Smarter by Design Newsletter
How Leading AEC Firms Manage Information, Share Knowledge, and Build Learning Organizations
Recent Issues
I spoke at AEC Innovate last month about Synthesis Knowledge Agents and walked through several examples of what AEC firms in our beta program are beginning to build.
In the presentation I showed a contract and NDA review agent that could evaluate an agreement against a firm’s own standards and accumulated judgment. I showed a fee proposal agent grounded in how a firm approaches pricing and scope. I talked about proposal assistants that could draw not only on project information and boilerplate, but also on a firm’s own guidance for writing strong project descriptions and approach statements.
The agents were doing different jobs, but they had something important in common: they were all powered by their firms capturing some version of “this is what good looks like” from their experts.
After my talk, the CEO of one of our prospective clients came up to me and said he loved what I shared. The agents I showed seemed powerful and genuinely useful, and he could immediately imagine a whole collection of them his firm might want to build.
But there was one part he could not quite get past. Was he supposed to sit down alone and write all of those best practices from scratch? Were the people on his leadership team supposed to somehow find the time to document everything they knew before the firm could build useful knowledge agents?
The whole thing suddenly felt daunting and I saw his shoulders had slumped.
Seeing his reaction, I shared the behind-the-scenes story of how MBH Architects created their NDA review agent.
Before their CFO retired, Ryan McNulty, President at MBH Architects, made sure to get him in a room for a brain dump. Over the course of a few conversations, Ryan and his team walked through how he reviewed contracts, specifically NDAs. Which clauses were always unacceptable. Which ones the firm would negotiate, and under what circumstances. What unusual language tended to appear, and how the firm had learned to respond. Decades of contract judgment, compressed over time into instinct, were suddenly made visible.
They distilled those conversations into a set of NDA best practices. Those best practices now power a contract review agent. Any manager at MBH can upload a new client NDA, and the agent can go clause by clause, identify potential risks, explain its reasoning, and suggest a response based on the firm’s own accumulated judgment.
The CFO had not sat down alone with a blank page and written the definitive guide to reviewing NDAs. Ryan and his team had partnered with him to draw that knowledge out through conversation, examples, questions, and iteration. AI could help accelerate that process even further.
The CEO’s reaction was immediate.
“Oh my gosh. I didn’t even think I could use AI that way. It's so obvious now that you are saying it.”
Between the people on his marketing and operations teams, the experts throughout the firm, and AI, he could imagine capturing a great deal of this knowledge much faster than he had assumed.
Building useful knowledge agents no longer felt out of reach. What had changed wasn’t the technology, it was his mental model for knowledge capture.
He had been imagining an expert alone with a blank page.
But there’s a better way.
Before their CFO retired, Ryan McNulty, President at MBH Architects, made sure to get him in a room for a brain dump.
Over the course of a few conversations, Ryan and his team walked him through how he reviews contracts, specifically NDAs. Which clauses were always unacceptable. Which ones the firm would negotiate, and under what circumstances. What language a client should be expected to provide. What unusual clauses tend to appear, and how the firm has learned to respond. Decades of contract judgment, compressed over time into instinct, were suddenly made visible.
They distilled those conversations into a set of NDA best practices. Those best practices now power a contract review agent. Any manager at MBH can upload a new client NDA, and the agent goes clause by clause, marking each one high, medium, or low risk, explaining the rating, and suggesting a response. Expertise that once lived in one person’s head is now available to everyone in the firm, consistently, at any hour.
The technology mattered, of course. But it was not the only thing that made this possible.
What made the agent valuable was the judgment behind it. Someone had to understand that NDA review was important enough to improve. Someone had to know which expertise mattered. Someone had to help extract that expertise from the head of an experienced leader and turn it into guidance an agent could actually use. Someone had to see that this was more than an interesting AI experiment. It was a chance to take a recurring business process and make the firm’s best thinking more available, consistent, and scalable.
As we have been working with AEC firms in the Synthesis Knowledge Agent private beta, I have found myself coming back to a simple observation: the firms getting the most traction are having their firm leaders build agents themselves.
That distinction matters because high-impact knowledge agents are not created from AI enthusiasm alone. They are created when people who run AEC firms begin to personally and viscerally understand how agents can improve work that matters.
Over the past year, I've had countless conversations about AI agents across the AEC industry — with clients, partners, peers, and practitioners at every level.
I keep noticing we're using the same word to describe wildly different systems.
Sometimes "agent" means an informational chatbot that can answer questions using firm knowledge. Sometimes it means a workflow assistant that helps generate proposals. Sometimes it means a system executing repeatable business processes with minimal human input. And sometimes it means fully autonomous systems coordinating multiple specialized agents across an entire operation.
That ambiguity matters. The way a firm should approach an informational agent is fundamentally different from how it would approach a fully autonomous system operating across multiple workflows. The technical requirements are different. The governance requirements are different. The trust, risk, and organizational implications are different. And yet most conversations about AI agents flatten all of this into a single category.
Autonomous vehicle companies solved a similar problem. Rather than debating whether a car was "autonomous" or not, they introduced a spectrum of capability levels — a shared language for discussing current capabilities, where they were headed, and what human oversight was still required along the way.
That framing inspired me. So I started sketching something similar for AEC: not a single definition of "agent," but a spectrum of increasingly capable systems — each with different strengths, risks, requirements, and use cases.
I've been calling it the Agent Capability Spectrum.
All AEC firms are learning organizations.
They have to be. From the moment a new firm takes on its first project, it begins a process of continuous learning. Learning how to deliver work, how to collaborate across disciplines, how to listen to clients, how to navigate permitting authorities, and how to translate ideas into drawings and built form. With each successive project that learning deepens and expands, shaped by new challenges, new contexts, and new people.
As firms grow, so does the scope of what they must learn. They learn how to recruit and onboard talent, how to develop people into capable and confident contributors, how to expand into new markets and take on unfamiliar project types, how to adopt and integrate new technologies, and how to navigate the broader cycles of the industry—periods of rapid growth as well as moments of contraction and uncertainty. Over time, many firms also learn how to transition leadership across generations, preserving what matters while adapting to what’s next.
In this sense, if a firm has endured—if it has grown, evolved, and remained relevant over time—it has done so by learning, continuously, and across every part of the organization.
And yet, while learning is ever-present, it is not always intentionally designed.
In many firms, learning emerges organically from the work itself. It is embedded in projects, carried through conversations, shaped by mentorship, and accumulated through experience. It is often rich and valuable, but also uneven—varying from team to team, from project to project, and from one moment in time to the next. It is deeply human, but not always structured in a way that allows the firm to scale with consistency.
For a long time, this has been sufficient. In fact, it has been the foundation of how the AEC industry has developed expertise for generations.
But the context in which firms operate is changing. The pace of work is accelerating. The complexity of projects is increasing while the timelines and budgets are shrinking. The demands on teams are growing as experienced professionals are stretched across more responsibilities, and we’re asking emerging professionals to take on more advanced tasks earlier in their careers than ever before. At the same time, new technologies, particularly those related to AI, are beginning to reshape how knowledge can be captured, accessed, and applied.
In this environment, the difference between firms is no longer simply what they know. It is how effectively they are able to learn, adapt, and apply that knowledge over time.
Over the past year, working closely with firms adopting Synthesis LMS and AI-powered search, I’ve started to notice a shift. The organizations that seem to be gaining the most traction are not just implementing new tools; they are becoming more intentional about how learning happens within their firms. They are stepping back and beginning to redesign the organization itself—how knowledge is created, how it is shared, how people develop skills, and how all of that connects to the work they do every day.
I’ve come to think of this shift as a movement from what we might call a traditional learning organization to a modern learning organization—one that is not defined by any single program or platform, but by a more deliberate and integrated approach to building and sustaining collective intelligence.
To better understand this change, I created a maturity model—one that reflects how learning capabilities tend to develop over time within AEC firms. This model begins with the foundational ways people learn through experience and interaction, and extends through more structured, scalable, and technology-enabled approaches, culminating in the emerging potential of AI-powered, just-in-time learning in the flow of work.
In the sections that follow, I’ll walk through that progression as a seven-level maturity model for AEC firms. Along the way, we’ll explore what each level looks like in practice, where it creates value, where it begins to show its limits, and how firms move from one stage to the next. We’ll also look at what fundamentally changes as organizations become more intentional in how they learn—and why the ability to learn well may become one of the defining characteristics of the most successful firms in the years ahead.
Here we go.
In the last issue of Smarter by Design, I introduced the Modern Learning Organization Pipeline — a practical, end-to-end model for turning learning opportunities into durable capability inside AEC firms. The nine steps of the pipeline move through identifying and prioritizing learning needs, designing and delivering learning experiences, unlocking just-in-time retrieval, and ultimately to measurement and continuous improvement.
At a strategic level, the logic of the pipeline is straightforward. If firms systematically capture expertise, distribute it intelligently, and reinforce it in the flow of work, they become more capable, more resilient, and less dependent on any single individual.
But models on paper are the easy part.
The road to the Modern Learning Organization runs directly through subject matter experts — through their willingness and ability to share what they know — and through the organization’s ability to help transfer and scale that knowledge.
And this is where things get interesting.
If you ask a senior architect or engineer to document what they know, record a short course, or capture best practices from a recent project, what objection would you expect to hear?
For most people, it’s the same answer. “I don’t have time.” Or, closely related, “I’m too busy.”
Picture an iceberg. The visible portion above the waterline is what gets said out loud. “I don’t have time.” “I’m too busy.”
Those are socially acceptable objections. They are real, and they matter. But they are rarely the whole story.
Beneath the waterline sit quieter forces of the iceberg— unspoken barriers to keeping experts from sharing knowledge which revolve around identity, legitimacy, confidence, cultural norms, maintenance, and trust. Questions about whether sharing knowledge will actually improve the quality of someone’s workday. Questions about whether the effort will have an impact. Questions about whether they are truly the right person to step forward. Questions about whether the system will support them or simply ask them to do more.
If we respond only to the spoken barriers of “I don’t have time” or “I’m too busy” we miss a major opportunity to overcome more deeply-seated emotional barriers to knowledge sharing.
Over the past 25 years working in knowledge management in AEC — and through countless conversations with subject matter experts, knowledge and learning leaders, CEOs, and project teams — I’ve come to see a pattern. The resistance to sharing expertise is rarely about time. It is almost always about something deeper and more emotional.
In this article, I surface seven of those unspoken barriers. More importantly, I explore what leading firms are doing to address them — through culture, partnership, process, and modern learning infrastructure.
I believe learning and development in AEC is going to change more in the next five years than it has in the last twenty-five.
Outside of work, people have grown accustomed to immediate, searchable, personalized access to information. That experience is reshaping what they expect from learning and knowledge inside their firms.
Many AEC professionals now expect knowledge and learning to be accessible exactly when they need it, in the flow of their work, rather than scheduled far in advance. And they would like to be able to find answers to their questions on demand, without having to attend hour-long, day-long, or week-long training delivered in linear formats. That shift is being shaped by generational change, the increased pace of work, and the growing availability of on-demand and AI-enabled tools.
For the first time, AEC firms have a real opportunity to deliver the right knowledge and learning to the right person at the right time. Technology is a major part of that story—including recent advances in AI and video capture, editing, and transcription—but it’s not the whole story. The real shift will come from how firms bring together people, process, technology, and culture to support learning as a core organizational capability.
That kind of change doesn’t happen organically. It happens by design.
I believe the firms that take full advantage of this moment will be the ones that intentionally evolve into what I’ve been calling Modern Learning Organizations.
In simple terms, a Modern Learning Organization does three things:
Builds and maintains collective intelligence
Leverages technology to deliver knowledge in the flow of work
Continuously adapts and thrives in a rapidly changing environment
This issue of Smarter by Design is the first in a multipart series exploring what it means to design a Modern Learning Organization in the AEC industry.
In this issue, I’ll introduce the Modern Learning Organization Pipeline—a practical, end-to-end model for turning learning opportunities into real, durable organizational capability. The pipeline reflects my nearly 25 years of knowledge management work in AEC, insights from the Knowledge Architecture community, and lessons emerging from firms in the Synthesis LMS public beta actively experimenting with new learning approaches.
Some parts of this model reflect practices that have always mattered: thoughtful prioritization, intentional design, and continuous improvement. Other parts reflect what has changed dramatically—especially the ability to unlock just-in-time, dynamically assembled learning that meets people where work actually happens.
My goal with this model isn’t to prescribe a single “right” way forward for all AEC firms. It’s to offer a shared framework you can react to, adapt, and refine as you think about how learning really works inside your firm—and how it could work better.
Here we go.
About Smarter by Design
The AEC industry is at a turning point—not just in technology, but in how firms think about learning, growth, and the role of knowledge in their work.
Published by Knowledge Architecture and written by our Founder and CEO, Christopher Parsons, Smarter by Design explores how forward-thinking firms are building cultures of learning, scaling expertise, and rethinking knowledge management for the modern era.
AI is part of the story, of course. But so are generational shifts, new business models, and a growing recognition that firms can’t just work harder—they need to learn smarter and faster.
To thrive in the decades ahead, AEC firms must become learning organizations: places where knowledge flows, expertise grows, and insights compound over time. That kind of transformation doesn’t happen by accident. It happens by design. Smarter design.
Each month, the newsletter shares stories, patterns, and lessons drawn from real conversations with AEC leaders, knowledge managers, and learning professionals who are quietly (and sometimes boldly) reimagining how their firms manage information, develop talent, and sustain culture.
Some issues zoom in on specific use cases—like improving onboarding, upskilling emerging professionals, or scaling expert knowledge. Others step back to examine broader trends shaping the future of knowledge, learning, and organizational design in AEC.
If you're curious about how firms are evolving into more adaptive, resilient, and knowledge-driven organizations, Smarter by Design is for you.
