Turn the production signal into a change engineers can review
Prilog is built for teams that want production failures to lead to proposed code fixes with less manual investigation and assignment. Connect the source repository, bring error evidence, and let Prilog investigate and prepare a change. Project automation can take an eligible generated fix through to a pull request, with engineers controlling review and merge.
Datadog Bits Code also documents automated code fixes. If you already use Datadog, it is an option to compare against Prilog on the same failures. Prilog is particularly worth evaluating when you want to start from different evidence sources, existing OpenTelemetry, a selected log file, or a supported public GitHub issue.
This article is published by Prilog. Product descriptions were checked on October 25, 2026; no comparative performance trial is claimed.
What Datadog Bits Code offers
Datadog's Bits Code documentation describes diagnosis, code changes, pull or merge requests, and iteration using CI logs and developer feedback. Automations can run on a schedule or respond to supported product findings. The documentation also states that Bits Code does not auto-merge PRs or MRs.
The useful question is how the workflow fits your telemetry, repositories, review process, and budget.
Compare inputs, automation, and cost
| Decision | Prilog | Datadog Bits Code |
|---|---|---|
| Starting point | Connected production source, OTLP, uploaded error logs, or supported public issue import. | Datadog findings, investigations, prompts, and supported product integrations. |
| Proposed changes | Repository-aware investigation and generated patches, with configured PR publication. | Code changes and PRs or MRs with CI and developer-feedback iteration. |
| Ongoing operation | Continuous evidence ingestion plus project analysis and action settings. | Scheduled or signal-triggered sessions and configurable outputs. |
| Pricing reference | $8 per publishable fix and three free publishable fixes in the current offer. | Consult current Datadog AI Credits terms and the products needed for your workflow. |
See current Prilog pricing and the Datadog setup guide before comparing total cost. A publishable fix is not a guaranteed maintainer merge.
Keep your OpenTelemetry investment
Your application may already export useful logs and traces. Prilog accepts OTLP HTTP/protobuf and HTTP/JSON for those signals, so a compatible SDK or Collector can add Prilog as a destination. You still need the repository connection, service identity, and enough failure context to investigate the code.
Follow OpenTelemetry to pull request for the transport, correlation, and review steps. Telemetry ingestion and automatic PR publication are configured separately; use the automation guide to confirm your project's behavior.
Compare speed and quality together
Prilog's published product metric is a five-minute average fix time. For a practical evaluation, record how long it takes to reach a useful patch, which checks ran, whether the patch reproduces and fixes the original behavior, and how much a reviewer changes. The average does not establish an under-five-minute guarantee for every issue or time to deployment.
Prilog's reported 91.2% SWE-bench Verified result (456/500) is additional evidence about the issue-solving engine. It uses feedback-guided selection: 413 prior passing patches are retained and 87 cases are regenerated. The open submission is self-reported and not pass@1 or a comparison with Bits Code. The evaluation page explains the method and artifacts.
Giving back through open-source fixes
We contribute fixes to open-source projects at no charge as part of our community work. Inspect the merged Newt connection-state fix and Prefect dependency compatibility fix. Their public review histories let you judge specific changes; they do not establish every generated patch's quality or the level of human involvement.
For your own trial, retain unsuccessful outcomes alongside accepted fixes. Measure reviewer minutes, extra edits, cost, and recurrence after deployment. This gives the team a basis for increasing automation across services.
Start with one service
Open Prilog, connect a repository, and follow the quickstart. Read the detailed Datadog comparison or compare Sentry Seer, Resolve AI, and Superlog.
