The ROI of Brief, in three buckets.
Brief helps your team in three ways: it cuts your token spend, it saves project cost by giving hours back to the people on the clock, and it shortens the time it takes to get work in front of customers. Below is each claim, the math behind it, and a calculator to run your own numbers.
Token Spend
Brief cuts the AI token bill by a conservative 15%, applied to whatever your organization spends across its teams. Benchmarked on SWE-bench, full breakdown in the paper.
Time Saved
Brief trims ~2-3% off a project's cost by giving an hour back per person each week. That adds up fast across a large org.
Faster Time-to-Market
Reduced alignment cost leads to ~30% shorter time to market. Features get out the door quicker.
Run your own numbers
Set your token spend, team size, and cycle length. Every figure below updates live using the same conservative model.
Direct savings combine token spend and time saved. Faster time-to-market compounds on top: revenue arrives sooner, but we leave that out of the total on purpose.
Where the return comes from
Every Brief use case drains one of three things: tokens, hours, or weeks. The ROI model prices exactly those three. Twelve use cases, each with its before and after, mapped to the bucket it feeds.
Tokens: agents that stop burning turns
Hours: time back on the clock
Weeks: compress the wait, not the work
Token Spend
When an AI coding agent works on a larger project, it breaks the work into atomic tasks, and a typical project runs 7-10 turns (a turn = one ask-and-reply) to finish.
To size the token savings, we benchmarked Brief against similar tools using public data like SWE-bench. We measured a 2.2% token savings per turn. Compounded across the turns in a project, that's 15% less token usage overall. We quote the bottom of the measured range on purpose.
| Turns in project | Per-turn saving | Cumulative token reduction |
|---|---|---|
| 7 | 2.2% | ~14% |
| 8 | 2.2% | ~16% |
| 10 | 2.2% | ~20% |
See this paper for the full breakdown of cost savings with AI coding agents.
Time Saved
When a team works on a large project, much of their time goes to finding relevant information and correcting AI agents when they steer off in the wrong direction.
We've calculated that, at a minimum, Brief saves each team member at least one hour per week by automatically aggregating relevant context and sharing it directly with their team and AI tools: an additional ~2-3% off a project's cost.
One hour is deliberately the floor, not the expected case. If your teams recover more, the model scales linearly and the saving rises with it.
Faster Time-to-Market
An additional cost of developing a project comes from meetings, status updates, roadmap planning, and everything else in the bucket of "making sure everyone is aligned."
Because Brief follows a feature through its entire development cycle, it gives every team full visibility into a project's history and what each stakeholder cares about. We estimate this meaningfully shortens time-to-market on most projects by around 30%.
| Step | Value | Logic |
|---|---|---|
| Total cycle time | 13 weeks | Baseline for a representative project |
| Alignment portion | 8 weeks | Meetings, status, roadmap, re-syncing context |
| Brief cuts alignment by | 50% | Full project history is visible to every stakeholder |
| Weeks recovered | 4 weeks | 50% of 8 weeks |
| Net cycle reduction | ~30% | 4 weeks saved / 13 week cycle |
A 50% cut to the alignment block is a ~30% cut to the whole cycle. Adjust the 8-week alignment estimate to your reality and the 30% moves with it.
How we got to these numbers
Token Spend
We benchmarked Brief against comparable tooling on public SWE-bench data and measured a 2.2% reduction in tokens per turn. Applied turn over turn, a typical project of 7-10 turns yields 14-20% fewer tokens. We quote 15%, near the bottom of that range, so the estimate stays conservative. Full breakdown in the paper.
Time Saved
Engineers lose time to two things Brief addresses directly: hunting for context that lives in someone's head or an old thread, and re-steering agents that drifted because they lacked that context. We size this conservatively at one hour recovered per person per week, which is roughly 2-3% of a 40-hour week, valued at your fully loaded cost per hour across 50 working weeks.
Time to Market
We take your total cycle time, isolate the alignment portion (meetings, status, roadmap, re-syncing context), and apply a 50% reduction to that block, since Brief makes full project history visible to every stakeholder. The recovered weeks divided by the total cycle give the net reduction.
Common questions
Does Brief make my agents use fewer tokens?
Yes. Agents with the right context up front spend fewer turns rediscovering decisions and backing out of wrong directions. We measured a 2.2% token saving per turn on public SWE-bench data, which compounds to roughly 15% across a typical project.
Where does the one hour per person per week come from?
It's a deliberate floor. It covers the two time sinks Brief addresses directly: hunting for context that lives in someone's head or an old thread, and re-steering agents that drifted because they lacked that context. If your teams recover more, the model scales linearly.
Is the 30% time-to-market number fixed?
No, it's derived. We assume a representative 13-week cycle with 8 weeks of alignment work, and a 50% cut to that alignment block. Adjust the alignment estimate to your reality and the number moves with it. The calculator above does exactly that.
How do I validate this for my org?
Run a pilot. Brief connects to your existing tools, so a small team can measure token usage, hours recovered, and cycle time against their own baseline within a quarter.
Ready to run the numbers for real?
Brief plugs into the tools your team already uses. A small pilot measures token usage, hours recovered, and cycle time against your own baseline in a quarter.