Keep the Why, OKF Agent Memory and RepoWise all address the problem of coding agents losing useful project context, but they assign memory different jobs. Keep the Why centers on preserving rationale; OKF Agent Memory structures durable knowledge and provides local retrieval; RepoWise derives a broader codebase-intelligence model with a reviewed decision layer. They are different approaches, not interchangeable implementations, and the best fit depends on what your team needs agents to remember and how that knowledge should be found and governed.
What job does each approach give project memory?
The distinction is more useful than treating all three as competing note-taking tools. Each starts from a different failure mode: forgotten reasoning, scattered knowledge, or insufficiently modeled codebase context.
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Keep the Why: preserve rationale that code does not explain
Keep the Why’s creator describes repository Markdown in a context/ directory as the durable record. The intended material includes why an architecture was chosen, which alternatives were rejected, why an awkward workaround remains, and what incidents or constraints shaped the code. The premise is that source code records what the system does, but may not preserve why the team chose it.
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#1 Best Overall
OKF Agent Memory: structure durable knowledge and retrieve it locally
OKF Agent Memory describes itself as a Git-native project-memory implementation based on OKF v0.2. Rather than focusing only on decision rationale, it organizes persistent project knowledge and documents local search and an MCP server over stdio, so compatible agents can query that knowledge through tool calls. Its repository lists an MIT license. Official OKF Agent Memory repository
Do not confuse the implementation with an official Google product. Its FAQ says Google Cloud published the OKF specification, while OKF Agent Memory is an independent implementation. The site lists release v0.6.0 and advertises an OKF Cloud private beta; release and beta details can change. OKF Agent Memory FAQ
RepoWise: derive codebase intelligence, then govern decisions explicitly
RepoWise models codebase information more broadly, with tools for code and repository context, risk, search, and decision rationale. Its documentation distinguishes an accepted decision from an unaccepted candidate: accepted decisions govern, while candidates are hints. The MCP documentation puts the distinction plainly: “A candidate governs nothing. A decision is a candidate a person accepted with repowise decision confirm.” RepoWise MCP documentation
That makes human review part of the decision model, rather than treating every inferred or proposed item as policy. RepoWise’s CLI documentation says confirmation requires a reason, scope, and evidence reference. RepoWise CLI decision documentation
Rank #3
- book
- A Guide to the Project Management Body of Knowledge (PMBOK Guide) – Seventh Edition and The Standard for Project Management (ENGLISH)
How do they store and retrieve what agents need?
The storage and retrieval model affects both day-to-day use and what happens as project memory grows. The comparison article describes Keep the Why as relying on ordinary repository and file search; OKF Agent Memory documents a structured knowledge corpus with local search and MCP tools; RepoWise uses a derived index and broader indexed retrieval, with MCP tools. The Keep the Why and cross-project architecture descriptions here are the creator’s account rather than independently verified product tests.
| Approach | Canonical memory or model | Retrieval described |
|---|---|---|
| Keep the Why | Markdown files in repository context/, according to its creator |
Normal repository and file search, according to its creator |
| OKF Agent Memory | Repository knowledge corpus using OKF v0.2 | Local search and MCP tools over stdio |
| RepoWise | Repository plus a derived codebase index; accepted decisions can be exported to a Git-tracked manifest, according to the comparison author | Indexed retrieval and MCP tools |
For a team weighing “What happens when the memory gets large?”, the important question is not just where notes live. Ask how agents locate relevant information, whether retrieval is explicit or indexed, and how people can inspect the underlying record. Repository Markdown keeps rationale visible in ordinary files; a structured corpus adds defined knowledge and local retrieval; a derived index aims to surface more kinds of codebase context. The cited materials establish these approaches, but do not provide a common scale test or comparative performance benchmark.
Rank #4
- Harvard Business Review Project Management Handbook: How to Launch, Lead, and Sponsor Successful Projects
- Harvard Business Review Press
- BLANK BOOK
How much authority does stored knowledge have?
Memory can be reference material, a search result, or a rule that constrains future work. The distinction matters: agents and developers need to know whether an item is merely informative or has been deliberately adopted.
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| Approach | Decision authority described |
|---|---|
| Keep the Why | Emphasizes deliberate capture of reasoning and rejected alternatives; the comparison does not describe a separate binding decision state. |
| OKF Agent Memory | Structures project knowledge; the cited materials do not establish an equivalent accepted-versus-candidate decision authority model. |
| RepoWise | Accepted decisions govern; candidates are hints until a person confirms them with a reason, scope, and evidence reference. |
If the team wants to represent, retrieve, compose, and govern durable knowledge for agents, separate those needs instead of assuming one feature solves all four. Knowledge organization and retrieval help an agent find material; an explicit review step answers whether an item should guide work as an accepted decision. The documentation supports that explicit distinction for RepoWise, but not a claim that the other two systems cannot be used alongside team review practices.
Best Value
What does the reported rejected-change experiment show?
The Keep the Why creator reports a controlled experiment involving a rejected simplification. Across 10 sessions without recorded rationale, 7 offered the already-rejected change as an option. Across 10 sessions with the rationale recorded, none offered it, and all 10 identified it as rejected. This is a project-author-reported result from 2026, not an independent replication or evidence that the same effect will occur across teams, models, or repositories. Keep the Why project site
Which approach should a team evaluate?
Choose based on the context your agents most often lose and the mechanism your team will actually maintain. These are fit-based implications of the documented scopes, not tested rankings.
- Evaluate Keep the Why if recurring mistakes come from forgotten rationale: why an architecture was chosen, why a workaround remains, or why an apparently simple change was rejected. Its creator’s described model makes intentional capture in repository Markdown central.
- Evaluate OKF Agent Memory if the need is a broader structured corpus of project knowledge, local search, and MCP access. Confirm the implementation and integration fit your agent setup; do not assume it is an official Google offering.
- Evaluate RepoWise if you want indexed codebase context across areas such as repository structure and risk, plus a decision layer where a person explicitly confirms what governs.
Before choosing, compare the systems against your actual workflow: what gets captured, who maintains it, how an agent retrieves it, what becomes authoritative, which integrations are required, and whether the license works for your use. RepoWise’s official CLI/business material describes its engine as AGPL-3.0 with a commercial license available; check the current terms before adopting it. RepoWise CLI documentation
At a glance
| Dimension | Keep the Why | OKF Agent Memory | RepoWise |
|---|---|---|---|
| Primary job | Preserve codebase rationale | Maintain structured durable knowledge | Derive codebase intelligence, including decisions |
| Knowledge access | Repository Markdown and ordinary file search, per creator | Local search and MCP tools | Indexed retrieval and MCP tools |
| Decision model | Deliberate rationale capture | Knowledge concepts; no equivalent authority distinction established in cited materials | Accepted decisions govern; candidates are hints |
| License in cited materials | Not independently verified | MIT, listed by the official repository | AGPL-3.0 engine; commercial license described in official CLI/business material |
No universal winner is established by these descriptions. For exact features, current release information, beta availability, and RepoWise licensing, consult the linked project documentation because those details can change.
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