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TRW
Our Story

Built by the thing
we were building.

TRW started as a question: what if AI agents could actually learn from experience?

The origin

Feb 2025

Deep in a Claude Code session — building, breaking, rebuilding. Same patterns. Same mistakes. Every session started from zero.

The problem

Context vanished. Hard-won discoveries evaporated between conversations.

The hack

We started writing things down. Learnings files. Checkpoint notes. A rough framework to carry knowledge forward.

It worked

It was scrappy. But the agents stopped repeating themselves.

Then something unexpected happened. The framework started building itself. Each session used the learnings from the last. Quality compounded.

What took hours took minutes. The agents stopped repeating mistakes because the mistakes were recorded, scored, and surfaced automatically.

Learn
Build
Review
Remember
N → N+1

Session N teaches session N+1. The loop never stops.

The framework named itself

We didn't name TRW. The agents did. During an early session, the framework was asked what it was building toward.

The Real Work is not the code. It is the compounding knowledge that makes every line of code better than the last.

— The agents, when asked what they were building

The name stuck — because the agents were right.

There's something worth pausing on here. In philosophy, the act of naming is an act of identity — it's how a thing declares what it is and what it values.

When a system names itself, it demonstrates a form of self-reference that most software never achieves. TRW didn't just build itself using its own mechanisms — it articulated its own purpose.

The framework that compounds knowledge named itself after the principle of compounding knowledge.

We think that says more about what TRW is than any marketing copy could.

What it became

TRW is accumulated intelligence for AI agents. Not another wrapper or prompt library — a persistent layer that sits underneath your development workflow and compounds over time.

01Memory that persists. Learnings, patterns, and gotchas survive across sessions. Your agents start where they left off.
02Workflows that enforce quality. Six phases from research to delivery. Automated gates catch what humans miss.
03Teams that coordinate. Multiple agents working in parallel with shared context, task ownership, and structured handoffs.
04Requirements that trace. From feature request to shipped code, every decision is linked and auditable.

By the numbers

Live data from a framework built entirely by TRW agents.

0+

Tests

0+

Sprints

0+

PRDs

0

MCP Tools

Where we are

TRW is in private beta. We're small, intentional, and building in the open. Starting with Claude Code, TRW is expanding to support any AI coding agent.

A universal memory and workflow layer that works wherever your agents run. The memory system (trw-memory) has been extracted into a standalone package any AI tool can integrate — featuring hybrid retrieval (BM25 + dense vectors), a knowledge graph, and lifecycle management.

An adversarial auditing agent now probes every change for security vulnerabilities before it ships.

This page was built by agents using TRW to coordinate the work.

TRW is built by Tyler Wall — and by the agents that use it every day.

We're not trying to replace developers.

We're trying to make the tools they already use dramatically better at remembering, learning, and shipping quality code.

Ready to give your AI the same advantage?

TRW is in private beta. Free for individual developers.

Get Early Access — Free