You're not losing productivity.
You're losing memory.
Every time a new engineer joins, you re-explain the architecture. Every time an agent starts a task, you re-paste the context. Every time someone leaves, a year of decisions leaves with them.
The problem isn't prompts. It's that your team has no shared memory your agents can actually read.
You're not the only one yelling at your AGENTS.md
Adding more rules doesn't fix compliance — it makes it worse. The same complaint, in 168 different ways.
Every time Claude ignored an instruction, I added another rule to CLAUDE.md. The file got longer; compliance got worse.
Claude completely invents new database paths. I barely check his work anymore.
AI coding agents hallucinate library internals constantly — confidently describing functions based on stale training data.
The agent forgets your conventions, introduces patterns you don't use, and you spend more time correcting than building.
Every time Claude ignored an instruction, I added another rule to CLAUDE.md. The file got longer; compliance got worse.
Claude completely invents new database paths. I barely check his work anymore.
AI coding agents hallucinate library internals constantly — confidently describing functions based on stale training data.
The agent forgets your conventions, introduces patterns you don't use, and you spend more time correcting than building.
My AI coding agent has no memory between sessions. Every new session starts from zero.
Context management in long conversations is a fundamental challenge.
Created an infinite loop that spiked my GCP invocations 10,000%. I love using Claude, but I barely check his work anymore.
It was too dumb to deduce what edge cases to test. I wasted hours cleaning up crappy code.
My AI coding agent has no memory between sessions. Every new session starts from zero.
Context management in long conversations is a fundamental challenge.
Created an infinite loop that spiked my GCP invocations 10,000%. I love using Claude, but I barely check his work anymore.
It was too dumb to deduce what edge cases to test. I wasted hours cleaning up crappy code.
A brief tree your team — and every agent — can query.
Brifly organizes knowledge as a tree of briefs: specs, RFCs, runbooks, walkthroughs, and postmortems. Each brief holds rich text, code blocks, diagrams, and inline video recordings (auto-transcribed) — and a CLI ships with every account.
Record once. Every engineer and every agent that joins your team inherits the full context.
Three things every team tool should already do.
Video-native
Record a bug repro, walkthrough, or system explanation. Brifly transcribes it automatically and makes it queryable — not just watchable.
Sarah Chen · 1m 47s
Agent-native
Structured JSON for any agent. Markdown piping drops a brief straight into Claude Code or Cursor.
Tree structure
Not a flat wiki. Briefs nest into briefs — your architecture is a hierarchy, your docs should be too.
Every tool owns one dimension.
Brifly owns all three.
| Tool | AgentAgent-native | VideoVideo-native | TreeTree structure |
|---|---|---|---|
| Briflyyou | |||
| Notion | Partial | ||
| Loom | |||
| Scott AI |
Built for teams already shipping with agents.
“Your team's quote could go here. We're onboarding our first cohort now — staff and lead engineers who've felt the brief tree save context during a departure, an outage, or a long-running agent task.”
Early access is limited.
We're onboarding teams gradually — not to create artificial scarcity, but because we set up every team properly before they go deep on the product. You'll get a setup call, a starter brief tree built for your stack, and a direct line to us while we're small.
We're looking for teams actively using Claude Code, Cursor, or Codex who have felt the context problem firsthand.