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Yes, AI-assisted code can be submitted to the Linux kernel, but it does not receive a special fast track or a lower standard. The human contributor must understand and review every submitted change, verify that its licensing and SPDX metadata are correct, certify the Developer Certificate of Origin (DCO) with a personal Signed-off-by line, disclose meaningful tool assistance, and provide credible build, test, and reproduction evidence.
An AI system is neither a DCO signer nor an accountable substitute author. Kernel maintainers can request more detail, additional testing, or reject a patch when provenance, licensing, reviewability, or verification is inadequate.
Can you submit AI-generated code to the Linux kernel?
You may submit a patch that was produced or materially shaped with an AI coding assistant, provided it goes through the normal kernel contribution process. The deciding question is not whether a model was involved; it is whether a human contributor can stand behind the complete change and demonstrate that it meets kernel standards.
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesThe human submitter must be able to explain the design, identify what the tool generated, check the provenance of copied material, and correct errors introduced by the assistant. If you cannot understand the resulting code well enough to defend it during review, do not submit it. The Kernel Guidelines for Tool-Generated Content state the rule plainly: “If you are unable to do so, then do not submit the resulting changes.”
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| Question | Kernel-facing answer |
|---|---|
| Is AI assistance itself prohibited? | No. AI assistance follows the ordinary contribution and review process. |
| Can an AI agent sign the patch? | No. Only a human can certify the DCO and add Signed-off-by. |
| Does generated code automatically have an acceptable license? | No. The contributor must establish GPL-2.0-only compatibility and use accurate SPDX metadata. |
| Must every autocomplete suggestion be disclosed? | Not necessarily. Meaningful generated content should be disclosed; trivial mechanical assistance is generally outside the disclosure rule. |
| Can a maintainer require extra scrutiny? | Yes. Individual maintainers decide how to handle a contribution and may request more testing or explanation. |
Who owns the submission and who signs it?
Kernel process assigns legal certification and accountability to the human in the Signed-off-by chain. The AI Coding Assistants guidance says: “AI agents MUST NOT add Signed-off-by tags. Only humans can legally certify the Developer Certificate of Origin (DCO).”
Before adding your line, read the DCO requirements and confirm that you are entitled to submit the work under the stated terms. Your signature means you are accepting responsibility for the contribution, including work generated by a tool. Do not describe the model as the DCO signer, and do not imply that an automated system is a substitute author.
Attribution and legal authorship are separate questions. A patch can record which tools assisted its creation while the human contributor remains responsible for review and certification. That project-process rule does not answer every copyright question in every jurisdiction. If a model reproduces identifiable third-party code, or if your organization has unusual provenance or employment rules, escalate the issue through your legal process before submission.
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The AI Coding Assistants guidance requires all submitted code to be compatible with GPL-2.0-only and says to use appropriate SPDX license identifiers. The Linux kernel as a whole is GPL-2.0, while individual files can use compatible licenses or documented dual-license expressions where the project permits them.
Check the source file’s SPDX declaration
SPDX identifiers are precise, machine-readable declarations of a file’s license. Review every new or materially generated source file, not just the main implementation. An assistant can omit a header, copy an incompatible notice, or suggest an identifier that does not match the actual licensing terms.
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Use the identifier required for the file’s real license and the kernel’s established conventions. UAPI headers may use GPL-2.0 WITH Linux-syscall-note, which is not interchangeable with a generic GPL declaration. A dual-license expression must also be documented and intentional; never add one merely because a model suggested it.
Audit generated and copied material
- Inspect generated functions, comments, examples, and test data for recognizable material copied from another project.
- Check that any third-party snippet has a license compatible with the destination file and with kernel distribution.
- Remove model-inserted license text that is unsupported or inconsistent with the file’s existing terms.
- Make sure every affected file has the precise SPDX identifier expected by the subsystem.
There is no authoritative published percentage for how much Linux kernel code is AI-generated, and no reliable acceptance-rate statistic that can replace patch-by-patch licensing review. Treat provenance as an individual contribution question.
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The Kernel Guidelines for Tool-Generated Content apply when a meaningful amount of contribution content was not written by a person in the Signed-off-by chain but was created by a tool. That includes a chatbot-generated function, a complete source file generated by an assistant and then cleaned up by hand, a generated changelog, or a translated changelog.
Trivial spelling corrections, identifier completion, mechanical renaming, and formatting are generally outside the rule. Even in those cases, a short disclosure can help a reviewer understand how the patch was produced.
What a useful disclosure contains
Put the explanation in the cover letter and, where appropriate, the changelog. Include:
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- The AI assistants or other tools used.
- The prompts or input, or a concise summary when a session is too long to reproduce verbatim.
- The portions of the patch affected by the tool.
- The human review performed and the testing completed.
- Tools used for testing or analysis and anything that could not be tested.
Disclosure is not a waiver of review. It gives maintainers enough context to assess provenance and decide whether ordinary review is sufficient.
How should patch metadata identify assistance?
For meaningful AI or specialized analysis assistance, the AI Coding Assistants page gives this format:
Assisted-by: LLM [TOOL1] [TOOL2]Use the tag to record tool involvement, not to delegate responsibility. The human contributor still supplies the DCO sign-off and remains the person answerable for the patch.
Tools that may be listed
Specialized analysis tools such as Coccinelle, Sparse, Smatch, and Clang-Tidy may be listed when they materially assisted the work. An AI assistant that generated or substantially rewrote code should likewise be identified.
Tools that normally should not be listed
Do not treat routine tools such as Git, GCC, Make, or an editor as authors or special contributors. Those tools are part of ordinary development and do not, by themselves, represent meaningful generated content under the guidance.
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What testing evidence do maintainers expect?
An AI-assisted patch must meet the same technical bar as any other kernel change. Generated code is not evidence that the code works. Review the full diff, build the relevant configurations, run appropriate tests, inspect warnings, and be explicit about gaps.
For an ordinary generated change
- Read the complete patch, including comments, error paths, locking changes, data validation, and cleanup paths.
- Confirm that you can explain the interfaces and invariants affected by each hunk.
- Build the relevant kernel configuration and architecture targets for the subsystem.
- Run the subsystem’s available tests and exercise the new or changed path.
- Check for compiler warnings and static-analysis findings; resolve them or document why a finding is false.
- Record the exact configurations and tools used in the cover letter or changelog.
- State clearly what you could not build, run, or reproduce.
For an AI-assisted bug report or fix
The official procedure requires more than pasting a model’s diagnosis. Read the relevant process documentation, record the affected commit ID, and attempt to reproduce a non-trivial bug. Then write the fix, build and verify it, avoid build warnings, and run the kernel’s checkpatch.pl checks. Commit the change with a detailed message and an appropriate Fixes: tag, identify the relevant maintainers and mailing lists, and disclose anything that could not be built, tested, or reproduced.
Unverified reports may be ignored. The assistant must never send a bug or security report itself. The human reporter reviews the result, decides whether it is credible, and submits it through the normal kernel reporting process.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How maintainers evaluate an AI-assisted patch
Maintainers generally have to balance correctness with limited review time. Five practical decision points determine whether a generated patch is easy to review or likely to be delayed:
| Decision point | What a strong submission shows | What raises concern |
|---|---|---|
| Provenance and disclosure | Tools, affected sections, prompts or a useful summary, and testing details are identified. | The contributor cannot say what was generated or where copied material came from. |
| Human understanding and DCO | The submitter explains the design and provides a valid personal sign-off. | The patch treats the model as a signer or the submitter cannot explain key lines. |
| GPL and SPDX compliance | Every file has a defensible SPDX expression and compatible provenance. | License headers are missing, contradictory, or copied without verification. |
| Reproducibility and tests | A reproducer, build evidence, test results, warnings status, and limitations are stated. | The report relies on an unverified model claim or omits failed and unavailable tests. |
| Reviewability | The change is focused, the commit message is detailed, and the reasoning is understandable. | Large unexplained rewrites consume maintainer time without showing why each change is needed. |
A technically correct patch can still be rejected if the contributor cannot establish licensing compliance, explain the change, or provide credible verification. As the guidelines note, “individual maintainers have discretion to choose how they handle the contribution.” A maintainer may accept normal review, request additional testing, ask how the model was trained, seek a more detailed explanation, or decline the patch.
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A practical submission workflow
- Preserve provenance. Keep a record of the assistant, prompts or session summary, generated portions, and any external snippets considered.
- Review and rewrite. Read every line and simplify or replace code you cannot confidently explain.
- Resolve licensing. Remove incompatible material and add the correct SPDX-License-Identifier expression to each affected source file.
- Prepare the patch. Use the normal kernel commit format, include a detailed rationale, and add a
Fixes:tag when correcting a specific earlier commit. - Verify the change. Reproduce the issue when applicable, build the relevant targets, run tests and analysis, check warnings, and record limitations.
- Add attribution. Add an
Assisted-byline for meaningful AI or specialized-tool assistance. Do not add a tool-generatedSigned-off-by. - Certify personally. Add your own
Signed-off-byonly after confirming the DCO requirements and accepting responsibility for the entire contribution. - Submit normally. Send the patch, cover letter, and disclosures through the relevant maintainer and mailing-list process. Do not let an AI system communicate with maintainers autonomously.
Common mistakes and how to correct them
“The model wrote it, so the model is the author.”
Correct the attribution. Record tool assistance, but keep DCO certification and accountability with a human who reviewed the complete patch.
“The code compiles, so the licensing is fine.”
Compilation does not prove provenance or license compatibility. Audit copied material, confirm the intended license, and verify each SPDX expression.
“I only disclosed the assistant’s name.”
That is incomplete for meaningful generated content. Add the affected portions, prompts or a session summary, and the testing and analysis performed.
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“The assistant found the bug, so I forwarded its report.”
Do not forward an unverified model report. Attempt reproduction, inspect the commit history, build and test the fix, and submit a human-reviewed report through the normal process.
“I added every tool to the attribution list.”
Reserve Assisted-by for meaningful AI or specialized analysis assistance. Routine Git, compiler, build, and editor use does not need to be listed.
Quick Recap
Final pre-submission checklist
- I reviewed the entire patch and can explain every line.
- I checked generated and copied material for compatible provenance.
- Every affected source file has the correct SPDX license expression.
- I understand and satisfy the DCO requirements.
- My own
Signed-off-byis present; no AI agent signed it. - A meaningful AI or specialized-tool contribution is identified with an
Assisted-byline. - The cover letter or changelog describes tools, prompts or summaries, affected sections, and testing.
- For a bug fix, I attempted a reproducer, built and tested the fix, checked warnings, used the required patch checks, and added a detailed message and
Fixes:tag where appropriate. - I stated what I could not build, test, or reproduce.
- The submission will be sent through the normal maintainer and mailing-list process by a human.
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