Generation keeps getting cheaper.Correctness does not.
TRW connects requirements, verification evidence, and revisable memory across sessions, models, and harnesses. Keep your existing tools, with inspectable records of what was required and what was checked.
Above your model, IDE, and storage. Alongside your coding agent.
Open public beta · Email verification required
Designed for the AI coding ecosystem
The core loop
From requirements to a clean handoff
Follow one change through five steps. The illustrative records below show what you can inspect as work progresses.
Orient
Start with context
Recall relevant constraints and inspect prior decisions before choosing an approach.
Explore MemoryIllustrative record
Recalled constraint: mobile navigation must support keyboard access.
Execute
Work from requirements
Give the agent a defined change with acceptance criteria to work against.
Explore RequirementsIllustrative record
Acceptance criterion: the menu opens, closes, and returns focus using the keyboard.
Verify
Run checks, record evidence
Run project-native checks and record their results. Recording does not run or independently verify a suite.
Explore VerificationIllustrative record
Build record: command, test scope, outcome, and remaining failures.
Preserve
Save material state
Checkpoint unfinished work. Keep discovered constraints and decisions with provenance so they can be recalled and revised.
Explore WorkflowsIllustrative record
Checkpoint: keyboard checks passed; mobile visual review remains.
Hand off
Make the next step clear
Leave the current state, evidence, and unresolved work for the next session or agent.
Explore WorkstreamsIllustrative record
Next-read pointer: mobile review notes, linked requirement, and recorded check results.
The numbers. Their source. The limits of the claim.
TRW runs on its own codebase. We publish the operational evidence it produces—and keep that separate from outcomes we have not proven yet.
Patterns Discovered
4,000
Saved constraints and decisions. A usage count, not a measured improvement in task success.
Agent Actions Tracked
1,000
Tool calls, checkpoints, and deliveries captured across TRW runs in this repo.
Projects Using TRW
1
Projects reporting TRW installs via opt-in telemetry. When telemetry is unavailable, we show this repo’s own numbers — never invented ones.
Reported Workflow Score
—
Reported workflow-adherence signal, not code correctness or compliance.
Read the evidence at the right confidence level
Product telemetry is useful. It is not a substitute for an outcome study.
Evidence level 01
Confirmed in this repo
Requirements, checkpoints, build results, reviews, and delivery records are persisted as inspectable artifacts.
Evidence level 02
Observed and counted
TRW records recalled learnings and workflow events. The figures above come from live telemetry when available, otherwise a labeled repository snapshot.
Evidence level 03
Still an open question
Whether retained context improves task success across teams, models, and repositories requires controlled evaluation. We do not turn usage counts into that claim.
Open public beta · Free framework · No approval required
Your project. Your existing tools.
TRW is MCP-native and local-first. After installation, basic project-local use needs no mandatory hosted runtime. trw-mcp and trw-memory are source-available under BUSL-1.1.
| 1 | # Install or upgrade TRW in your project |
| 2 | curl -fsSL https://trwframework.com/install.sh | bash |
Local by default
Your project data stays local. Uploads are opt-in.
Inspectable local state
Run artifacts live under .trw/. Memory uses a local database with project namespaces and export paths.
Language-agnostic
Use your project-native checks and record their results. Client-specific hooks are optional adapters.
Common questions
AI writes code. TRW makes it engineering.
Start with the docs, create a free account, and keep requirements, verification, and learnings connected from one session to the next.
Open public beta · Free framework · Plain-file repo-local state