1
Map for zero tokens
Codna builds a dependency and blast-radius graph deterministically — no LLM, no embeddings, ~60ms per repo. It is exact, and it reflects the code as it is right now, not as it was at the last index.
Comparison
Codna vs Devin
Devin runs the whole job for you, end to end. Codna does one part with certainty: it maps the repo deterministically for zero tokens, then ships only fixes your own tests pass. Use it to make whatever agent you run surgical.
The problem
How Devin understands your repo
Devin is a full autonomous software engineer. It spins up a VM, plans the task, edits, runs commands, and opens a PR. To navigate a codebase it leans on Codemaps and DeepWiki — an LLM reads your repository and writes a description of it: architecture diagrams, execution flow, component relationships, re-indexed every couple of hours. That description is genuinely useful for humans, and it gives the agent context. But it is a model's account of the code, generated with tokens and refreshed on a clock — not a precise, current map of what actually depends on what. Billing is ACU-based: $20/mo plus $2.25 per Agent Compute Unit, Team at $500/mo for 250 ACUs (Cognition, retrieved 2026-06). You pay for the compute the agent spends understanding before it acts.
How Codna fixes it
How Codna scopes the same fix
Whole repo100,000+
Evidence bundle~600
2
Hand over evidence, not the repo
The agent receives a ~600-token bundle: suspect files, call paths, the failing test. No model spends tokens describing the codebase before work begins.
3
Verify before it ships
Every patch must pass your existing test suite. A fix that fails tests never ships — the test is the gate, not a model's confidence.
codna fix . --issue "the checkout test is failing"
What you get
Why teams pair Codna with Devin
A map that's derived, not described
Codna builds an exact dependency and blast-radius graph deterministically in ~60ms per repo for zero tokens — no LLM, no embeddings, no clock-based re-index. Where Devin's Codemap is a model's account of the code refreshed on a clock, Codna's map is current the moment you run it.
Every fix gated by a passing test
A patch is only proposed if your existing test suite passes — the test is the gate, not a model's confidence. That turns an agent's reasoning into a verified change instead of a plausible one.
Yours to run, on your terms
Codna is bring-your-own-key, model-agnostic, and self-hostable with fail-closed egress, and it never trains on your code. It ships three ways — CLI, MCP server, and native GitHub App — so it scopes the agent you already run rather than locking you into a cloud.
The proof
Fewer tokens. Faster. Verified.
Frequently asked
No, and that is the point. Devin is a cloud-hosted autonomous software engineer that runs the whole task end to end, billed by usage. Codna is the precision and verification layer underneath: deterministic repo mapping plus a test-verified fix gate. Pair it with Devin or any agent through the MCP server.
A Codemap is an LLM's description of your repo, generated with tokens and re-indexed every few hours. Codna's map is computed deterministically in ~60ms for zero tokens, and it is current at the moment you run it — no model, no staleness window. One describes the structure; the other is derived from it.
Yes — that is the intended setup. Codna is not an agent replacement; it exposes an MCP server, a CLI, and a native GitHub App, so it can hand any agent a ~600-token evidence bundle and gate the result on your tests. Use it to make whatever agent you run more surgical.
Codna is model-agnostic through bring-your-own-key, so you choose the model or use a managed option. The deterministic understanding layer is language-broad: 130 repos across 110 languages were mapped in 9.2 seconds at 100% ecosystem accuracy, for zero LLM tokens.
Devin is a cloud-hosted service that runs the agent on its own infrastructure. Codna is bring-your-own-key and can run fully self-hosted with fail-closed egress, and it never trains on your code — the deterministic map runs locally for zero tokens.
Devin bills by usage at $20/mo plus $2.25 per Agent Compute Unit, so you pay for the compute the agent spends understanding before it acts (Cognition, retrieved 2026-06). Codna does that understanding for zero tokens and fixes from a ~600-token evidence bundle — about $0.04 per verified fix at public model rates.
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