Free planning resource

Write a software brief a product team can actually use.

Clarify the problem, people, first release and constraints before asking for estimates. A useful brief does not need technical language—it needs specific business context.

Download the plain-text template

Use it for

  • Custom business software
  • Android or iPhone apps
  • SaaS product development
  • Customer portals and dashboards
  • AI tools and automation

The eight sections

Enough detail to improve the conversation—not lock the solution too early.

01

Business outcome

What should become faster, safer, simpler or commercially possible after this software exists?

02

Users

Who uses it, what are they trying to do, and what access or permission differences matter?

03

Current workflow

How does the work happen today? Include spreadsheets, messages, approvals, hand-offs and known pain points.

04

First-release scope

What is the smallest complete journey that would deliver useful evidence or operational value?

05

Data and integrations

What existing systems, APIs, files, payments, identity providers or reporting tools must connect?

06

Constraints and risks

Note privacy, security, compliance, migration, offline use, deadlines and critical dependencies.

07

Success measures

How will you know the product is useful—time saved, errors reduced, adoption, completion or revenue?

08

Decision process

Who gives feedback, who approves scope and budget, and how quickly can the team answer questions?

Before requesting a quote

Avoid turning assumptions into requirements.

Describe what needs to change and why it matters before prescribing every screen or technology. A product team should be able to question the approach while protecting the commercial outcome.

Separate the first useful release from future ideas. This makes estimates more meaningful and gives the team a clear way to test whether the product is solving the right problem.

Include examples of the current process. Screenshots, forms, spreadsheets and anonymised sample data often explain more than a long feature list.

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