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Devin Signals

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

Read the findings

What the evidence says

Whose sources count

Practitioner sentiment, leaders and teams

+39 Positive from 24 sources that take a side

How this figure is made

Positive overall signal, net 39 points

From 23 authors in 23 discussions. Small sample. Use a task pilot to measure accepted work and review time.

Analyzed
84 total sources
Top praise
Codebase understanding (11 of 11 sources) See praise evidence
Top concern
Requires strong review (7 of 8 sources) See concern evidence

Jan 2025 to Oct 2026.

63 sources from practitioners, by month and sentiment.

Leader and team accounts lean positive. All 11 that discuss codebase understanding praise it, as do all 8 discussing ticket delegation. Review is their most frequent concern. 7 of the 8 who discuss it say Devin's pull requests need heavy review, and they split 4 to 3 on whether Devin saves time once review is counted.

Positive, mixed and negative sources

The score counts them as 13 positive, 6 mixed and 4 negative votes, one per author. See How the numbers work.

See the evidence

Below: 5 praise themes, 2 concerns, 1 point of agreement and 2 disagreements.

Findings

Counted for Engineering leaders and teams, from 28 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. Codebase understandingAll 11 sources on it praise itReading, searching, and explaining an existing repository, including through Ask Devin and DeepWiki.

    Counted for Engineering leaders and teams.

    1. Positive

      David Griffiths, Group Head of AI at Citi

      A Competitive Differentiator: David Griffiths on Building the World's Most AI-empowered Financial InstitutionCompany perspectives article, Citi

      Citi's profile of its Group Head of AI says the bank adopted Devin early to speed up complex, multi-step coding tasks. One task re-mapped more than 30 years of legacy code across the firm in two days.

      "Early on, Citi adopted Devin, a coding agent developed by the AI lab Cognition to expedite complex, multi-step coding tasks. One such task involved re-mapping more than 30 years of legacy code across the firm in two days."
      Excerpt, David Griffiths

      Published Sep 22, 2026Global bank; firmwide AI platform team serving employees in more than 87 countries and jurisdictions

      Practitioner account, self-described; ran the rollout; counts toward Delivered outcomes

    2. Positive

      Prashant Naikar, Developer at a startup acquired by a UK company

      Using Devin AI Daily for 6 Months: What Actually ChangedPersonal blog post, Medium

      After six months of daily use, Prashant Naikar's work shifted to reviewing Devin's pull requests and teaching it the product. Devin navigated the codebase well but missed edge cases and coupling.

      Published Feb 6, 2026self-described: Company-wide AI push after acquisition; manager gave Devin access to two developers

      Practitioner account; direct use; counts toward Delivered outcomes

    3. Positive

      joshgachnang, Hacker News commenter

      Comment on: Devin Review: AI to Stop SlopHacker News comment

      joshgachnang is impressed with Devin, calling it the best tool for AI-generated features when you know what you want and have patterns to follow, likely helped by its project context.

      Published Jan 21, 2026self-described: Team codebase with its own review rules; using Devin for features and review

      Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account

    4. Positive

      nikisweeting, Engineer at browser-use

      Comment on: DeepWiki: Understand Any CodebaseHacker News comment

      DeepWiki was instrumental in the browser-use team's refactor of a large codebase from Playwright to pure CDP; nikisweeting rates its follow-up research questions above OpenAI deep research for complex codebases.

      Published Aug 26, 2025self-described: browser-use, refactor of a large codebase from Playwright to CDP

      Practitioner account, pseudonymous; opinion; not counted, takes no position

    5. Positive

      Zach Davis, Director of engineering at LaunchDarkly

      Successfully coding with AI in large enterprises: Centralized rules, workflows for tech debt, & morePodcast episode, How I AI (YouTube)

      Davis consolidated Cursor rules and a Claude MD file into one in-repo agents directory, started from Devin's per-repo wiki to write docs, got Devin running in front-end-only mode before a colleague set up the back end, and can Slack Devin to pick up the next tech-debt cleanup task.

      "…for anybody trying to deploy AI agents in a real engineering team with a real codebase, not just vibe coding. We have Zach Davis, director of engineering at Launch Darkley, who's going to show us how he sets up centralized rules and…"
      Transcript excerpt, at 1:12Partial support

      Published Jul 21, 2025self-described: LaunchDarkly, 100-plus-person engineering team working in a large, roughly 10-year-old monorepo

      Practitioner account, self-described; ran the rollout; counts toward Delivered outcomes, Adoption and upkeep

    6. Positive

      Rick Blalock, co-founder at Agentuity

      The Agent-Native CompanyConference talk page with transcript, AI Engineer World's Fair 2025

      Blalock reports that it is really common at Agentuity standups to have Devin take on a task, with a pull request to review before the meeting ends. A few months in, Devin has documented so much of the company's code and knows how the team handles certain things; Blalock calls it a superpower.

      "We started using it a few months ago. It was good. We had to do some things. And now over time it's learned so much, it's documented so much of our code, it knows how we handle certain things."
      Excerpt, Rick Blalock
      "During a team meeting, it's really common to hear things like, "Well, just have Devin go do that."…"
      Same speaker

      Published Jun 3, 2025Agentuity, an early-stage agent cloud startup of six or seven people

      Practitioner account, self-described; direct use; counts toward Delivered outcomes

    7. Positive

      Zachary Proser, Applied AI at WorkOS

      Devin AI Has Come a Long WayPersonal blog post, zackproser.com

      WorkOS abandoned a 2024 Devin trial with zero completed sessions; by 2026 it became a daily, organically adopted Slack agent shipping reviewable PRs, bug fixes and data queries.

      Published May 24, 2026self-described: WorkOS engineering team using Devin in Slack; also personal blog repos

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Adoption and upkeep

    8. Mixed

      Hiroki Akamatsu (@hi120ki), AI Security engineer at Mercari

      Enabling AI usage at Mercari with Secure Devin ManagementEngineering blog post, Mercari Engineering blog

      Mercari's AI Security team built a Terraform provider and automation on Devin's Enterprise API to manage members, ACU caps, secret rotation and API key expiry that Devin lacks natively.

      Published Apr 3, 2026self-described: Mercari, Devin Enterprise with separate Organizations per team across multiple business domains

      Practitioner account; ran the rollout; counts toward Operational control, Cost predictability and limits, Adoption and upkeep

    9. Positive

      Eight Sleep data team (Editorial byline)

      How Eight Sleep Uses Devin as a Data AnalystCompany blog post, Eight Sleep blog

      Eight Sleep runs Devin in Slack as a data analyst over its dbt repo and warehouse; with curated knowledge it ships 3x more data work and clears ad-hoc asks.

      "Faster shipping. We’re shipping 3x as many data features and data investigations each week compared to before…"
      Excerpt, Eight Sleep data team

      Published Sep 4, 2025self-described: Eight Sleep small data team; dbt, Snowflake, Looker, Amplitude; Devin used as a data analyst, not for app code

      Practitioner account, self-described; ran the rollout; not counted, tied to the vendor

    10. Mixed

      Daniel Price, docs team at Neon

      AI Workflows for Docs: Putting Devin to WorkCompany blog post, Neon

      Neon's docs team uses a Devin playbook to set up the weekly changelog, sends it to work through older docs issues and small UI copy fixes, and has it explain code. A feature rename left awkward edits that took 20+ manual commits, and open-ended tasks often failed silently, so Cursor stays their interactive tool.

      "Devin does well when the problem is clearly scoped, but once things get open-ended, it still struggles."
      Excerpt, Daniel Price
      "But its edits leaned heavily on direct find/replace, which led to some awkward constructions like “instant instant restore.” It took another 20+ manual commits to polish the changes."
      Same speaker
      "But when the task is clear and the scope is right, it’s a genuinely helpful assistant."
      Same speaker

      Published Jun 23, 2025Neon docs team; docs repo, changelogs and small Neon Console UI fixes

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability

    11. Mixed

      Vikram Sreekanti and Joseph E. Gonzalez, RunLLM

      One month of using DevinNewsletter, The AI Frontier (Substack)

      Sreekanti and Gonzalez found Devin effective on hour-sized fixes that took 1-5 ACUs (US$2-10). A full-stack task they expected a junior engineer to finish within a day was beyond it, and 2 of the 3 bigger tasks, averaging about 20 ACUs, gave no usable results.

      "The 3 bigger tasks we tried averaged about 20 ACUs and 2 of the 3 didn’t yield usable results."
      Excerpt, Vikram Sreekanti and Joseph E. Gonzalez

      Published Jan 23, 2025self-described: RunLLM, a startup codebase (frontend and Python backend); tested over the holidays

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Cost predictability and limits, Adoption and upkeep

    Open them in the record
  2. Async delegationAll 9 sources on it praise itHanding off a task from Slack, Linear, Jira, or GitHub and getting a pull request back without watching the session.

    Counted for Engineering leaders and teams.

    1. Positive

      John Wang, Co-Founder and CTO at Assembled

      Code review bottlenecks: How we hill climbed our way to higher PR throughputCompany blog post, Assembled

      Assembled's CTO reports that non-engineers wrote 13% of all PRs after the rollout, and credits the company's auto-reviewer combined with cloud agents like Devin for letting non-engineers contribute without much engineering handholding.

      "The auto-reviewer, combined with cloud agents like Devin, allowed non-engineers to contribute significantly without requiring a large amount of engineering handholding."
      Excerpt, John Wang
      "Non-engineers accounted for 13% of all PRs."
      Same speaker

      Published Aug 7, 2026Assembled, a customer support software company; engineers and non-engineers ship through coding agents and an in-house auto-reviewer

      Practitioner account, self-described; opinion; not counted until substantiated

    2. Positive

      Zachary Proser, Applied AI at WorkOS

      Devin AI Has Come a Long WayPersonal blog post, zackproser.com

      WorkOS abandoned a 2024 Devin trial with zero completed sessions; by 2026 it became a daily, organically adopted Slack agent shipping reviewable PRs, bug fixes and data queries.

      Published May 24, 2026self-described: WorkOS engineering team using Devin in Slack; also personal blog repos

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Adoption and upkeep

    3. Positive

      cloudking, Hacker News commenter

      Comment on: Why we built our own background agentHacker News comment

      Says the team uses Devin and it works very well: it has its own virtual environment, IDE, terminal and browser, can be configured to run the application, and can modify the app, test changes in the browser and send a screen recording of the working feature with a PR.

      Published Jan 14, 2026self-described: Team using Devin as its background agent

      Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes

    4. Positive

      Sahil Lavingia, CEO of Gumroad, interviewed by Aakash Gupta

      How to PM Production Changes with Devin: Tutorial From Gumroad CEO, Sahil LavingiaPodcast episode show notes, The Growth Podcast (Product Growth)

      Gumroad's CEO sends small, clear features straight to Devin from Slack and reviews the pull request it opens only as closely as the change's importance calls for.

      "Small and clear feature → Straight to Devin…"
      Excerpt, Aakash Gupta
      "Devin opens a PR. You review it (or don’t, depending on importance)."
      Same speaker

      Published Oct 19, 2025Gumroad, a US$10M ARR company with one employee; Devin connected to Slack and the codebase

      Practitioner account, self-described; direct use; counts toward Delivered outcomes

    5. Positive

      Eight Sleep data team (Editorial byline)

      How Eight Sleep Uses Devin as a Data AnalystCompany blog post, Eight Sleep blog

      Eight Sleep runs Devin in Slack as a data analyst over its dbt repo and warehouse; with curated knowledge it ships 3x more data work and clears ad-hoc asks.

      "Faster shipping. We’re shipping 3x as many data features and data investigations each week compared to before…"
      Excerpt, Eight Sleep data team

      Published Sep 4, 2025self-described: Eight Sleep small data team; dbt, Snowflake, Looker, Amplitude; Devin used as a data analyst, not for app code

      Practitioner account, self-described; ran the rollout; not counted, tied to the vendor

    6. Positive

      Marco Argenti, Chief Information Officer, Goldman Sachs

      American Banker: Goldman Sachs staff now write a million gen AI prompts a monthNews report quoting the CIO

      Goldman Sachs' CIO describes Devin as a virtual colleague developer teams can delegate work to, beside the Copilot every developer has.

      "All the developers have Github Copilot. They are getting the Devin technology. There's a shift from the developer assistant that helps you auto complete your code or generate code for a specific task, so I now have a virtual colleague that I can delegate work to."
      Excerpt, Marco Argenti

      Published Jul 25, 2025self-described: Goldman Sachs developer teams

    7. Positive

      Rick Blalock, co-founder at Agentuity

      The Agent-Native CompanyConference talk page with transcript, AI Engineer World's Fair 2025

      Blalock reports that it is really common at Agentuity standups to have Devin take on a task, with a pull request to review before the meeting ends. A few months in, Devin has documented so much of the company's code and knows how the team handles certain things; Blalock calls it a superpower.

      "We started using it a few months ago. It was good. We had to do some things. And now over time it's learned so much, it's documented so much of our code, it knows how we handle certain things."
      Excerpt, Rick Blalock
      "During a team meeting, it's really common to hear things like, "Well, just have Devin go do that."…"
      Same speaker

      Published Jun 3, 2025Agentuity, an early-stage agent cloud startup of six or seven people

      Practitioner account, self-described; direct use; counts toward Delivered outcomes

    8. Positive

      Sahil Lavingia, CEO and founder of Gumroad

      Gumroad CEO's playbook to 40x his team's productivity with v0, Cursor, and Devin | Sahil LavingiaPodcast episode, How I AI (YouTube)

      Lavingia's flow is v0, then Devin, then Cursor: prototype in v0, hand the work to Devin, and open Cursor when Devin fails to completely finish. Ran a US$33,000 competition for whoever merged more Devin PRs than the author in May; the host cites Devin writing 41% of Gumroad's PRs.

      "…sort of fails to completely finish then I open it up in cursor. though I did I think last week Devon launched this pairing mode where you can actually like jump in and so I haven't really experimented with that yet but that's presumably I…"
      Transcript excerpt, at 8:40Partial support
      "Yeah, so generally my flow is V0, Devin cursor, is probably how I would say it. Like generally V0 is my prototyping tool of choice. And once I have like a really good prototype that I'm happy with, then I go to Devin and if Devin sort of fails to completely finish then I open it up in cursor."
      Transcript excerpt, Sahil Lavingia (automatic captions), at 8:20

      Published Apr 22, 2025self-described: Gumroad engineering team; episode description says AI agents write 41% of code commits

      Practitioner account, self-described; ran the rollout; counts toward Delivered outcomes, Operational control, Adoption and upkeep

    9. Mixed

      Vikram Sreekanti and Joseph E. Gonzalez, RunLLM

      One month of using DevinNewsletter, The AI Frontier (Substack)

      Sreekanti and Gonzalez found Devin effective on hour-sized fixes that took 1-5 ACUs (US$2-10). A full-stack task they expected a junior engineer to finish within a day was beyond it, and 2 of the 3 bigger tasks, averaging about 20 ACUs, gave no usable results.

      "The 3 bigger tasks we tried averaged about 20 ACUs and 2 of the 3 didn’t yield usable results."
      Excerpt, Vikram Sreekanti and Joseph E. Gonzalez

      Published Jan 23, 2025self-described: RunLLM, a startup codebase (frontend and Python backend); tested over the holidays

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Cost predictability and limits, Adoption and upkeep

    Open them in the record
  3. End-to-end execution7 of 8 sources on it praise itPlanning, editing, running tests or the browser, and iterating to a working pull request without step-by-step prompting.

    Counted for Engineering leaders and teams.

    Positive, 7

    1. Positive

      Brian Xu, engineer on the Agents team at Rox

      Living Evals: an eval suite that grows from productionCompany engineering blog post, Rox

      Xu describes how each week Devin "samples" about 350 production conversations from Braintrust and labels them, replays cases in a "preview" environment holding a full copy of Rox, and opens a pull request with each eval. The first sweep's suite covered 72% of unseen conversations, against 43 to 57% for 142 hand-written evals.

      "It works in its own environment, so it can stand up a preview environment, use Rox there the way a salesperson would, and open a pull request with the finished eval."
      Excerpt, Brian Xu
      "One automated sweep covered twice as many behaviors as everything we had written by hand."
      Same speaker
      "When the skill gets something wrong, Devin proposes a fix to the skill itself, and we review it like any other change."
      Same speaker
      "Every week, Devin, the coding agent from Cognition, reads real conversations on Rox from our production traces in Braintrust, turns them into evals, and opens a pull request that we review."
      Same speaker

      Published Oct 14, 2026Rox engineering team, revenue agent product; post published in partnership with Cognition and Braintrust

      Practitioner account, self-described; ran the rollout; not counted, tied to the vendor

    2. Positive

      deet, Hacker News commenter

      Comment on: Cognition launches new SWE-2 model, Rivaling Fable 5.1 and GPT-AstraHacker News comment

      deet's team uses Devin heavily and calls it one of the best cloud-hosted, team-managed coding agents, citing its UX, sandboxed testing and QA, and API control.

      Published Sep 10, 2026self-described: Team using Devin heavily as a team-managed agent

      Practitioner account, pseudonymous; direct use; not counted, takes no position

    3. Positive

      Prashant Naikar, Developer at a startup acquired by a UK company

      Using Devin AI Daily for 6 Months: What Actually ChangedPersonal blog post, Medium

      After six months of daily use, Prashant Naikar's work shifted to reviewing Devin's pull requests and teaching it the product. Devin navigated the codebase well but missed edge cases and coupling.

      Published Feb 6, 2026self-described: Company-wide AI push after acquisition; manager gave Devin access to two developers

      Practitioner account; direct use; counts toward Delivered outcomes

    4. Positive

      cloudking, Hacker News commenter

      Comment on: Why we built our own background agentHacker News comment

      Says the team uses Devin and it works very well: it has its own virtual environment, IDE, terminal and browser, can be configured to run the application, and can modify the app, test changes in the browser and send a screen recording of the working feature with a PR.

      Published Jan 14, 2026self-described: Team using Devin as its background agent

      Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes

    5. Positive

      Zachary Proser, Applied AI at WorkOS

      Devin AI Has Come a Long WayPersonal blog post, zackproser.com

      WorkOS abandoned a 2024 Devin trial with zero completed sessions; by 2026 it became a daily, organically adopted Slack agent shipping reviewable PRs, bug fixes and data queries.

      Published May 24, 2026self-described: WorkOS engineering team using Devin in Slack; also personal blog repos

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Adoption and upkeep

    6. Positive

      Sahil Lavingia, CEO and founder of Gumroad

      Gumroad CEO's playbook to 40x his team's productivity with v0, Cursor, and Devin | Sahil LavingiaPodcast episode, How I AI (YouTube)

      Lavingia's flow is v0, then Devin, then Cursor: prototype in v0, hand the work to Devin, and open Cursor when Devin fails to completely finish. Ran a US$33,000 competition for whoever merged more Devin PRs than the author in May; the host cites Devin writing 41% of Gumroad's PRs.

      "…sort of fails to completely finish then I open it up in cursor. though I did I think last week Devon launched this pairing mode where you can actually like jump in and so I haven't really experimented with that yet but that's presumably I…"
      Transcript excerpt, at 8:40Partial support
      "Yeah, so generally my flow is V0, Devin cursor, is probably how I would say it. Like generally V0 is my prototyping tool of choice. And once I have like a really good prototype that I'm happy with, then I go to Devin and if Devin sort of fails to completely finish then I open it up in cursor."
      Transcript excerpt, Sahil Lavingia (automatic captions), at 8:20

      Published Apr 22, 2025self-described: Gumroad engineering team; episode description says AI agents write 41% of code commits

      Practitioner account, self-described; ran the rollout; counts toward Delivered outcomes, Operational control, Adoption and upkeep

    7. Negative

      tlarkworthy, Hacker News commenter

      Comment on: Thoughts on a month with DevinHacker News comment

      Devin impressed when it grasped formatting and local tests, but it kept adding extraneous, breaking changes it could not undo, so tlarkworthy will recommend canceling it.

      Published Jan 17, 2025self-described: Trial of Devin including its Slack interface; author plans to recommend canceling

      Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account

    Mixed or negative, 1

    1. Negative

      Hamel Husain, Isaac Flath, and Johno Whitaker, Answer.AI

      Thoughts On A Month With DevinCompany blog post, Answer.AI blog

      Over one month the Answer.AI team gave Devin 20 real tasks: 14 failed, 3 succeeded, 3 were inconclusive, and they could not predict which tasks would work.

      "The results were sobering. Out of 20 tasks, we had 14 failures, 3 successes (including our 2 initial ones), and 3 inconclusive results."
      Excerpt, Hamel Husain

      Published Jan 8, 2025self-described: Answer.AI, a team that routinely experiments with AI developer tools; month-long test on real projects

      Practitioner account, self-described; structured test; counts toward Delivered outcomes, Reliability, Operational control

    Open them in the record
  4. Migrations & repetitive changesAll 5 sources on it praise itLarge sets of similar changes such as migrations, upgrades, dependency updates, and test backfills.

    Counted for Engineering leaders and teams.

    1. Positive

      David Griffiths, Group Head of AI at Citi

      A Competitive Differentiator: David Griffiths on Building the World's Most AI-empowered Financial InstitutionCompany perspectives article, Citi

      Citi's profile of its Group Head of AI says the bank adopted Devin early to speed up complex, multi-step coding tasks. One task re-mapped more than 30 years of legacy code across the firm in two days.

      "Early on, Citi adopted Devin, a coding agent developed by the AI lab Cognition to expedite complex, multi-step coding tasks. One such task involved re-mapping more than 30 years of legacy code across the firm in two days."
      Excerpt, David Griffiths

      Published Sep 22, 2026Global bank; firmwide AI platform team serving employees in more than 87 countries and jurisdictions

      Practitioner account, self-described; ran the rollout; counts toward Delivered outcomes

    2. Mixed

      Daniel Price, docs team at Neon

      AI Workflows for Docs: Putting Devin to WorkCompany blog post, Neon

      Neon's docs team uses a Devin playbook to set up the weekly changelog, sends it to work through older docs issues and small UI copy fixes, and has it explain code. A feature rename left awkward edits that took 20+ manual commits, and open-ended tasks often failed silently, so Cursor stays their interactive tool.

      "Devin does well when the problem is clearly scoped, but once things get open-ended, it still struggles."
      Excerpt, Daniel Price
      "But its edits leaned heavily on direct find/replace, which led to some awkward constructions like “instant instant restore.” It took another 20+ manual commits to polish the changes."
      Same speaker
      "But when the task is clear and the scope is right, it’s a genuinely helpful assistant."
      Same speaker

      Published Jun 23, 2025Neon docs team; docs repo, changelogs and small Neon Console UI fixes

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability

    3. Positive

      nikisweeting, Engineer at browser-use

      Comment on: DeepWiki: Understand Any CodebaseHacker News comment

      DeepWiki was instrumental in the browser-use team's refactor of a large codebase from Playwright to pure CDP; nikisweeting rates its follow-up research questions above OpenAI deep research for complex codebases.

      Published Aug 26, 2025self-described: browser-use, refactor of a large codebase from Playwright to CDP

      Practitioner account, pseudonymous; opinion; not counted, takes no position

    4. Positive

      Zach Davis, Director of engineering at LaunchDarkly

      Successfully coding with AI in large enterprises: Centralized rules, workflows for tech debt, & morePodcast episode, How I AI (YouTube)

      Davis consolidated Cursor rules and a Claude MD file into one in-repo agents directory, started from Devin's per-repo wiki to write docs, got Devin running in front-end-only mode before a colleague set up the back end, and can Slack Devin to pick up the next tech-debt cleanup task.

      "…for anybody trying to deploy AI agents in a real engineering team with a real codebase, not just vibe coding. We have Zach Davis, director of engineering at Launch Darkley, who's going to show us how he sets up centralized rules and…"
      Transcript excerpt, at 1:12Partial support

      Published Jul 21, 2025self-described: LaunchDarkly, 100-plus-person engineering team working in a large, roughly 10-year-old monorepo

      Practitioner account, self-described; ran the rollout; counts toward Delivered outcomes, Adoption and upkeep

    5. Mixed

      David Griffiths, Chief Technology Officer, Citi

      American Banker: Citi is rolling out agentic AI to its 40,000 developersNews report quoting the CTO

      Citi's CTO gives developers Devin for simple, repeatable tasks such as upgrades, rewrites, patches, documentation and tests, and would not yet ask an agent to build a complicated feature end to end.

      ""It's not at the point where you would want to ask the agent to implement a very complicated feature from start to finish. We may get there with the technology in time, but today, I wouldn't recommend anyone to do that. We focus on the simple, repeatable tasks, which it can do at our scale."
      Excerpt, David Griffiths

      Published Jul 14, 2025self-described: Citi, 40,000 developers

    Open them in the record
  5. Developer experience5 of 7 sources on it praise itDevin's session interface and chat, including response speed and access to its shell, IDE, and browser.

    Counted for Engineering leaders and teams.

    Positive, 5

    1. Positive

      Zachary Proser, Applied AI at WorkOS

      Devin AI Has Come a Long WayPersonal blog post, zackproser.com

      WorkOS abandoned a 2024 Devin trial with zero completed sessions; by 2026 it became a daily, organically adopted Slack agent shipping reviewable PRs, bug fixes and data queries.

      Published May 24, 2026self-described: WorkOS engineering team using Devin in Slack; also personal blog repos

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Adoption and upkeep

    2. Positive

      deet, Hacker News commenter

      Comment on: Cognition launches new SWE-2 model, Rivaling Fable 5.1 and GPT-AstraHacker News comment

      deet's team uses Devin heavily and calls it one of the best cloud-hosted, team-managed coding agents, citing its UX, sandboxed testing and QA, and API control.

      Published Sep 10, 2026self-described: Team using Devin heavily as a team-managed agent

      Practitioner account, pseudonymous; direct use; not counted, takes no position

    3. Mixed

      Vikram Sreekanti and Joseph E. Gonzalez, RunLLM

      One month of using DevinNewsletter, The AI Frontier (Substack)

      Sreekanti and Gonzalez found Devin effective on hour-sized fixes that took 1-5 ACUs (US$2-10). A full-stack task they expected a junior engineer to finish within a day was beyond it, and 2 of the 3 bigger tasks, averaging about 20 ACUs, gave no usable results.

      "The 3 bigger tasks we tried averaged about 20 ACUs and 2 of the 3 didn’t yield usable results."
      Excerpt, Vikram Sreekanti and Joseph E. Gonzalez

      Published Jan 23, 2025self-described: RunLLM, a startup codebase (frontend and Python backend); tested over the holidays

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Cost predictability and limits, Adoption and upkeep

    4. Negative

      tlarkworthy, Hacker News commenter

      Comment on: Thoughts on a month with DevinHacker News comment

      Devin impressed when it grasped formatting and local tests, but it kept adding extraneous, breaking changes it could not undo, so tlarkworthy will recommend canceling it.

      Published Jan 17, 2025self-described: Trial of Devin including its Slack interface; author plans to recommend canceling

      Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account

    5. Negative

      Hamel Husain, Isaac Flath, and Johno Whitaker, Answer.AI

      Thoughts On A Month With DevinCompany blog post, Answer.AI blog

      Over one month the Answer.AI team gave Devin 20 real tasks: 14 failed, 3 succeeded, 3 were inconclusive, and they could not predict which tasks would work.

      "The results were sobering. Out of 20 tasks, we had 14 failures, 3 successes (including our 2 initial ones), and 3 inconclusive results."
      Excerpt, Hamel Husain

      Published Jan 8, 2025self-described: Answer.AI, a team that routinely experiments with AI developer tools; month-long test on real projects

      Practitioner account, self-described; structured test; counts toward Delivered outcomes, Reliability, Operational control

    Mixed or negative, 2

    1. Mixed

      hightrix, Hacker News commenter

      Comment on: Cognition launches new SWE-2 model, Rivaling Fable 5.1 and GPT-AstraHacker News comment

      hightrix's company has used Devin enterprise seats for about nine months; it beats Copilot, but hightrix now finds Claude and Codex much better and the web and desktop harnesses inconsistent.

      Published Sep 10, 2026self-described: Company with a number of Devin seats on an enterprise plan, used for about 9 months

      Practitioner account, pseudonymous; direct use; counts toward Reliability

    2. Mixed

      Kieran Klaassen, GM of Cora at Every

      Transcript: 'How Two Engineers Ship Like a Team of 15 With AI Agents'Podcast transcript, AI & I (Every)

      Ranking the coding agents his team uses, Klaassen grades Devin a B: less integrated and harder to set up than Cursor or Claude Code, with less well-rounded code quality.

      "It's not as integrated. It's a little bit hard to set up, and the code quality is not as well rounded as Cursor or Claude Code."
      Excerpt, Kieran Klaassen

      Published Jun 11, 2025Two-engineer team building Every's Cora email assistant with several coding agents

      Practitioner account, self-described; direct use; not counted, from a competitor's side

    Open them in the record

What concerns them

Every concern practitioners raise, most raised first.

  1. Requires strong review7 of 8 sources on it raise it as a concernThe human review and rework needed before Devin's pull requests can be trusted.

    Counted for Engineering leaders and teams.

    Raised as a concern, 7

    1. Negative

      Fit_Sprinkles_8649, Reddit user in r/programming

      Comment on: Someone uses Devin AIReddit comment

      Fit_Sprinkles_8649's team dropped Devin after two months: its pull requests ignored existing patterns, so senior developers spent more time reviewing and fixing than writing the code themselves.

      Published Feb 2, 2026self-described: Company team, two-month trial

      Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes

    2. Negative

      tlarkworthy, Hacker News commenter

      Comment on: Thoughts on a month with DevinHacker News comment

      Devin impressed when it grasped formatting and local tests, but it kept adding extraneous, breaking changes it could not undo, so tlarkworthy will recommend canceling it.

      Published Jan 17, 2025self-described: Trial of Devin including its Slack interface; author plans to recommend canceling

      Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account

    3. Mixed

      steve_avery, Hacker News commenter

      Comment on: We tried hard to make Devin work for us, But it didn'tHacker News comment

      Devin impressed their team early on but has lately been a letdown; steve_avery is wading through a bloated Devin PR, though the team is not yet ready to cancel.

      Published Jan 17, 2025self-described: Team using Devin; author reviewing a Devin PR

      Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account

    4. Positive

      Prashant Naikar, Developer at a startup acquired by a UK company

      Using Devin AI Daily for 6 Months: What Actually ChangedPersonal blog post, Medium

      After six months of daily use, Prashant Naikar's work shifted to reviewing Devin's pull requests and teaching it the product. Devin navigated the codebase well but missed edge cases and coupling.

      Published Feb 6, 2026self-described: Company-wide AI push after acquisition; manager gave Devin access to two developers

      Practitioner account; direct use; counts toward Delivered outcomes

    5. Mixed

      Daniel Price, docs team at Neon

      AI Workflows for Docs: Putting Devin to WorkCompany blog post, Neon

      Neon's docs team uses a Devin playbook to set up the weekly changelog, sends it to work through older docs issues and small UI copy fixes, and has it explain code. A feature rename left awkward edits that took 20+ manual commits, and open-ended tasks often failed silently, so Cursor stays their interactive tool.

      "Devin does well when the problem is clearly scoped, but once things get open-ended, it still struggles."
      Excerpt, Daniel Price
      "But its edits leaned heavily on direct find/replace, which led to some awkward constructions like “instant instant restore.” It took another 20+ manual commits to polish the changes."
      Same speaker
      "But when the task is clear and the scope is right, it’s a genuinely helpful assistant."
      Same speaker

      Published Jun 23, 2025Neon docs team; docs repo, changelogs and small Neon Console UI fixes

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability

    6. Mixed

      Vikram Sreekanti and Joseph E. Gonzalez, RunLLM

      One month of using DevinNewsletter, The AI Frontier (Substack)

      Sreekanti and Gonzalez found Devin effective on hour-sized fixes that took 1-5 ACUs (US$2-10). A full-stack task they expected a junior engineer to finish within a day was beyond it, and 2 of the 3 bigger tasks, averaging about 20 ACUs, gave no usable results.

      "The 3 bigger tasks we tried averaged about 20 ACUs and 2 of the 3 didn’t yield usable results."
      Excerpt, Vikram Sreekanti and Joseph E. Gonzalez

      Published Jan 23, 2025self-described: RunLLM, a startup codebase (frontend and Python backend); tested over the holidays

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Cost predictability and limits, Adoption and upkeep

    7. Negative

      Hamel Husain, Isaac Flath, and Johno Whitaker, Answer.AI

      Thoughts On A Month With DevinCompany blog post, Answer.AI blog

      Over one month the Answer.AI team gave Devin 20 real tasks: 14 failed, 3 succeeded, 3 were inconclusive, and they could not predict which tasks would work.

      "The results were sobering. Out of 20 tasks, we had 14 failures, 3 successes (including our 2 initial ones), and 3 inconclusive results."
      Excerpt, Hamel Husain

      Published Jan 8, 2025self-described: Answer.AI, a team that routinely experiments with AI developer tools; month-long test on real projects

      Practitioner account, self-described; structured test; counts toward Delivered outcomes, Reliability, Operational control

    Discussed without concern, 1

    1. Positive

      Zachary Proser, Applied AI at WorkOS

      Devin AI Has Come a Long WayPersonal blog post, zackproser.com

      WorkOS abandoned a 2024 Devin trial with zero completed sessions; by 2026 it became a daily, organically adopted Slack agent shipping reviewable PRs, bug fixes and data queries.

      Published May 24, 2026self-described: WorkOS engineering team using Devin in Slack; also personal blog repos

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Adoption and upkeep

    Open them in the record
  2. Unpredictable task success3 of 6 sources on it raise it as a concernSessions that fail or loop on an impossible path, and difficulty predicting which tasks will succeed.

    Counted for Engineering leaders and teams.

    Raised as a concern, 3

    1. Mixed

      Vikram Sreekanti and Joseph E. Gonzalez, RunLLM

      One month of using DevinNewsletter, The AI Frontier (Substack)

      Sreekanti and Gonzalez found Devin effective on hour-sized fixes that took 1-5 ACUs (US$2-10). A full-stack task they expected a junior engineer to finish within a day was beyond it, and 2 of the 3 bigger tasks, averaging about 20 ACUs, gave no usable results.

      "The 3 bigger tasks we tried averaged about 20 ACUs and 2 of the 3 didn’t yield usable results."
      Excerpt, Vikram Sreekanti and Joseph E. Gonzalez

      Published Jan 23, 2025self-described: RunLLM, a startup codebase (frontend and Python backend); tested over the holidays

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Cost predictability and limits, Adoption and upkeep

    2. Negative

      Hamel Husain, Isaac Flath, and Johno Whitaker, Answer.AI

      Thoughts On A Month With DevinCompany blog post, Answer.AI blog

      Over one month the Answer.AI team gave Devin 20 real tasks: 14 failed, 3 succeeded, 3 were inconclusive, and they could not predict which tasks would work.

      "The results were sobering. Out of 20 tasks, we had 14 failures, 3 successes (including our 2 initial ones), and 3 inconclusive results."
      Excerpt, Hamel Husain

      Published Jan 8, 2025self-described: Answer.AI, a team that routinely experiments with AI developer tools; month-long test on real projects

      Practitioner account, self-described; structured test; counts toward Delivered outcomes, Reliability, Operational control

    3. Mixed

      Daniel Price, docs team at Neon

      AI Workflows for Docs: Putting Devin to WorkCompany blog post, Neon

      Neon's docs team uses a Devin playbook to set up the weekly changelog, sends it to work through older docs issues and small UI copy fixes, and has it explain code. A feature rename left awkward edits that took 20+ manual commits, and open-ended tasks often failed silently, so Cursor stays their interactive tool.

      "Devin does well when the problem is clearly scoped, but once things get open-ended, it still struggles."
      Excerpt, Daniel Price
      "But its edits leaned heavily on direct find/replace, which led to some awkward constructions like “instant instant restore.” It took another 20+ manual commits to polish the changes."
      Same speaker
      "But when the task is clear and the scope is right, it’s a genuinely helpful assistant."
      Same speaker

      Published Jun 23, 2025Neon docs team; docs repo, changelogs and small Neon Console UI fixes

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability

    Discussed without concern, 3

    1. Positive

      Zachary Proser, Applied AI at WorkOS

      Devin AI Has Come a Long WayPersonal blog post, zackproser.com

      WorkOS abandoned a 2024 Devin trial with zero completed sessions; by 2026 it became a daily, organically adopted Slack agent shipping reviewable PRs, bug fixes and data queries.

      Published May 24, 2026self-described: WorkOS engineering team using Devin in Slack; also personal blog repos

      Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Adoption and upkeep

    2. Positive

      Prashant Naikar, Developer at a startup acquired by a UK company

      Using Devin AI Daily for 6 Months: What Actually ChangedPersonal blog post, Medium

      After six months of daily use, Prashant Naikar's work shifted to reviewing Devin's pull requests and teaching it the product. Devin navigated the codebase well but missed edge cases and coupling.

      Published Feb 6, 2026self-described: Company-wide AI push after acquisition; manager gave Devin access to two developers

      Practitioner account; direct use; counts toward Delivered outcomes

    3. Positive

      Sahil Lavingia, CEO and founder of Gumroad

      Gumroad CEO's playbook to 40x his team's productivity with v0, Cursor, and Devin | Sahil LavingiaPodcast episode, How I AI (YouTube)

      Lavingia's flow is v0, then Devin, then Cursor: prototype in v0, hand the work to Devin, and open Cursor when Devin fails to completely finish. Ran a US$33,000 competition for whoever merged more Devin PRs than the author in May; the host cites Devin writing 41% of Gumroad's PRs.

      "…sort of fails to completely finish then I open it up in cursor. though I did I think last week Devon launched this pairing mode where you can actually like jump in and so I haven't really experimented with that yet but that's presumably I…"
      Transcript excerpt, at 8:40Partial support
      "Yeah, so generally my flow is V0, Devin cursor, is probably how I would say it. Like generally V0 is my prototyping tool of choice. And once I have like a really good prototype that I'm happy with, then I go to Devin and if Devin sort of fails to completely finish then I open it up in cursor."
      Transcript excerpt, Sahil Lavingia (automatic captions), at 8:20

      Published Apr 22, 2025self-described: Gumroad engineering team; episode description says AI agents write 41% of code commits

      Practitioner account, self-described; ran the rollout; counts toward Delivered outcomes, Operational control, Adoption and upkeep

    GILD's fact checks, which don't count as sources

    Checked Oct 12, 2026.Cognition's guidance puts the reliable range at tasks an engineer could finish in about three hours, with tests or CI as the success criteria. It recommends splitting larger work into separate sessions. When to use Devin

    Open them in the record

Where the evidence agrees

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

  1. Recurring point

    Devin performs best on well-scoped tasks with clear success criteria, such as tests or CI, that it can check for itself.

    6 supporting sources

Close to agreement: each needs 6 supporting sources

  1. Below threshold

    A working environment per repository and maintained written context, through Knowledge, Skills, playbooks, or AGENTS.md, make Devin's results more reliable.

    5 supporting sources

Where it disagrees

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

  • Evidence remains mixed

    Should Devin work as a hands-off teammate, or do engineers get more from an interactive agent for the same work?

    • Hands-off delegation, 4 sources

      Some hand Devin whole tickets or parallel threads and come back to the pull request.

    • Interactive tools, 4 sources

      Others tried Devin and went back to tools such as Cursor or Claude Code, where they steer each step.

  • Evidence remains mixed

    Once review and rework are counted, does Devin reduce total engineering time?

    • Net time saved, 4 sources

      Some report work shipped with minutes of their own attention, or several times more output.

    • Absorbed by review, 3 sources

      Others find review and rework absorb the time saved, or make the work slower than doing it by hand.

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

    28 sources. These accounts focus on delegated throughput, environment setup, written context, usage cost, review load, and what changes when Devin moves from a few engineers to many teams.

  • Individual builders

    35 sources. These accounts focus on whether a single session finishes, how long it takes, what it costs, and how Devin compares with interactive tools for self-directed work.

  • All practitioners

    63 sources. This group gives the broadest read. It combines solo and team settings that can reach different conclusions about Devin.

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

  1. Individual practitionerSolo developers and independent builders35 sources

    Emphasizes Whether a single session finishes and what it costs

  2. Very small team2 to 10 engineers10 sources, counted here

    Emphasizes Delegating tickets and whether the subscription pays off

  3. Professional team11 to 50 engineers, or a named company's team7 sources, counted here

    Emphasizes Merged pull requests and cost per task

  4. Technical leadershipLeaders setting adoption across teams8 sources, counted here

    Emphasizes Where to delegate and whether engineers keep using it

  5. Organization-wideEnterprise or company-wide rollout3 sources, counted here

    Emphasizes Usage limits and access management across many developers

What changes with scale. Individual builders judge Devin on whether a session finishes and what it costs. Team accounts turn to codebase understanding, review load, and whether the time saved survives review.

Where the sources come from

Where this group's sources were published.

Counted for Engineering leaders and teams, from 28 sources. Change group

49 sources for this group, 21 of them documentation

  • Product documentation21, 43% of 49 sources
  • Engineering blogs & reviews12, 24% of 49 sources
  • Developer communities11, 22% of 49 sources
  • Podcasts, Talks & Videos5, 10% of 49 sources

Older evidence is retained when it still applies. Sources that depend on a changed plan, price, or product version stay in the history, marked 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

  • Nov 1, 2026: by the owner's decision, a record whose own words state no overall view of Devin now casts no vote; it still counts toward its topics and is listed, and 9 records that counted leave the vote this way. Leaders and teams move from +38 to +39, individual builders from +26 to +36 and all practitioners from +32 to +37.
  • Oct 31, 2026: counts the Answer.AI trial once. Jeremy Howard's post reports the same trial as the team's write-up, so it stays listed and counts toward nothing. Leaders and teams move from +43 to +52, now Strong Positive, and all practitioners from +35 to +40.
  • Oct 30, 2026: a second-model check removed the Operator Insight drawn from Scott Logic's post, a consultancy's own write-up, while its earlier Signals record stays. It filed a Hacker News developer's trial as an evaluation, since they recommended cancelling and did not say they had cancelled. Citi's card now says Citi began rolling Devin out to a developer organization of 40,000. It dated Indeed's accounts to the talk DX published in June 2026, since DX's page prints no day.
  • Oct 28, 2026: added 2 records from GILD's research ledger, American Banker reports quoting Citi's CTO and Goldman Sachs' CIO on running Devin beside Copilot, and quoted six accounts already listed, from Gumroad, Answer.AI, RunLLM, Scott Logic, Rox and Eight Sleep. Leaders and teams stay at +43 on 28 counted sources, individual builders at +24 on 35, and all practitioners at +35 on 63.
  • Each account links to an English-language source dated 2025 or later and names its author and publication date.
  • A finding shows for a group only when at least 5 sources from 3 different authors discuss it. A disagreement requires at least 2 sources on each side.
  • Leaves out Migrations & Repetitive Changes (4 sources) and the junior-engineer and parallel-sessions statements (4 each). Each falls short of the rule: 5 sources from 3 authors. Launch-video criticism from 2024 is out of the window.
  • Checks every documentation page against Cognition's current Devin docs, including the move from Knowledge to Skills.
  • Oct 25, 2026: added Needs close steering from what existing accounts state: 7 report sessions that drifted or looped until they stepped in, and 1 says Devin planned the work without hand-holding.
  • Oct 25, 2026: added 6 sources from outside forums. Three are GitHub issues on Cognition's Devin CLI repository; the others are a Qubika engineer's test on a client project and two podcast pages, with Every's Cora team and with Gumroad's CEO.

Method

A running review of what engineering teams report about Devin, 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. On the AI coding agent hubs, each account's overall stance comes from GILD's blind coding: two models from different families read the source's own words without seeing each other's codes, and a third settled where they differed. An account that states no overall view there, such as a bug report, casts no vote and still counts toward its topics. Other hubs count the stance stored on each record. 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 +52 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 +43 Positive; with one vote per author it read +31 Positive. No evidence changed.
  • Correction, Nov 1, 2026. GILD now takes each account's overall stance from its blind two-model coding, and accounts that state no overall view cast no vote. It read +38 Positive and now reads +39 Positive.
  • 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 4 of 24, individual builders 10 of 29, all practitioners 14 of 53.

Limits

  • GILD reviewed 63 public accounts dated 2025 or later. They comprise 27 Hacker News comments, 5 Reddit comments, 3 GitHub issues on the Devin CLI repository, and 1 X post. The rest are 17 English blog, newsletter and company posts, 2 news reports, and 8 videos, talks and podcast episodes. Five sources review DeepWiki or Devin Review, which Cognition includes with Devin. Records note any creator-disclosed access or credits from Cognition. Counts describe these sources and do not represent all Devin users.
  • Sources record the plan, price, and product version inconsistently; each source shows what it states. Sources from before Devin 2.0 (April 2025), or that depend on the retired ACU-based self-serve plans, are marked Needs a recheck.

Every count, and the sources behind it

20 findings for 3 groups

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

FindingEngineering leaders and teamsIndividual buildersAll practitionersSources
Current readCurrent sentiment13 positive, 7 mixed, 4 negative17 positive, 4 mixed, 8 negative30 positive, 11 mixed, 12 negativeSources
PraiseAsync delegation9 of 9 positive7 of 7 positive16 of 16 positiveSources
PraiseEnd-to-end execution7 of 8 positive10 of 10 positive17 of 18 positiveSources
PraiseCodebase understanding11 of 11 positive3 of 5 positive14 of 16 positiveSources
PraiseMigrations & repetitive changes5 of 5 positive2 of 2 positive (under the minimum)7 of 7 positiveSources
PraiseDeveloper experience5 of 7 positive3 of 8 positive8 of 15 positiveSources
ConcernUnpredictable task success3 of 6 raise it8 of 11 raise it11 of 17 raise itSources
ConcernUsage and cost3 of 4 raise it (under the minimum)8 of 14 raise it11 of 18 raise itSources
ConcernRequires strong review7 of 8 raise it4 of 7 raise it11 of 15 raise itSources
ConcernEnvironment & context setup3 of 4 raise it (under the minimum)1 of 4 raise it (under the minimum)4 of 8 raise itSources
ConcernSession speed1 of 2 raise it (under the minimum)2 of 3 raise it (under the minimum)3 of 5 raise itSources
ConcernNeeds close steering3 of 3 raise it (under the minimum)6 of 7 raise it9 of 10 raise itSources
ConsensusSetup and written context improve results5 supporting (below threshold)2 supporting (under the minimum)7 supporting (below threshold)Sources
ConsensusStrongest on scoped, verifiable tasks6 supporting2 supporting (under the minimum)8 supporting (below threshold)Sources
ConsensusManaged like a junior engineer1 supporting (under the minimum)3 supporting (under the minimum)4 supporting (under the minimum)Sources
ConsensusValue comes from parallel sessions0 supporting (under the minimum)4 supporting (under the minimum)4 supporting (under the minimum)Sources
DisagreementShould Devin work as a hands-off teammate, or do engineers get more from an interactive agent for the same work?Hands-off delegation 4, Interactive tools 4Hands-off delegation 2, Interactive tools 3Hands-off delegation 6, Interactive tools 7Sources
DisagreementOnce review and rework are counted, does Devin reduce total engineering time?Net time saved 4, Absorbed by review 3Net time saved 5, Absorbed by review 2Net time saved 9, Absorbed by review 5Sources
DisagreementHow much work should Devin take on before a human checkpoint?Broader delegation 1, Tighter steering 1 (under the minimum)Broader delegation 3, Tighter steering 3Broader delegation 4, Tighter steering 4Sources
Current readEvidence mix49 sources56 sources84 sourcesSources

Fact checks

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

  • Unpredictable task success. Cognition's guidance puts the reliable range at tasks an engineer could finish in about three hours, with tests or CI as the success criteria. It recommends splitting larger work into separate sessions. When to use Devin, checked Oct 12, 2026
  • Usage and cost. Spending controls depend on the plan: self-serve admins set default session spending limits and auto-reload thresholds. Enterprise admins set organization and per-user ACU limits. Anyone can see a session's cost in Session Insights. A report of unexpected spend does not establish that spending controls are missing. Usage, checked Oct 12, 2026
  • Environment & context setup. Cognition ranks environment configuration first among the steps that improve results. A blueprint per repository produces the snapshot every session boots from, and Devin can draft the blueprint itself. Environment setup, checked Oct 12, 2026