Architecture Decision Record Drafting AI Prompt
Writing an Architecture Decision Record (ADR) feels slow when the details live in your head. You know the decision, but you still need clear context, options, and tradeoffs.
A strong prompt fixes that by forcing structure. It guides the AI to produce an ADR your team can review and approve. AskSmarter.ai helps you get there by asking a few focused questions. You’ll capture the “why,” not just the “what.”
In this example, you’ll learn how to:
- Define the decision and scope
- Compare 2–3 viable alternatives
- Document consequences and follow-up tasks
You’ll ship a review-ready ADR faster, with fewer rewrites.
The transformation
Before — Vague prompt
Write an ADR for choosing our new message queue. Make it clear and include pros and cons.
After — Optimized prompt
You’re a staff software engineer. Draft an ADR in Markdown for this decision:
- Context: We run a B2B SaaS on AWS. 12 services publish events. Peak 8,000 msgs/sec. 99.9% SLO.
- Decision needed: Choose SQS + SNS or Kafka (MSK) for async events.
- Audience & tone: Senior engineers. Direct, neutral, no marketing.
- ADR format: Title, Status, Context, Decision, Alternatives (2), Rationale, Consequences, Rollout Plan, Open Questions.
- Constraints: 3-month delivery, team of 4, on-call load must not increase.
Call out cost, ops burden, ordering needs, replay strategy, and failure modes.
Why this works
The vague prompt can’t produce a usable ADR. It leaves the AI guessing your scale, constraints, and decision drivers.
The improved prompt fixes that with clear context and a strict structure:
- It sets a persona and a target audience, so the writing matches your review group.
- It adds measurable inputs like 8,000 msgs/sec and a 99.9% SLO.
- It defines real constraints like timeline, team size, and on-call impact.
- It enforces an ADR template, so you get a consistent artifact.
- It lists evaluation criteria like ordering, replay, and failure modes.
AskSmarter.ai reaches this quality by asking the questions you’d otherwise skip. It pulls out scale, constraints, and success criteria. It then assembles them into a prompt the AI can follow. You get an ADR you can circulate today, not a draft you need to rewrite.
When to use this prompt
Product Managers Aligning Technical Tradeoffs
Turn a rough decision into an ADR that explains impacts, risks, and rollout steps for stakeholders.
Engineering Leads Standardizing Decisions
Create consistent ADRs across teams so reviews focus on tradeoffs, not missing context.
Customer Success Teams Needing Clear Internal Notes
Document backend choices that affect SLAs, incident response, and customer commitments.
Researchers Comparing Solution Approaches
Capture assumptions, alternatives, and open questions before you run experiments or pilots.
Pro tips
- 1
Define success metrics first so the ADR defends the decision with numbers.
- 2
Specify your rollout plan so reviewers can judge risk, not just design.
- 3
List 2–3 realistic alternatives so the rationale feels credible and complete.
- 4
Add operational constraints so the AI addresses on-call load and monitoring needs.
More coding & technical examples
Terraform Infrastructure Module Design AI Prompt
API Rate Limiting Strategy Documentation AI Prompt
Continuous Integration Pipeline Setup Guide AI Prompt
Build a prompt for your situation
This example shows the pattern. AskSmarter.ai guides you to create prompts tailored to your specific context, audience, and goals.