By Arjun Mehta
I have seen a lot of architecture documents. Neat C4 diagrams. Detailed service maps. Carefully labeled component charts. And I have watched almost all of them become fiction within six months of being drawn.
The problem isn't that engineers are undisciplined about updating docs. It's that the standard approach to software architecture documentation has a fundamental design flaw: it treats architecture as something you document once, rather than something you continuously surface.
Here's what actually happens at teams that take architecture documentation seriously. A senior engineer spends a week creating a comprehensive system diagram. It's accurate and genuinely useful. Three months later, two new services have been added, one has been refactored into three, and a caching layer nobody documented was quietly introduced to fix a production issue. The diagram is now misleading. Updating it would take another three days. Nobody has three days. The diagram stays wrong. People stop trusting it.
This cycle repeats until teams either stop doing architecture documentation entirely or convince themselves the docs are "good enough" while privately not relying on them for anything important.
What Software Architecture Documentation Is Supposed to Do
Before fixing the problem, it helps to be precise about what architecture documentation is actually for. There are two distinct purposes, and conflating them is the root cause of most documentation failures.
Purpose 1: Capturing architectural decisions. Why was this service split out? Why is authentication centralized? Why do we use event sourcing for the order flow but not for user profiles? These are decisions made at a point in time, with specific context. They deserve documentation because the context that produced them often isn't obvious from looking at the resulting code. Architecture Decision Records (ADRs) exist precisely for this purpose. An ADR written in 2021 explaining why the team chose a microservices approach over a monolith is still useful in 2026, even if the specific services have changed significantly.
Purpose 2: Capturing architectural structure. What exists? How does it connect? What calls what? Who owns what? This is the "map of the territory" problem - giving engineers a way to understand the system without reading every line of code.
The mistake is treating both purposes the same way: write a document, maintain it manually, update it when things change. This works reasonably well for Purpose 1 (decisions are relatively stable). It fails systematically for Purpose 2 (structure changes constantly).
Why Structure Documentation Always Goes Wrong
For architecture structure to stay accurate in a living codebase, it has to be updated in parallel with the code. In practice, this means:
Every time a new service is added, someone updates the architecture diagram. Every time a dependency relationship changes, someone updates the service map. Every time a module is refactored, someone updates the component diagram. Every time an API contract changes, someone updates the API documentation.
In a team shipping continuously, this is a second job. It's a second job that has no on-call rotation, no sprint allocation, no deadline, and no immediate visible consequence if you skip it. So it gets skipped. Not because engineers are irresponsible - because the incentive structure makes skipping the rational choice in the short term.
There's also a subtler problem: the person best qualified to update the architecture documentation is the person who made the change. But they wrote the code, the PR, the commit message, and reviewed two other PRs today. Adding "update the architecture doc" to that list is friction, and friction compounds. Teams that mandate architecture doc updates in their PR checklists see one of two outcomes: engineers stop making changes in ways that require diagram updates (bad), or the mandate silently stops being enforced after two sprints (common).
The ADR Pattern: What Actually Works for Decisions
Architecture Decision Records are worth doing properly because they solve a real problem (preserving decision context) in a way that's resistant to staleness (decisions don't change as fast as structure).
A good ADR has four parts: the context (what situation prompted this decision), the decision (what you chose to do), the rationale (why you chose it over the alternatives), and the consequences (what this means going forward). It's written once, at the time of the decision, and essentially never updated - if the decision changes, you write a new ADR referencing the old one, rather than editing the original.
The format works because the cognitive load is front-loaded. You write it when the context is freshest. Future engineers reading it understand not just what the system does but why it works the way it does. This is the engineering knowledge that most resists recovery without documentation - code tells you what, ADRs tell you why.
For teams not currently using ADRs: start small. Don't try to document every past decision retroactively. Pick the next significant architectural choice you make and write an ADR for it. One paragraph of context, one paragraph of decision, one paragraph of rationale. That's enough to establish the habit.
Structural Architecture: The Case for Derivation over Documentation
For architectural structure - the "map of the territory" problem - the right answer is not better documentation practices. It's accepting that manual structural documentation is the wrong tool for the job and finding approaches that derive structure from the code itself.
The code already contains the structural information. Import statements encode dependency relationships. Service calls encode integration patterns. Module organization encodes architectural boundaries. API schemas encode contracts. The information exists - it's just embedded in the code rather than in a diagram.
This is why a growing category of engineering tools focuses on surfacing structural architecture from the codebase rather than asking humans to document it. Tools that analyze import graphs to produce live dependency maps. Tools that visualize service call patterns from actual traffic rather than from manually-drawn diagrams. Tools that map ownership from git history rather than from an org chart.
Glue, for instance, reads the codebase directly to surface exactly this kind of structural knowledge - who owns what, what depends on what, where the high-risk change areas are - without requiring any manual documentation. This isn't a pitch for one specific tool. It's a point about category: if your architecture documentation keeps going stale, the fix probably isn't more disciplined documentation. It's switching from documentation to derivation for the structural layer. See Understanding Code Dependencies for a deeper look at how dependency relationships are embedded in code.
What Good Architecture Documentation Looks Like in Practice
Based on what actually works at teams that have solved this, the approach that holds up is a hybrid:
ADRs for decisions. Written at decision time. Stored in the repo alongside the code (so they're version-controlled and change-tracked). Never edited retroactively. A well-maintained ADR log is genuinely valuable engineering knowledge that compounds over time.
Derived maps for structure. Architecture diagrams generated from the code, not drawn by hand. Dependency visualizations from actual imports and API calls. Ownership maps from git activity. These can be regenerated at any time and are always current because they come from the current code.
Lightweight README discipline. Each service or module has a README that explains its purpose and main interfaces. Not the full architecture - just "what is this thing and what does it do." This is small enough to maintain and useful enough to justify the effort.
Runbooks for operations. How to deploy, how to roll back, what to do when it breaks. This is separate from architecture documentation proper but often gets conflated with it. Runbooks have a different maintenance pattern: they're updated when the process changes, and the change usually happens alongside an incident, which provides the forcing function.
The common thread is matching the documentation approach to the stability of what's being documented. Decisions are stable - document them carefully. Structure changes constantly - derive it from code. Operations change on event - update runbooks with events.
The Deeper Problem: Architecture Documentation as Status Symbol
There's a meta-issue worth naming. In many engineering organizations, having architecture documentation functions as a signal of engineering maturity rather than as a practical tool. Teams create elaborate documentation because it demonstrates seriousness, not because anyone relies on it for day-to-day decisions.
When documentation is primarily performative, the quality bar becomes "looks comprehensive in a review" rather than "helps engineers make better decisions." This produces exactly the kind of documentation that fails: beautiful when new, misleading when old, and trusted by nobody.
The practical test for any architecture document is simple: did an engineer use it to make a decision last week? If the answer is consistently no, the documentation isn't serving its purpose regardless of how thorough it looks.
Good software architecture documentation is sparse, current, and trusted. Bad architecture documentation is comprehensive, stale, and ignored. Most teams, if honest, have the latter. The fix isn't more of the same approach with more rigor applied. It's recognizing which parts of architecture knowledge belong in documents and which parts should be derived directly from the codebase.
FAQ
What should a software architecture document include?
It depends on which type of architecture documentation you're creating. For decision documentation (ADRs), include: context, decision, rationale, and consequences. For structural documentation, consider whether you're better served by documentation or by tooling that derives structure from the code itself. At minimum, a software architecture document should include system context (how the system fits into the larger environment), component overview (major parts and their responsibilities), and key interface definitions (how components communicate).
How do you keep architecture documentation up to date?
The honest answer is that most teams don't - and the ones that try often fail because manual updates are too high-friction. The practical approaches that work: use ADRs for decisions (they're inherently stable and don't need updating), use tooling that derives structural information from the codebase automatically (so it's always current), and keep manually-maintained docs as lightweight as possible so the maintenance burden stays manageable.
What is the difference between software architecture and system design?
Software architecture refers to the high-level structure of a software system: its major components, how they relate to each other, and the principles guiding its design. System design is a broader term that often includes infrastructure, hardware, deployment topology, and operational concerns alongside the software architecture. In practice, "system design" is frequently used as a synonym for software architecture, particularly in interview contexts.
What tools are used for software architecture documentation?
Common tools fall into two categories. Diagramming tools (Miro, Lucidchart, draw.io, the C4 model with tools like Structurizr) help create visual architecture documents. Codebase intelligence tools (which analyze the actual code to derive architectural structure) produce maps that stay current without manual updates. Most mature engineering teams use both: diagramming for presentations and ADRs, codebase tooling for operational architectural understanding.
Related Reading
- What Is Engineering Intelligence?
- What Is Codebase Intelligence?
- The CTO's Guide to Product Visibility
- Glue for Competitive Gap Analysis
- What Is Product Knowledge Management?