The Agentic Organization
Building AI Highways to Bypass Human Traffic Jams
Humans are the bottleneck. Agentic organizations separate AI workflows from human processes, like ring roads that bypass city centers. Dual-lane processes should prevent intellectual traffic jams.
Driving through Peru last month taught me more about organizational design than most MBA programs ever could.
Picture this: you’re cruising along on a highway, minding your own business, when suddenly the road dumps you straight into the heart of some random city you’ve never heard of. No warning. No bypass. No escape route. One minute you’re doing highway speeds; the next you’re crawling past vendors hawking empanadas and ceviches while three-wheeled taxis cut you off and camouflaged speed bumps strategically hidden every fifty meters try to wreck your rental car.
Half an hour of pure chaos later, you emerge on the other side of town, the rental car miraculously intact, wondering why anyone thought it was brilliant urban planning to funnel every piece of through-traffic directly past the town square. Sometimes, my partner and I would just give up, park the car, and grab lunch while contemplating the obvious: there had to be a better way to let fast-moving traffic skip a tour of the local mercado.
Turns out, this traffic challenge perfectly illustrates what’s broken in many organizations today.
The Theory of Constraints, dreamed up by Dr. Eliyahu M. Goldratt, cuts through management BS with surgical precision. Find the single biggest bottleneck in your system. Fix it. Everything else is theater. The approach doesn’t care about your org chart, your processes, or your feelings; it cares about throughput. Goldratt’s five-step process is beautifully ruthless: identify the constraint, try to get the most out of it, subordinate everything else to it, then elevate it to another level, and repeat. No fluff, no improvement committees, just relentless focus on what actually matters now.
Apply this to traffic, and the solution becomes rather obvious. When high-speed traffic gets tangled with low-speed traffic, the slow stuff becomes the constraint that drags everything down to its sluggish pace. Solution: build a ring road! Keep the highway traffic moving around the city instead of straight through it. Add proper on-ramps and off-ramps so people can switch lanes safely when they need to. Everyone wins: speedsters keep their velocity, locals get their peace, and nobody loses their chassis over a speed bump.
This same principle shows up everywhere, though most organizations are too busy admiring AI-generated meeting notes and PowerPoint slop. Fast-moving value streams crashing into slow-moving process steps? System-wide slowdown. High-speed trains sharing railroad tracks with freight wagons? Delays for everyone. Broadband internet packets pushing themselves through a landline? Digital Stone Age. The pattern is universal: when you mix different speeds on the same infrastructure, you get the worst of both worlds.
But here’s what many people forget: the slow lane enables the fast lane, not the other way around. Those highways don’t build themselves. They’re constructed, maintained, and funded by the people puttering around in their tuk-tuks. Speed doesn’t equal importance. Strategy—real strategy—almost always happens in the slow lane, not the fast one.
Which brings us to the organizational intelligence revolution that most companies can still only dream of.
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The Non-Agentic Trap
Walk into any “AI-powered” organization today and you’ll probably witness a masterpiece of inefficiency. Employees are prompting ChatGPT, wrestling with Copilot, and sweet-talking Gemini all day long. They share their clever prompts in Slack channels, celebrate their AI wins in all-hands meetings, and generally feel very cutting-edge about their human-machine collaboration.
But look a bit closer. Every AI interaction starts with a human typing something and ends with a human reading something. The AIs never talk to each other. They execute nothing independently. They make no meaningful decisions or kick off workflows without a human standing there, hand on the wheel, ready to intervene. This is humans-in-the-loop territory, where artificial intelligence exists purely as a fancy autocomplete for human workflows.
This is the equivalent of those Peruvian towns with no bypass. All organizational intelligence—human and artificial—gets funneled through the same bottleneck: the human brain. And guess what happens? Everything slows down to human speed. The AI might be capable of processing thousands of documents per second, but it has to wait for Susan from product management to read the summary, think about it over lunch, discuss it in Tuesday’s meeting, and maybe, just maybe, decide what to do about it by Friday.
The constraints here are Susan’s brain, Susan’s calendar, and Susan’s need to feel important by being in every decision loop. The result is organizational traffic jams that would make a Peruvian city center blush.
The Agentic Alternative
Now imagine a different world. Employees orchestrate AI agents that can work autonomously, share results directly with other AI agents, initiate workflows without human approval, and manage entire value streams from start to finish. Humans are still crucial, but they’re watching from the sidelines, monitoring dashboards, setting strategic direction, and intervening only when something needs the slow, deliberate thinking that humans excel at.
This is humans-on-the-loop: artificial intelligence running its own native workflows at AI speed while humans focus on what humans do best. The AIs take the highway; the humans work the town square.
This isn’t science fiction. Some companies are building these systems right now. They’re creating separate infrastructure for AI-driven value streams, letting machines talk to machines while humans focus on the strategic work that actually benefits from human judgment, creativity, and wisdom.
The transformation isn’t just about speed—though speed matters when you’re trying to spot risks and seize opportunities faster than your competitors. It’s about using each type of intelligence where it adds the most value. AI excels at processing massive amounts of data, recognizing patterns, and executing well-defined tasks at superhuman velocities. Humans excel at setting context, making judgments with incomplete information, and thinking strategically about wicked problems.
Building the Bypass
Agentic organizations don’t happen by accident. They require deliberate architectural choices that most companies are afraid to make. You need to build a separate infrastructure for AI workflows, with clear protocols for when and how humans intervene. You need to design handoff points where human intelligence and artificial intelligence can collaborate without creating bottlenecks. And you need to be ruthless about identifying which processes truly need human involvement versus which ones are being slowed down by human ego.
Most importantly, we need to accept that artificial intelligence doing its work without constant human supervision is our next human challenge. The goal isn’t to keep humans in control of everything; it’s to let humans control what matters while letting machines handle everything else.
We need to accept that artificial intelligence doing its work without constant human supervision is our next human challenge.
This requires a fundamental shift in how we think about work. Instead of asking, “How can AI help humans be more productive?” the question becomes, “What work should humans do, and what work should go to the machines?” The first question keeps you trapped in the non-agentic model, where AI is just a fancy tool in human-first workflows. The second question opens up the possibility of true organizational intelligence that operates at multiple speeds simultaneously.
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Different Lanes, Different Speeds
I’m betting my career on agentic organizations. As I described earlier in “Scrum Is Done,” we need to operate at multiple speeds without everything grinding to a halt. Strategic thinking happens slowly, deliberately, with humans wrestling with ambiguous problems and making judgment calls that shape the organization’s direction. Operational execution happens fast, with AI agents processing transactions, updating systems, generating reports, and handling routine decisions without human intervention.
The magic happens when these different intelligences enable rather than obstruct each other. Humans set the strategic direction and design the guardrails. AI agents execute within those parameters at AI speed. When edge cases arise or strategic pivots are needed, the system should know how to escalate to human judgment. When humans make strategic decisions, those decisions get translated into AI-executable workflows that run autonomously.
Humans set the strategic direction and design the guardrails. AI agents execute within those parameters at AI speed.
You know you’ve built an agentic organization when the machines can safely ignore the humans for any kind of work where humans are more than happy to be ignored. Let people focus on what they do best: thinking slowly, creatively, and strategically about hard problems. Let the AI focus on what it does best: processing information and executing defined workflows at superhuman speed.
That’s the real promise of the agentic organization: not replacing human intelligence, but giving it room to operate where it adds the most value while everything else runs in the fast lane. Different intelligences, different speeds, different infrastructure—each optimized for what it does best.
I look forward to a future without needless traffic jams around the town square. No more bottlenecks disguised as collaboration. Just clear lanes for different types of work, with proper on-ramps and off-ramps for when you need to switch between them.
And next time, I hope Peru will have a few more ring roads.
Jurgen
Scrum Is Done. Finished. History.
For twenty years, Scrum was the Shinkansen (新幹線) of work management. The fastest kid on the block. Now, it’s the family minivan blocking the left lane while AI agents are flashing their headlights. Once, Scrum was the fast lane—the bullet train of modern work, the agile manifesto made flesh. But times change, work accelerates, and the machines aren’t wa…
AGI—Complex, Not Complicated
True Agentic AI? When? I haven’t seen a single AI benchmark that steps into this messy, wicked, unpredictable arena.
I wouldn't claim AI is unbiased. But probably less so than humans.
One angle this brought back to mind from your earlier piece on the Stochastic Parrot vs the Sophistic Monkey is the role of cognitive bias in all these traffic jams. People carry bias into every decision, every meeting, and every approval cycle. AI does not. That alone creates a natural speed gap long before we even look at calendars or processes.
In your Peru metaphor, humans are not only the slower vehicles. They are also the ones who occasionally take the wrong exit, stop for no reason, or drift into the oncoming lane because of bias, instinct, or habit. AI does none of that. It follows the route with perfect consistency.
That difference makes the case for true agentic lanes even stronger. The speed issue is real, but the predictability advantage is just as important.