isn’t “Do we have AI?” It’s “What does this unlock for our mission, values, and goals?” Values Are Not a Poster. They Are a Design Requirement. Change principle: Change succeeds when it aligns with what the organization values and how the work must be done. This is where many efforts drift. Leaders approve tools, teams start experimenting, and the organization hopes value will appear. But innovation only sticks when it attaches to the real expectations of the work. If your team is creative, solutions must protect creative integrity while accelerating the process. If your team safeguards physical security at data centers, innovation must increase trust and visibility—not weaken them. If your team leads digital transformation, AI should enhance engagement, speed innovation, and limit disruption. Different missions require different boundaries, measures, and behaviors. AI must serve the work, not the other way around. Discipline Is the Differentiator When AI Is No Longer Shiny. Change principle: Change is the catalyst that turns capability into outcomes through clear decisions and consistent implementation. Most organizations can buy the tools. Far fewer can convert them into a reliable way of working. That conversion is change discipline. Change discipline looks like: Leaders making intent explicit Clear decisions about where work will change and where it will not Ethical boundaries that protect trust Reinforcement until new behaviors become normal Data and systems coherent enough to support the new ways of working Tools don’t create outcomes. Discipline does. What Leaders Must Make Explicit. Change principle: Clarity creates momentum by giving people permission to act inside defined guardrails. Start with three statements people can repeat: What investment is meant to unlock What values must it protect What “good” looks like in day‑to‑day work Then back those statements with visible decisions: Which workflows change first? Which roles get trained and reinforced? What measures prove progress against the mission? AI will keep improving. Your advantage won’t come from chasing the next model. It will come from disciplined change that consistently turns investment into outcomes that matter. To learn more about how to translate AI intent into new ways of working, contact RedCloud’s Business Transformation Services Practice team.

As a key member of our rapidly growing European team, Lovisa Nyman brings a rare blend of structure, curiosity, and global perspective to her role as Global PMO Lead for RedCloud’s Physical Security practice. Her work sits at the heart of the program’s operational rhythm—turning complex project data into clarity, building processes that actually work, and spotting opportunities for improvement before anyone else sees them. In this conversation, she shares what energizes her about the role, how she balances a truly global schedule, and the unexpected life experiences that shaped her approach to problem-solving. It’s a glimpse into the mindset of someone who quietly keeps an entire program running smoothly while never losing sight of what matters most outside of work. Describe your role and what you do in a nutshell. My work as a Global Project Management Office (PMO) Lead involves reporting on the projects our Physical Security TPMs are working on to ensure we capture all required data throughout the projects and at project close-out, as well as project forecasting for the leads and Technical Program Managers (TPMs) to plan workload. Process improvement is also a big part of the PMO's day-to-day work, ensuring we have clear processes to follow so projects run as smoothly as possible. Data and reports are being created and automated to ensure all data we need is easily accessible and up to date. What do you enjoy most or find especially interesting about your current role? The possibility of seeing a gap, a process not working, or getting a new idea of what can be improved, and being able to create what's needed to make an improvement. The flexibility of figuring out what’s needed after discussions with the team and the leads, and creating something that will support the whole team and program. How do you maintain a healthy work-life balance in your role? Being global makes the workdays look different day to day, depending on meetings and what is currently going on. Therefore, I usually work out during my lunch breaks to clear my head after a morning of working with Asia-Pacific (APAC) and Europe, the Middle East and Africa (EMEA), and get a refresh and some energy for later meetings when North America/South America (NASA) wakes up. What's one thing people don't know about you that they would be surprised to discover? When I studied, I moved to Mexico for one semester to study and learn Spanish. Being from Sweden, this is something that often surprises people. I left my then-boyfriend, now husband, at home for half a year and moved to a country where I did not know the language. It taught me that you can always figure things out, despite how challenging they are. What are you passionate about or enjoy outside of work? I’ve always liked being active and working out to get energy. Lately, as I build a family, it’s also about spending quality time with my husband and daughter and experiencing things through her eyes.