Work out what the solution needs to achieve.
A request for an application often starts with a feature list. The useful question is what those features need to make possible for the people doing the work.
Who needs the result? What is difficult today? Which rules must the solution respect? These answers shape the business requirements and give the design a purpose.
This is where Signal Logic Labs starts. We work through the need and the proposed response before committing to the build. That gives us a chance to catch missing decisions while they are still easier to fix.
Follow people through the whole task.
A screen can look convincing while leaving the difficult parts unresolved. Consider a simple request-approval feature.
Who can approve a request? Can they approve their own? If the request changes while someone is reviewing it, which version are they approving? What should the user see if a notification fails?
Working through these situations tells you far more than the feature name alone. The answers belong in the requirements, user journeys and technical specifications.
Design also needs to cover people arriving for the first time, missing information, restricted access and recovery from errors. Walk through those tasks before treating a set of screens as a finished design.
Give implementation a clear starting point.
A useful technical specification explains how the solution will behave and what it depends on. It connects the business rules with the data, permissions, interfaces and failure handling needed to make them work.
Clients need to understand the proposed solution and its trade-offs. Developers and AI agents need enough detail to implement it without deciding important business rules for themselves.
The specification should also explain how the result will be checked. If a request needs two approvals, the acceptance test should exercise that rule, including what happens when one approval is missing.
Keep the design connected to the build.
You will learn more as work progresses. When a requirement changes, revisit the affected design, implementation and tests. Keep those parts in agreement rather than relying on a decision that has become outdated.
People remain responsible for important scope and risk choices and for authorising release. AI agents can take on implementation tasks and routine corrections within the agreed limits.
Make faster delivery serve a better solution.
We developed Signal Logic Factory around this whole project workflow. It organises requirements, design, specifications and checks above the execution harness, which is the environment where AI agents run tasks and work with code.
The opportunity is to put more human attention into solving the problem while reducing the effort needed to implement the answer. Clear specifications give that work direction and make it possible to check whether the solution meets the brief.
Bring us a new idea, an existing system or a design already taking shape. Share your project and we can work through what it needs to achieve and how to deliver it.
