Writing: The Enterprise Architect’s Primary Tool

[Robert Melton]4 min read (826 words)
#architecture  #team-leadership  #communication  #documentation 
Writing: The Enterprise Architect's Primary Tool

Enterprise architects bridge executives, developers, and users. No tool automates this. The primary skill is writing - clear, concise documentation that aligns technology with business goals.

AI makes this more important, not less. LLMs need context. Agents need documentation. Teams need alignment. All of this starts with written artifacts.

Strategic Alignment Requires Written Clarity#

Technology alignment begins with understanding business goals. This means listening, asking questions, and writing down what you learn. Written documentation creates shared understanding across the organization.

When priorities shift, written strategy documents show what changed and why. When new leaders arrive, written architecture decisions explain current state. When teams debate direction, written goals provide the reference point.

Architecture as Written Artifact#

Creating architecture involves research, conversations, and decisions. Document all three.

Research findings become reference material for future decisions. Conversation outcomes captured in writing prevent repeated discussions. Decision records explain tradeoffs to teams implementing the architecture.

If you can’t explain an architectural decision in writing, you don’t understand it well enough. The act of writing forces clarity.

Governance Through Documentation#

Governance without written goals devolves into aligning to what exists rather than what’s needed. Written governance frameworks prevent this drift:

  • Document desired state first
  • Measure current state against it
  • Track gap closure over time
  • Adjust framework based on results

Without written goals, governance becomes reactive rather than strategic.

Technical Evaluations as Knowledge Base#

Every tool evaluation generates knowledge. Document it.

Write evaluation criteria before testing tools. Write findings during evaluation. Write recommendations with specific rationale. Future evaluations reference this work, preventing repeated analysis.

Template example:

# Tool Evaluation: [Tool Name]

## Criteria
- Performance requirements: [specific metrics]
- Integration requirements: [systems to connect]
- Cost constraints: [budget limits]
- Team expertise: [learning curve acceptable]

## Findings
- Performance: [actual measurements]
- Integration: [compatibility results]
- Cost: [total cost of ownership]
- Adoption: [team feedback]

## Decision
[Adopt/Reject with specific reasoning]

This becomes searchable organizational knowledge.

Collaboration Requires Persistence#

Meetings generate decisions. Conversations surface insights. Written records make them permanent.

Meeting notes capture action items and context. Design discussions documented become references. Decisions recorded prevent revisiting settled questions.

Unwritten collaboration is ephemeral. Written collaboration compounds.

Risk Management Starts With Documentation#

Risk identification requires talking to everyone. Risk mitigation requires writing everything down.

Risk registers document what keeps teams up at night. Mitigation strategies record how you’re addressing each risk. Incident reports capture what went wrong and what you learned.

When incidents occur, written risk documentation shows whether this was known or novel. When audits happen, written risk management demonstrates due diligence.

AI Amplifies Writing’s Importance#

LLM-based tools need written context:

Documentation becomes AI context: Well-written architecture docs let AI agents answer questions about your systems.

Written decisions train agents: Decision records help AI understand your organization’s reasoning patterns.

Text artifacts enable automation: Scripts, workflows, and agents can process written documentation. They can’t process verbal agreements.

Prompt engineering IS writing: Communicating with AI requires the same clarity as communicating with humans.

The better your written documentation, the more effectively AI can assist with architecture work.

Modern AI Tools for EAs#

Context Assembly:

# AI agent reads your architecture docs
context = load_architecture_docs()
decision_history = load_decision_records()

# Agent answers questions using your documentation
answer = llm.ask(
    question="Why did we choose Kafka over RabbitMQ?",
    context=context + decision_history
)

Document Generation:

# AI helps draft evaluation reports
evaluation = llm.generate(
    prompt="Create evaluation report for [tool]",
    template=standard_eval_template,
    findings=research_notes
)

Risk Analysis:

# AI identifies gaps in risk coverage
risks = llm.analyze(
    documentation=architecture_docs,
    prompt="What risks aren't documented here?"
)

All of this requires well-written input. AI quality depends on documentation quality.

Practical Writing Patterns#

Architecture Decision Records (ADRs):

# ADR-001: Use PostgreSQL for Primary Database

## Context
Need persistent storage for user data and transactions.

## Decision
Use PostgreSQL 14+ as primary database.

## Rationale
- ACID compliance required for financial data
- Team has 5 years PostgreSQL experience
- Handles 10K writes/sec (current: 2K writes/sec)
- Lower total cost than DynamoDB at our scale

## Consequences
- Need to manage backups and replication
- Requires database expertise on team
- Cannot leverage serverless patterns easily

Technical Evaluation Template:

# Evaluation: [Tool Name]

**Problem:** [What we're trying to solve]
**Candidates:** [Tools evaluated]
**Winner:** [Selected tool]
**Why:** [Specific reasons with metrics]
**Trade-offs:** [What we gave up]
**Next Steps:** [Implementation plan]

Risk Register Format:

| Risk | Likelihood | Impact | Mitigation | Owner |
|------|-----------|--------|------------|-------|
| Database failure | Medium | High | Daily backups, read replica | DevOps |
| Vendor lock-in | High | Medium | Abstract via interface layer | Architecture |

The Core Skill#

Tools help. Processes help. AI helps. But writing remains the fundamental skill for enterprise architects.

You align strategy through written documents. You create architecture through written decisions. You govern through written standards. You evaluate through written analysis. You collaborate through written artifacts. You manage risks through written registers.

Everything traces back to writing.

Available examples at github.com/robertmeta in various architecture documentation repos.