Introduction
As a software engineer, I solve problems constantly. Looking back, I realize that at their core, software engineers are essentially thinking machines. Our daily routine closely resembles that of professional business consultants: we ask questions, gather data, validate our understanding, identify the root problem, and explore possible solutions.
Larger companies typically handle significantly more traffic than smaller ones, which means their backend systems operate at a much greater scale. In addition, bigger businesses tend to have more teams, bringing more people into the mix. With increased manpower and more complex systems, it's safe to say: the bigger the company you work for, the more challenges you're likely to encounter.
I've made my fair share of mistakes throughout my career. I frequently struggled with issues like logical inconsistency and inaccurate solutions in my thinking. As I transitioned to larger companies, these challenges began to affect both my speed and performance. Fast forward to today—now a more experienced engineer—I’ve found myself returning to the fundamentals and renewing my trust in the logical tools and thinking frameworks I once learned. More often than not, they've helped me deliver beyond expectations. Through this article, I hope to help readers reconnect with those same foundations.
Entity Relationship Diagram
Also known as ERD, the Entity-Relationship Diagram is often underestimated by engineers as a communication tool—at least in my experience over the past four years. While it may work reasonably well for communicating with other engineers, non-technical stakeholders are often left in the dark. When the message isn’t clear or memorable, they end up asking the same questions repeatedly down the line.
In my experience, ERDs aren't limited to database design. Even when entities aren't directly related, an ERD can still be useful—it helps abstract away the underlying complexity and clarify their relationships. Many data analysts often misinterpret the data they work with simply because they’re unaware of how downstream entities are connected.
In some cases, even class object relationships can be visualized using ERD-like diagrams, although UML is the more standard approach for this purpose. Clearly representing these relationships adds transparency to backend systems and makes them easier to reason about.
When communicating with non-technical stakeholders, a full-blown ERD can be overwhelming. To make things more accessible, we can simplify it into a conceptual ERD instead. Conceptual ERDs typically omit internal fields, allowing readers to focus more clearly on the entities themselves and the relationships between them.
Sequence Diagram
In many engineering teams, you’ll see one “mega diagram” that tries to do everything — show infrastructure, endpoints, databases, and the step-by-step flow of a process. This is very common when engineers gather and sketch up a rough system design proposition. While it’s technically possible, in practice it often ends up looking like an overstuffed subway map. They are hard to read, harder to maintain, and usually outdated within a few sprints.
In reality, architecture diagrams and sequence diagrams serve different purposes. Keeping them separate not only makes them clearer but also makes the documentation far more useful in the long run.
To put simply, an architecture diagram shows the layout of your system. They highlight resources and components, help distinguish public and private boundaries, as well as show all the supporting middlewares. This view helps engineers estimate the effort and resources needed for a change or integration. The main purpose of the diagram is to highlight where things live and how they connect — not about how they behave over time.
A sequence diagram shows how a process happens. They highlight the actors or services involved as well as the messages exchanged in a chronological order. Rather than having to bring the entire infrastructure into focus, a sequence diagram only displays relevant actors and services involved in a certain due process.
When you try to capture both system structure and process behavior in the same diagram, the result is usually so unreadable that it does neither of the jobs well. Separating them gives you the best of both worlds: a clean high-level architecture view for planning and integration work and a focused step-by-step sequence view for understanding specific flows. This separation keeps each diagram lightweight, relevant, and easy to update. When you or your teammates revisit the documentation months later, it’s easy enough to recognize. The small extra effort up front pays for itself many times over in clarity and maintainability.
Nodal Analysis
In electrical engineering, Kirchhoff’s Current Law (KCL) states that the total current entering a node must equal the total current leaving it. This principle ensures that no energy is mysteriously created or lost in a circuit—it all flows in balance. Interestingly, this idea has a valuable parallel in software engineering, especially when it comes to observability and system monitoring.
Think of a node in an electrical circuit as a service, endpoint, or processing unit in your architecture. Requests, events, or messages flow into it, and outcomes flow out. These outcomes can be categorized as successful responses, failures, timeouts, or even dropped requests. If we want reliable metrics and trustworthy dashboards, we must account for all inputs and outputs at the same observation point, just like how an electrical engineer analyzes a circuit node.
Too often in software systems, teams monitor “success rate” without fully accounting for what flows in and out of the system. Maybe successful responses are logged at the application layer, but errors are only visible at the proxy level. Or incoming requests are counted at the edge service, while failures are logged deeper in the stack. These mismatches in observation scope make metrics unreliable and can mislead you about the health of your system.
By borrowing from KCL, we can enforce a clean accounting model:
Total Inputs = Successful Outputs + Failed Outputs + Any Other Exit States
This mindset forces rigor. If you see 10,000 requests coming into a node, but only 9,500 accounted for in your success and failure metrics, something is wrong. Are 500 being dropped silently? Are retries being double-counted upstream? Are metrics being sampled inconsistently? Just like charge can’t pile up in a circuit, requests shouldn’t “disappear” in a system. Applying this “sum in = sum out” framework helps engineers spot blind spots in their observability stack and encourages consistent monitoring instrumentation across distributed systems.
Flow Chart Diagram
If you mostly work on high-level designs, you might not use flowcharts very often. In many projects, they’re even skipped entirely, especially when the code implementation seems self-explanatory.
However, when you need to explain and document complex logic with multiple conditions, a flowchart is often the best tool for the job. Compared to architecture and sequence diagrams, it’s far better at showing branching paths, loops, and step-by-step tasks. Flowcharts are commonly used to illustrate low-level algorithms or detailed workflows, where an engineer can dive into specifics — such as exactly how many tasks are involved to complete a process. This level of detail makes it easier to communicate complex logic clearly to a wide range of audiences.
Gantt Chart
It’s commonly used by project managers to identify critical paths and estimate timelines for key milestones. Usually displayed as a directed graph, it serves as an effective visualization tool for displaying the number of tasks, their relative difficulty, and the dependencies between them.
For software engineers, this kind of visualization can be especially helpful. For example, when planning a project, you can estimate a realistic completion date by breaking your sprint into clear checkpoints and subtasks. Mapping these out helps you identify dependencies and allocate time more effectively.
The Gantt chart can also be great for simpler use cases. For instance, when working on a project that involves multiple parties, it’s easy to lose track of who’s responsible for what, leading to wasted productive time. A Gantt chart helps your team by showing the dependencies between subtasks, allowing everyone involved to focus their energy on actionable items in parallel—rather than waiting or getting lost in the process. And to make it effective, you don’t even need to define a minimum or maximum time estimates for each subtask if what you’re trying to achieve is just parallelism and not time estimation.
SWOT Framework
The SWOT Framework is a popular method usually used to assess an individual, a team, or a company's competitive position and to plan a strategy for growth. The name stands for the 4 aspects that the framework covers:
- Strength: These are positive attributes internal towards the subject. They can be efficient task handling, skilled work force, or high brand reputation.
- Weakness: These are negative aspects or limitations that can hinder the subject from growth. This includes poor customer care, slow response, and lack of discipline.
- Opportunities: These are external factors that can be leveraged for growth.
- Threats: These are external factors unfavorable to the subject's progress.
Ironically, the framework’s popularity sometimes works against it — people overlook it or treat it as a routine checkbox exercise. In reality, it’s one of the most valuable tools for activities like sprint reviews or team retrospectives. From personal experience, filling out a SWOT grid on the spot can be surprisingly challenging; when past challenges or successes aren’t fresh in mind, engineers often struggle to recall key lessons learned or what went particularly well. It can be far more effective if the SWOT form is available to fill out at any time during the week or sprint, so when incidents occur, team members can capture them while the details are still fresh.
Conclusions
- As a problem solver, you don’t have to reinvent the wheel by coming up new ways to break down a problem or display information.
- Existing frameworks can help us move faster when used for the right purpose properly.
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