GitMir vs Augment Code
Augment Code is built for retrieval quality across a large codebase. GitMir is built one layer above the code: what the product does, and what a change reaches in it.
The same repository, questions
and AI model for both.
Fifty questions in the words work is assigned in, the same model and settings for every system, answers graded blind.
Augment Code works with the code
and its sources. GitMir works
with the business logic.
Augment Code
Index everything the team has — code, history, docs, tickets — and give the model the most relevant slice per prompt.
Built around retrieval quality for large codebases: index everything the team has — code, history, docs, tickets — and give the model the most relevant slice. The context is assembled per prompt and inferred; there is nothing standing and inspectable that a person could review or a second tool could reuse.
GitMir
Features, rules, customer paths and how they connect, built from your code and kept current with every commit.
GitMir establishes what a product does once, from the repository, and serves each task only what it needs — with every statement traceable to the source it came from.
Context assembled per prompt is gone when the prompt ends. Nothing stands that a person can review, a second tool can reuse, or a commit can be checked against.
| Dimension | Augment Code | GitMir |
|---|---|---|
| Primary layer | AI Context | Meaning / Product |
| What it understands | Code, history, patterns, docs, tickets, knowledge | What the product does and how it behaves |
| Relationships | Cross-repo / service | Business + technical |
| AI agent context | Core | Established product knowledge |
| Change impact | Code-level | Product-logic level |
| Primary buyer | Developers / AI engineering | CTO / VP Eng / Product / AI |
Positioning per each vendor’s own public description. Nothing here says a tool is bad at what it is built for.
Keep Augment Code. Add the business logic.
Keep Augment for retrieval and give the agent the business logic as well: /with/augment shows the two running together.
Asked before choosing.
Keep Augment for retrieval and give the agent the business logic as well: /with/augment shows the two running together.
Benchmark 001: one repository, fifty questions in the words work is actually assigned in, the same AI model and settings for every system, answers graded blind. GitMir answered 92% correctly against 74% for Augment Code, on 8.4K tokens of context per question against 31.6K. The full method and every number are published.
Context assembled per prompt is gone when the prompt ends. Nothing stands that a person can review, a second tool can reuse, or a commit can be checked against. GitMir builds the business logic of the product once — features, rules, customer paths and how they connect — keeps it current with every commit, and gives the part a task touches to people and to AI.
GitMir vs Unblocked →GitMir vs Sourcegraph →GitMir vs Qodo →GitMir vs Greptile →