Build shared context on software engineering problems, reach consensus before the work starts, and have confidence that you’re building the right thing.
The Problem
Your codebases span many systems and millions of lines that no single person understands. Teams working on different parts of it must asynchronously agree on what they’re building before the work can start. That alignment is the bottleneck: hours of meetings, documents, diagrams and side conversations, juggled alongside day-to-day development. This exercise is often so unstructured that it comes down to chasing colleagues until they agree. Agentic development has only raised the stakes. Now that developers work at the speed of AI, a wrong decision can reach your users within a single prompt, without sign-off from the team on the other end of your API or the senior engineer responsible for the design.
Every hour spent getting people to the same understanding is an hour before anyone starts building. Now that AI agents write much of the code, alignment is the slowest part of the work, and the part most worth speeding up.
The people who know the system best end up walking colleagues through the same architecture decision, call after call. That is your most expensive time, spent away from the hard problems only they can solve.
When a decision turns out to be wrong, the work doesn't just stop: it has to be undone. Data gets migrated back, services get redeployed, and the time spent building it is lost along with the time spent unwinding it.
When a service you own goes down because of a misaligned decision upstream, your customers feel it first, and some of them will move to a competitor.
In mid-sized and larger organizations, teams depend on each other for API boundaries, data models and shared services. Everyone involved has to agree before anyone starts building.
When a team spans timezones and cultures, the technical plan can't live in a meeting or in one person's head. It has to be written down precisely, with a clear history, so everyone can build from it with confidence.
Where a wrong decision is hard or expensive to undo once it ships: embedded and air-gapped devices, financial services and similar fields.
Teams that move at the speed of their AI agents need a firm, shared understanding of what they're building before they let those agents loose on the codebase.