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Greptile Signals

What engineering leaders and their teams report about Greptile, with every finding tied to its evidence.

Read the findings

What the evidence says

Whose sources count

Practitioner sentiment, leaders and teams

+40 Positive from 20 sources that take a side

How this figure is made

Positive overall signal, net 40 points

From 20 authors in 18 discussions. Small sample. Run a pilot on live pull requests to measure which comments engineers act on and which they dismiss.

Analyzed
66 total sources
Top praise
Bug Detection (8 of 8 sources) See praise evidence
Top concern
For engineering leaders and teams, no concern theme reaches 5 sources from 3 authors.

Mar 2025 to Oct 2026.

48 sources from practitioners, by month and sentiment.

Team and leadership accounts mostly keep Greptile. Eleven kept it, including Brex, which aligned on Greptile as its one agentic reviewer, and PostHog, which kept it while retiring CodeRabbit. Five ended a trial or moved to Codex, Cursor's Bugbot, Claude, or CodeRabbit. Every team account about bug detection reports real catches, including two serious bugs in an Appwrite pull request. Teams use Greptile before human approval. On comment noise, two team accounts raise it, and two, Brex's CTO among them, find the noise acceptable.

Positive, mixed and negative sources

The score counts each source once, as the split does. See How the numbers work.

See the evidence

Below: 1 praise theme, 1 point of agreement and 2 disagreements.

Findings

Counted for Engineering leaders and teams, from 20 sources. Change group

What practitioners praise

Every capability practitioners describe positively, ranked by how many sources say so. Open one to read who said it.

  1. Bug DetectionAll 8 sources on it praise itReal bugs Greptile catches in pull requests, including logic errors and regressions.

    Counted for Engineering leaders and teams.

    1. Positive

      Torsten Dittmann, product architect at Appwrite

      Don't approve while a bug finding is open, and re-check approvals after new commitsGitHub issue

      On an Appwrite pull request, Greptile found two serious bugs that the author confirmed and fixed, after the author's own reviewer, Hansi, had approved the change and later missed one of them.

      Published Oct 6, 2026self-described: Appwrite's appwrite/appwrite pull requests, where the author compares a self-built reviewer, Hansi, with Tenki and Greptile

    2. Positive

      Contributor to pomerium/agentops

      Platform stack: Greptile findings left after five review roundsGitHub issue

      Pomerium's agentops stack went through five Greptile review rounds, each fixed test-first. The issue lists the concurrency and error-handling findings still open, such as queued startup errors that are dropped and retries that outlast a token.

      Published Oct 6, 2026self-described: Pomerium's agentops repository, a stack of 12 pull requests reviewed by Greptile

    3. Positive

      Luca Marturana, Chief Architect at Spark

      [Technical] Code reviews at Spark: What we changed after AICompany blog post, SparkNotes (Spark)

      Spark's Chief Architect reports that the team uses Greptile to catch bugs in review and that it has caught both large and small ones, such as an unhandled business-logic edge case and a missing data migration step. Style rules run through an in-house Claude Code agent, and humans review design documents, data models and customer fit.

      "We leverage Greptile for the former; in our experience, it has been very good at catching bugs big and small, such as an edge case in the business logic we forgot to handle, or a data migration step we forgot to add."
      Excerpt, Luca Marturana

      Published Sep 9, 2026self-described: Spark, early-stage energy software company; agents write most code, Claude Code style agent beside Greptile

    4. Positive

      Sherwood, founder of Sazabi (X profile)

      Post by @shcallawayX post

      After trying Bugbot, Graphite, CodeRabbit, Codex and others, calls Greptile their favorite reviewer and says it rarely lets a bug or regression through.

      Published Sep 8, 2026self-described: Sazabi engineering team

    5. Positive

      Andrew Churchill, CTO of Weave

      3 things top 1% teams do differentlyNewsletter guest post, Manager.dev

      Weave's CTO runs Greptile with Cursor Bugbot and Cubic on every pull request because each catches bugs the others miss, and treats a PR with no meaningful bot comment as free of obvious bugs. Human review now goes mostly to plans and to sensitive areas such as infra.

      "We use three different ones: Cursor Bugbot, Cubic and Greptile. Each of them catches some stuff that the other ones don't, and as long as that is true, it is worth it to us to have 3 of them."
      Excerpt, Andrew Churchill
      "If there is no meaningful comment from any AI bot, we can be pretty confident there are no obvious bugs in it."
      Same speaker

      Published Jul 28, 2026Weave engineering team; three AI reviewers on every PR, about 5% of PRs get a human review

    6. Positive

      James Reggio, CTO at Brex

      Full Story of Brex’s AI Hail MaryPodcast episode show notes and transcript, Latent Space

      Brex aligned on Greptile as its one agentic code review tool on top of traditional linters. Its CTO singles out the signal-to-noise ratio of its pull request comments and says he never regrets reading all 65 comments it leaves on his diffs.

      "According to James, what is most impressive about Greptile is their signal to noise ratio of comments left on a PR, “I never regret going through all 65 comments [Greptile] leaves on my diffs because it catches so many things.”…"
      Excerpt, James Reggio

      Published Jan 17, 2026Brex, about 300 engineers; traditional linters plus Greptile for agentic code review

    7. Positive

      James Hartig, software engineer at Admiral (HN profile)

      Comment on: Why Greptile just does code reviews and doesn't also generate codeHacker News comment

      Their employer uses Greptile. It is sometimes overzealous but usually catches real issues, so authors fix them before a human reviews the pull request.

      Published Aug 4, 2025self-described: Admiral, engineering team

    8. Mixed

      disillusionist, Hacker News commenter

      Comment on: There is an AI code review bubbleHacker News comment

      After a several-week trial against Cursor, their company declined to buy Greptile. Developers were split, and it overwrote PR descriptions and argued with itself in comments.

      Published Jan 26, 2026self-described: Employer engineering team, evaluating against Cursor

    Open them in the record

What concerns them

Every concern practitioners raise, most raised first.

For engineering leaders and teams, no concern reaches 5 sources from 3 authors.

    Where the evidence agrees

    Statements this group's sources agree on, then the ones close to agreement.

    1. Strong agreement

      Greptile identifies issues before human review. People still judge the change and approve it.

      9 supporting sources

    Where it disagrees

    Questions the sources split on, with the count on each side.

    • Evidence remains mixed

      After a trial or a price change, do teams keep Greptile?

      • Kept it, 11 sources

        These users keep Greptile on every pull request for its bug catches and 5/5 score.

      • Dropped it, 5 sources

        These users ended trials or canceled because of noise or per-review prices. Others preferred another reviewer.

    • Evidence remains mixed

      Against other AI reviewers tried hands-on, does Greptile come out ahead?

      • Prefers Greptile, 2 sources

        These users chose Greptile after trying Copilot, Cubic, Bugbot, CodeRabbit, or Codex.

      • Prefers another reviewer, 5 sources

        These users switched to Cursor's Bugbot, Codex, Claude, CodeRabbit, or their own reviewer.

    The evidence

    Whose experience this is

    The three groups, then every practitioner by the context they work in, and how emphasis changes with scale.

    Three groups drawn from the same sources. Choose a group to select whose experience counts. Within that group, each author counts once in the practitioner sentiment, with their latest view. Signals open on Engineering leaders and teams.

    • Engineering leaders and teams

      20 sources. These accounts focus on how team trials end, review quality on shared repositories, billing administration, and how Greptile compares with reviewers teams already run.

    • Individual builders

      28 sources. These accounts focus on spend, comment quality on personal and open source repositories, and how Greptile fits a coding agent loop.

    • All practitioners

      48 sources. This gives the broadest read, but combines work settings that can reach materially different conclusions.

    48 sources from practitioners, by the context they work in. Filled rows count for this group.

    1. Individual practitionerSolo developers and open source maintainers28 sources

      Emphasizes Bug catches, workflow fit, and comment noise

    2. Very small team2 to 10 engineersNo sources from this setting yet
    3. Professional team11 to 50 engineers, or a named company's team11 sources, counted here

      Emphasizes Reviewer trials and noise, plus spending alerts

    4. Technical leadershipLeaders setting adoption across teams7 sources, counted here

      Emphasizes Reviewer comparisons and subscription decisions

    5. Organization-wideEnterprise or company-wide rollout2 sources, counted here

      Emphasizes Brex and PostHog keeping Greptile on their main codebases

    What changes with scale. Individual builders discuss Greptile's bug catches and workflow integration, alongside noise and cost. Team and leadership accounts focus on trial purchase decisions and visibility into per-review spending. Most compare Greptile with Codex, Cursor's Bugbot, Claude, or CodeRabbit.

    Where the sources come from

    Where this group's sources were published.

    Counted for Engineering leaders and teams, from 20 sources. Change group

    38 sources for this group, 18 of them documentation

    • Product Documentation18, 47% of 38 sources
    • Developer Communities15, 39% of 38 sources
    • Independent Reviews3, 8% of 38 sources
    • Talks & Podcasts2, 5% of 38 sources

    GILD retains older evidence that still applies. Accounts tied to changed billing, limits, or product versions carry Needs a recheck.

    See sources by origin

    The record

    Who each source is, how it knows, whether it still applies and what it counts toward.

    About this read

    What changed, and how we count

    What changed

    • Every Greptile account links to its public page and records the author and publication date.
    • A finding shows only when at least 5 sources from 3 different authors discuss it. Disagreements require at least 2 sources on each side.
    • Configuration comes up firsthand in 3 accounts, among them PostHog retargeting Greptile's skip label and a maintainer who stopped reviews on every push to save quota. Two G2 reviewers report slow reviews, one of them on large pull requests. Both themes stay under GILD's 5-source minimum. Before a trial, teams with data-residency rules should read Greptile's security page and deployment options and ask for its retention terms in writing. The reviewed accounts do not cover firsthand data handling or self-hosting.
    • GILD excluded 12 X posts from March and April 2026 gathered from a pricing-complaint compilation. It added Hacker News comments and named G2 reviews collected without regard to sentiment.
    • GILD keeps English-language accounts by named practitioners from 2025 onward. The October 2026 cleanup removed 3 engineering posts that failed the source standard and a pseudonymous DEV Community comparison. It added 9 sources, including 6 GitHub issues with team accounts from Pomerium, Appwrite, Brite Nites, deftai, and Youtab. The additions also include 2 Hacker News comments and a developer's blog post.
    • GILD checks each documentation page against Greptile's current docs.
    • Oct 25, 2026: added GitHub Workflow Friction from what existing accounts state: 2 teams raise Greptile comments and checks that broke their merge gates.
    • Oct 25, 2026: added 3 sources from outside Hacker News. They are Brex CTO James Reggio on the Latent Space podcast, PostHog's pull request keeping Greptile while retiring CodeRabbit, and Paperclip's cofounder on the Open Source Ready podcast.

    Method

    A running review of what engineering teams report about Greptile, from individual builders to company-wide rollouts. Each finding links to its sources, and each conflict shows both sides.

    Counts cover only the sources GILD reviewed.

    Who counts

    Engineering leaders and teams
    Very small team, Professional team, Technical leadership, Organization-wide
    Individual builders
    Individual practitioner
    All practitioners
    Everyone in the leaders and teams and individual builders groups

    Choose a group to select whose experience counts. Within that group, each author counts once in the practitioner sentiment, with their latest view. GILD files each source in a group from how the account describes its author. A role or employer marked self-described is what the source states about themselves. Documentation checks facts for every group and never counts toward sentiment.

    How the numbers work

    • Overall signal. Positive votes minus negative ones, per 100 votes from the sources that take a side. Each author counts once, with their latest view, whoever they are and wherever they posted. The older weighted reading, where accounts GILD matched to a named person count three times when GILD lists the author among engineering leaders and twice otherwise, is shown beside it as a second view. Where an author wrote more than one source, the line beside the split gives the votes, one per author, so the score follows from it. When one author's sources from the same day disagree, that author counts as mixed, and a half point rounds away from zero. Sources with no opinion are listed and not counted. Strong positive is +50 or higher, positive +20 to +49, mixed −19 to +19, negative −20 to −49, strong negative −50 or lower.
    • Weighted reading, second view. Counted the older way, where an account GILD matched to a named person counts two or three times, leaders and teams read +59 strong positive (method sentiment/S1). GILD printed that number as "GILD score" until October 29, 2026; most of those matches rest on a name or a self-described role.
    • Method change, Oct 30, 2026. GILD changed how practitioner sentiment counts, to one vote per author. Weighted, it read +59 Strong positive; with one vote per author it reads +40 Positive. No evidence changed.
    • Unscored. A group gets a score only with 20 sources from 15 authors. Below that, one source moves the score about 5 points, so the read says "Unscored until 20 sources from 15 authors" and shows its counts.
    • Independence. A source whose author works for the vendor, for one of its partners or programs, or for a competitor, and a page the vendor published or ran, is listed with that tie and counts toward nothing. One author counts on at most two records per product. The line under the score says how many authors and how many separate discussions the counted sources come from: comments in one thread are one discussion.
    • Praise and concerns. How many of the sources that discuss a theme praise it or raise it.
    • Consensus. A statement joins when 20% of the group's sources support it and fewer contradict it. Contradicting sources are counted separately. Below that line a statement shows as building. At 40% or more it reads Strong agreement; below, Recurring point.
    • Disagreements. The count on each side. GILD names no winner and gives no share of all users.
    • Minimum evidence. A finding needs 5 sources from 3 authors; a disagreement also needs 2 on each side. Smaller counts stay in the table below, marked under the minimum.

    Labels on a source

    A source's date and whether it still applies are separate: a recent post can describe an old version, and an old one can still hold.

    Documented
    Stated in official documentation.
    Reported
    A practitioner's account of their own use.
    Measured
    Backed by the source's own measurements, such as a comparative test or tracked team metrics.
    GILD analysis
    GILD's check of a claim against official documentation.
    Current
    Describes the product as it is now.
    Still applicable
    Older, and the behavior or lesson still holds.
    Needs a recheck
    May depend on a plan, version or setting that changed since it was written. It keeps counting until GILD rechecks it, since the rest of the account usually holds, and its card says so.
    Out of date
    No longer accurate. Kept in the record; counts toward nothing current.

    Flagged for a recheck, of the sources that take a side: leaders and teams 0 of 20, individual builders 0 of 26, all practitioners 0 of 46.

    Limits

    • GILD reviewed 48 public sources from people using Greptile. They comprise 22 Hacker News comments, 9 GitHub issues, 1 GitHub pull request, and 4 X posts. Another 6 are named reviews among the 10 newest G2 reviews on Greptile's AWS Marketplace listing. The list also includes 2 podcast episodes, 2 personal blog posts, and 2 company and newsletter posts. The counts do not establish prevalence among all Greptile users. GILD excluded 12 X posts from March and April 2026 collected from a compilation of complaints about March 2026 pricing. That collection selected only complaints. Undated Greptile customer stories do not count as Signals. A GitHub bug report counts as mixed unless its author drops Greptile or recommends against it. Of the included sources, 20 describe a team or its leaders.
    • Few accounts identify a Greptile version or plan. Cost accounts after March 2026 describe the per-review pricing introduced that month, US$30 per developer with 50 reviews, then US$1 per review. By October 28, 2026, Greptile's pricing page listed Pro with no seat fees and credits at US$1 each.

    Every count, and the sources behind it

    13 findings for 3 groups

    Each row opens its sources for the group you are reading.

    FindingEngineering leaders and teamsIndividual buildersAll practitionersSources
    Current readCurrent sentiment11 positive, 6 mixed, 3 negative14 positive, 5 mixed, 7 negative25 positive, 11 mixed, 10 negativeSources
    PraiseBug Detection8 of 8 positive5 of 7 positive13 of 15 positiveSources
    PraiseCodebase Context0 of 1 positive (under the minimum)6 of 7 positive6 of 8 positiveSources
    PraiseSummaries & Confidence Scores2 of 4 positive (under the minimum)0 of 1 positive (under the minimum)2 of 5 positiveSources
    PraiseWorkflow Fit2 of 4 positive (under the minimum)6 of 6 positive8 of 10 positiveSources
    ConcernComment Noise2 of 4 raise it (under the minimum)7 of 10 raise it9 of 14 raise itSources
    ConcernPricing & Billing0 of 0 raise it (under the minimum)4 of 6 raise it4 of 6 raise itSources
    ConcernMissed Issues1 of 1 raise it (under the minimum)1 of 1 raise it (under the minimum)2 of 2 raise it (under the minimum)Sources
    ConcernGitHub Workflow Friction2 of 4 raise it (under the minimum)0 of 0 raise it (under the minimum)2 of 4 raise it (under the minimum)Sources
    ConsensusA first pass before human review9 supporting7 supporting16 supportingSources
    DisagreementAfter a trial or a price change, do teams keep Greptile?Kept it 11, Dropped it 5Kept it 5, Dropped it 3Kept it 16, Dropped it 8Sources
    DisagreementAgainst other AI reviewers tried hands-on, does Greptile come out ahead?Prefers Greptile 2, Prefers another reviewer 5Prefers Greptile 2, Prefers another reviewer 4Prefers Greptile 4, Prefers another reviewer 9Sources
    Current readEvidence mix38 sources46 sources66 sourcesSources

    Fact checks

    GILD's checks of claims against official documentation, kept apart from the source counts.

    • Comment Noise. Greptile documents strictness from 1 to 3 and comment types, plus ignore patterns in .greptile/config.json or greptile.json. It learns from team replies and reactions. Most noise reports do not state the settings their authors used. One G2 reviewer reports noise on large pull requests falling as the team trained Greptile with reactions, so set strictness and comment types before judging a trial. Controlling nitpickiness, checked Oct 12, 2026
    • Pricing & Billing. As GILD read the billing page on October 12, 2026, before the change: the Flex Usage Limit in Organization Settings skipped reviews that would incur flex charges once projected spend reached the cap, and cancellation ran through the Billing Portal under Settings, Billing. On October 28, 2026 the page bills prepaid credits instead, and new reviews pause when they run out unless automatic recharge is on. Billing, checked Oct 12, 2026