1. Introduction
In networking, OSPF (Open Shortest Path First) is a routing protocol that ensures traffic flows along the shortest and lowest cost path through a network. It does not care about hierarchy, seniority, or intent. It routes based on capability, cost, and reliability.
Modern engineering organisations behave in exactly the same way, whether they realise it or not. Workloads move through teams, people, and processes, naturally finding the path that resolves uncertainty with the least friction. This article explores how OSPF maps directly onto human workload routing inside engineering driven organisations.
2. How Networks Route Work vs How Organisations Route Work
In a network, routers advertise their capabilities and current state. OSPF continuously recalculates the optimal path based on these signals.
In an efficient engineering organisation, teams do the same thing implicitly. Through their behaviour, outcomes, and delivery patterns, teams advertise whether they are high or low cost paths for work. Workloads should not stick to a single team and just wait on resources, due to ownership bias’s. Instead workloads should route themselves toward the teams that require the fewest handoffs, the least clarification, and the lowest coordination overhead.
3. Understanding Cost Beyond Time and Effort
In OSPF, cost is not simply distance. It includes bandwidth, latency, reliability, and congestion.
In software delivery, cost includes change risk, testing overhead, coordination effort, context switching, review latency, and rework probability.
A team that looks fast on paper but requires excessive reviews, repeated testing cycles, and constant external validation is not a low cost path, even if their delivery metrics appear healthy.
4. The Hidden Cost of Micro Changes and the MTU Analogy
In networking, the Maximum Transmission Unit (MTU) defines the largest packet size that can traverse a network path without fragmentation. When packets exceed the MTU, they must be split into smaller fragments. Each fragment carries its own headers, sequencing, and failure risk. If a single fragment is lost, the entire packet must be retransmitted.
Micro changes in software delivery behave exactly like fragmented packets.
Every change, no matter how small, carries a fixed overhead. This includes build time, deployment effort, testing cycles, reviews, coordination, monitoring, and rollback planning. When work is artificially split into very small parcels, the organisation pays this overhead repeatedly, just as a network pays repeated headers and retransmissions for fragmented packets.
Fragmentation feels safer because each unit appears smaller and more controlled. In reality, fragmentation increases total risk. The probability of failure rises with the number of deployments. Testing effort multiplies. Cognitive load increases as engineers must reassemble intent across multiple changes rather than reason about a coherent whole.
Competent teams intuitively manage their effective MTU. They batch related changes when it reduces total risk. They expand the scope just enough to keep work below the fragmentation threshold while still remaining safe to deploy. This allows intent, testing, and validation to stay aligned.
Optimising delivery is therefore not about making changes as small as possible. It is about making them as large as safely possible without fragmentation. Teams that understand this reduce total system cost, improve reliability, and deliver outcomes that are easier to reason about and support over time.
A common misconception in delivery organisations is that smaller changes are always safer.
Every change introduces fixed overhead. Every deployment carries risk. Every test cycle has a non trivial cost. When work is broken into micro parcels, those costs multiply.
Competent teams understand this and naturally batch changes when appropriate. They reduce total system cost by limiting the number of times risk is introduced, rather than optimising for superficial progress metrics.
5. Competent Teams as the Shortest Path
In OSPF, traffic flows toward routers that forward packets efficiently and rarely drop traffic.
In organisations, work flows toward teams that terminate uncertainty quickly and safely. These teams do not just execute instructions. They resolve ambiguity, anticipate downstream impact, and reduce the need for future work.
They attract work not because they ask for it, but because the system optimises around them.
6. A Message to Junior Engineers: How to Become a Highly Desirability Execution Path
If you are early in your career, attracting meaningful and complex work is not about visibility, speed, or saying yes to everything. Work flows toward engineers who consistently reduce effort, risk, and uncertainty for the rest of the system. Becoming that engineer is a deliberate skill.
6.1 Build Trust Through Follow-Through
Nothing increases desirability faster than reliability. Finishing what you start, closing loops, and making outcomes explicit tells the organisation that routing work to you is safe. Partial delivery, vague status, or silent stalls increase perceived cost, even if the technical work is strong.
High-desirability engineers are predictable in the best possible way. People know that when work lands with you, it will progress to a clear outcome.
6.2 Make Ambiguity Smaller
Many workloads are not technically hard; they are poorly defined. Engineers who can take a vague request and turn it into a clear execution plan dramatically lower organisational cost.
This means asking clarifying questions early, documenting assumptions, and explicitly stating what will and will not be delivered. Turning uncertainty into clarity is one of the fastest ways to become a preferred execution path.
6.3 Learn the System, Not Just the Code
Junior engineers often focus narrowly on the component they are assigned. High-growth engineers invest in understanding how data, requests, failures, and deployments move through the entire system.
Knowing where data comes from, who consumes it, how failures propagate, and how changes are rolled back makes you safer to route work to. System understanding compounds faster than any single technical skill.
6.4 Reduce Hand-Offs Proactively
Every hand-off is a routing hop. Engineers who can take work further end-to-end lower total delivery cost.
This does not mean doing everything yourself. It means anticipating what the next team will need, providing clean interfaces, clear documentation, and well-tested changes that reduce downstream effort.
6.5 Surface Trade-Offs, Not Just Solutions
High-value engineers do not present a single answer. They explain options, risks, and costs in simple terms. Even junior engineers can do this.
When you articulate trade-offs clearly, decision makers trust you with more complex work because you reduce the cognitive burden of decision making itself.
6.6 Take Ownership of Quality, Not Just Completion
Finishing a task is not the same as completing a workload. Quality includes operability, observability, testability, and clarity.
Engineers who think about how their change will be supported at three in the morning quickly become trusted paths for critical work. Supportability is a strong desirability signal.
6.7 Invest in Communication as an Engineering Skill
Clear written updates, concise explanations, and honest status reporting are not soft skills. They are routing signals.
Engineers who communicate well reduce the need for meetings, escalation, and oversight. This makes them cheaper to route work to, regardless of seniority.
6.8 Be Curious Beyond Your Boundary
The fastest way to grow is to follow problems across team and system boundaries. Ask why a dependency behaves the way it does. Learn what happens after your code runs.
Curiosity expands your problem-solving surface area and accelerates your transition from task executor to system engineer.
6.9 Optimise for the Organisation, Not the Ticket
The most desirable engineers think beyond the immediate task. They consider whether a change creates future work, reduces it, or merely shifts it elsewhere.
When people see that routing work to you improves the organisation rather than just closing tickets, you naturally become a preferred execution path.
6.10 Desirability Is Earned Through Reduced Friction
Ultimately, workloads flow toward engineers who make life easier for everyone else. By reducing ambiguity, risk, hand-offs, and future cost, even junior engineers can become the shortest path to execution.
In human workload routing, competence, clarity, and intent matter far more than seniority or title.
If you are early in your career, attracting meaningful work is not about appearing busy. It is about reducing friction for everyone around you. Its about having deep enough and broad enough skills to tackle workloads without handoffs. Its about pushing knowledge boundaries, about challenging the status quo and about making yourself an obvious choice to include in conversations through your knowledge and ability to get things done.
7. Going Beyond Requirements
Requirements define minimum constraints, not the full problem space. Engineers who limit themselves to ticking boxes behave like routers that blindly forward packets without understanding the network.
High value engineers ask what else will break, what future change this enables, and what hidden complexity already exists in the area they are touching.
7.2 Expanding the Problem Boundary Responsibly
Expansive problem solving does not mean gold plating. It means recognising when adjacent issues can be safely resolved while the system is already open.
By solving nearby problems at the same time, engineers reduce future change cost and increase the return on every intervention.
7.3 Reducing Future Work
The most valuable engineers remove entire classes of future tickets. They simplify mental models, clarify ownership, and leave systems easier to change than they found them.
They optimise for the long term cost curve, not the next status update.
8. Why Robotic Delivery Models Fail
Some organisations treat teams as input output machines, managed through narrow SLAs and superficial progress indicators.
This approach produces local optimisation and global inefficiency. Work may appear to move, but value leaks through rework, fragility, and accumulated complexity.
This is the organisational equivalent of forcing traffic through a congested network path because it looks short on a diagram.
9. Execution Pathways Matter More Than Velocity
High performing teams debate execution strategy, not just timelines. They consciously choose when to refactor, when to batch changes, and when to absorb risk versus defer it.
This is human workload routing in action. The goal is not raw speed. The goal is the lowest total system cost over time.
10. Self Regulating Teams vs Managed Bottlenecks
The strongest teams self regulate delivery risk, testing effort, non functional gains, and release timing. They do not require constant external control to make safe decisions.
Like OSPF, they adapt dynamically to changing conditions and advertise their true state through outcomes rather than promises.
11. The Cost of Indulgence
Indulgence in engineering teams rarely looks like laziness. More often, it presents as helpfulness, flexibility, or responsiveness. Teams accept work that should be declined, reshaped, or challenged, and they pivot repeatedly in the name of being accommodating. While well intentioned, this behaviour carries a high and often hidden cost.
An indulgent team says yes to workloads that are expensive, poorly framed, or actively harmful to client outcomes. They accept complexity without questioning its origin. They implement features that satisfy a request but degrade system clarity, performance, or safety. In doing so, they optimise for short term harmony rather than long term value.
Another form of indulgence is constant pivoting. Teams abandon partially completed work to chase the next urgent request, leaving behind half built solutions, unreconciled design decisions, and accumulated technical debt. Nothing truly completes, and the organisation pays repeatedly for context switching, relearning, and revalidation.
Examples of indulgent behaviour include implementing bespoke logic for a single client when a systemic solution is required, layering exceptions instead of fixing a broken abstraction, accepting unrealistic deadlines that force unsafe shortcuts, or continuing work on initiatives that no longer have a clear outcome simply because they were already started.
These behaviours increase total system cost. They inflate testing effort, complicate support, and create fragile software that is harder to reason about. Most critically, they lead to anti client outcomes where apparent progress masks declining quality and trust.
Avoiding indulgence requires tension. Productive, respectful tension between execution teams and those requesting work is essential. Tense conversations clarify intent, surface hidden costs, and force prioritisation. They allow teams to reshape workloads into something that is achievable, valuable, and safe.
High performing teams do not confuse compliance with effectiveness. They are willing to say no, not as an act of resistance, but as an act of stewardship. By declining or reframing indulgent work, they protect the organisation from inefficiency and ensure that every execution pathway is intentional rather than reactive.
12. Why Complex Support Always Routes to the Same Engineers
In every engineering organisation, complex support issues have a way of finding the same people. These are the incidents that span multiple systems, lack clear ownership, and resist simple fixes. This is not accidental. It is workload routing in action.
When a problem is poorly understood, the organisation implicitly looks for the shortest path to understanding, not just resolution. Engineers who take the time to deeply understand systems, data flows, and failure modes advertise themselves as low cost paths for uncertainty. Over time, the routing becomes automatic.
These engineers share common traits. They are curious rather than defensive. They ignore artificial boundaries between teams, technologies, and responsibilities. They ask how the system actually behaves instead of how it is documented. They are willing to trace a problem across layers, even when it falls outside their formal scope.
By doing this repeatedly, they accumulate something far more valuable than narrow expertise. They develop system intuition. Each complex support issue expands their mental model of how the organisation’s technology really works. This compounding knowledge makes them faster, calmer, and more effective under pressure.
As a result, they become critical to the organisation. Not because they hoard knowledge, but because the system naturally routes its hardest problems to those who can resolve them with the least friction. With every incident, their skills sharpen further, reinforcing the routing decision.
This is why the best engineers are almost always the ones who leaned into complex support early in their careers. They treated ambiguity as a learning opportunity, not an inconvenience. In doing so, they became the shortest path not just to fixing problems, but to understanding the system itself.
13. Organisations Route Work Whether You Design for It or Not
Every organisation has an invisible routing protocol. Work will always find the path of least resistance and lowest cognitive load.
You can fight this reality with process and control, or you can design for it by building competent teams that reduce total organisational cost.
In both networks and organisations, traffic flows toward reliability, not authority.