The context your agents are missing
The reason behind a technical choice already exists, scattered across code, closed tickets and documents. Brain holds it together, anchored to the lines that implement it, and you query it from your coding agent.
- Requirements and functional specifications
- Architectural decisions, and the reasoning behind them
- Relationships between system components
- The history of choices: what was replaced, and when
- Documentation attached to the code, not filed beside it
Brain
One source, anchored to the code
services/auth/session.py88-140
Claude Code
Cursor
GitHub Copilot
OpenAI CodexWhat Brain does in your software factory
It starts with requirements, because that is where the value shows first. Every use case ships in two forms: a skill for the agents and a web view for the people.
› userI have to rebuild the authentication module. Which requirements sit behind it?
grep -r "session" services/41 files
open services/auth/session.py1,240 lines
open services/auth/tokens.py386 lines
open services/auth/throttle.py212 lines
open services/auth/middleware.py174 lines
follow the imports9 more files
open services/auth/legacy/sso.py640 lines
open tests/auth/28 files
search Jira for "auth"312 tickets
read AUTH-1180, AUTH-1204, AUTH-1250no rationale
search Confluence for "sessions"7 pages, last edited 2023
infer the behaviour from the code
› agentI reconstructed three behaviours from the code. Why the tokens are opaque is not written down anywhere, so I infer it from the code itself.
a) they needed to revoke a session at once, and a signed JWT cannot be
b) a compliance requirement on how session data is handled
c) they wanted to avoid rotating the signing keys
Impact analysis
From a requirement to the code it touches and to what depends on it, with the architectural decisions and constraints that apply there.
Onboarding people and agents
The project or company brief in a single read. And from any file you can trace back to its reason.
Technical debt, with its reasons
Every debt item tied to the decision or the incident that produced it. Not “there is some debt”, but this debt comes from there.
Your tools feed Brain
It connects to what the team already uses. No migration up front, and no bulk upload to do first.
ClickUpTasks, projectsJiraRequirements, issuesLinearIssues, cyclesAzure DevOpsWikis, tasks, repositoriesGitHubCode repositoriesGitLabCode repositoriesConfluenceDocuments, ADRsNotionDocuments, wikis, notesA context you can query
Entities linked to each other, each anchored to the point in the code it refers to, with its history: what was replaced, when and why. What goes in is proposed by automation and confirmed by people.
In a software factory, knowledge is scattered
It sits in different tools, in sessions that close, and in people. Context is what holds it together, and it is worth more than the tool working on top of it, because it survives every change of model or application.
Costs under control
An agent without context rediscovers the codebase every session, and it does it at your expense. With curated context it consumes less and gets it wrong less often.
A skill for the agents, a view for the people
Agents use it inside the tools the team already has. People explore it from the web, with search, the context of every entity, and a confirmation queue.
Measured, not promised
At one customer, giving the agent the domain glossary took the same task from 60% to 100% success across ten repetitions. One case, and we say so.
The three moments when the problem shows up
The people who work with us got here the same way. Medium or large teams, a codebase nobody documented, and knowledge spread across different tools. Then one of these three moments arrives.
A new feature has to be built
Before writing it you have to understand what it touches, and whether something similar had already been done.
The system has to be understood
A migration, an inherited system, a supplier changing. The code is there, the reason is not.
Someone leaves
They retire or change job, and the only reliable account of how that part works walks out with them.
Every time, someone has to go and reconstruct it, and that time was not in the budget. Delivery on that part stretches, without anyone having planned for it.
Behind the three moments there is one common denominator: the code accumulates, the reasoning does not. Every change leaves behind lines that work and an account of how they got there that is written down nowhere. Whoever comes next starts from the code, and spends their own time rebuilding the rest.
With agents the gap widens instead of closing. They produce more change in less time, and when the session ends the trace of how they got there is left to no one.
The alignment score, on a 0 to 1 scale, between how the best agents reorganize their just-finished work into readable commits, and how a person would organize the same change. Less than half.
AtomicCommitBench, Lin, Zhou, Li (Beihang University), July 2026, on 800 real development episodes across 10 mature Python projects.
It's not broken code, the code works. It's the story of how and why you got there that gets lost, even for the agent that just wrote it.
What a CTO asks first
What we usually find
Three questions you can answer without us. In the companies we talk to, at least one answer is almost always missing.
- How long a new person takes to make their first change on their own, on a repository they did not write.
- When someone asks why a technical choice was made, where they go to look, and how often they end up asking a colleague.
- How many business rules exist only inside the code, with no document explaining them.
If this is not your problem we will say so and stop there.
Thirty minutes with one of the founders, free and with no commitment.
Nothing to install and no access to give us.
What happens in the 30 minutes
- 1You pick a module you already have in production.
- 2We feed it to Brain and look together at what comes out: which requirements sit behind it, and where they got lost.
- 3You keep the notes from the session, even if nothing comes of it.
What happens after
- 1You choose the sources to connect, starting from the ones the team uses every day.
- 2Brain fills up from there, and every entry stays anchored to the lines of code it refers to.
- 3You query it from your coding agent, inside the tools you already have.