83 sources from practitioners, by month and sentiment.
76 sources give an opinion, and the read is mixed. Developers value the pull request workflow and the free allowance, and report tasks that do not finish, pull requests that need rework, and slow runs. Hacker News leans positive, while r/JulesAgent, where users bring problems, leans negative.
Positive, mixed and negative sources
261824
The score counts them as 24 positive, 18 mixed and 24 negative votes, one per author. See How the numbers work.
Counted for All practitioners, from 83 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.
1End-to-end executionAll 17 sources on it praise itPlanning, editing, installing dependencies, and running tests in its VM until the change works, without step-by-step prompting.
Running the same prompts through Jules and Claude Opus 4.6, filipoi found each better at times and credits Jules's memory of the codebase. After two months on one project the output is good enough.
Published Feb 7, 2026self-described: Two months of daily work on one project; compared with Claude Opus 4.6
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes, Cost predictability and limits
A single prompt ran for over two hours as Jules worked step by step through a complex issue, without looping or losing the task, which itstingsandithurts saw as a new capability.
Published Jan 30, 2026self-described: A complex issue worked in one long session
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes, Reliability
Testing Jules on the free plan in forked websocket (Go) and qwen-code (TypeScript) repos, Heller asked it to pick and fix an open bug. On qwen-code it noticed and fixed build errors, and its code review caught a JSON file that did not belong in the PR; says Jules behaved better than Gemini CLI.
Published Nov 11, 2025self-described: Review on forks of public repositories (websocket in Go, qwen-code in TypeScript)
Practitioner account, name and role on their organization's own page; structured test; counts toward Delivered outcomes, Operational control, Cost predictability and limits, Adoption and upkeep
Jules runs unit tests, linting and Playwright on its VMs, works well on mobile with notifications, and xetxov calls 100 daily tasks on Google AI Pro a fantastic deal.
Published Aug 12, 2025
Practitioner account, pseudonymous; direct use; counts toward Cost predictability and limits
Workaccount2 reports really good results from Jules in the beta and finds it much more capable than the regular Gemini API, within the 5 tasks a day the beta allowed.
Published May 25, 2025
Practitioner account, pseudonymous; direct use; counts toward Cost predictability and limits
maaakks was impressed by how much Jules handles almost on its own, more than Roo Code or OpenHands on Flash or local models, but expects review to become the bottleneck.
Published May 25, 2025self-described: Compared with Roo Code and OpenHands on Gemini Flash and local models
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes, Operational control
After about 50 prompts across other models failed on a persistent web app bug, Jules fixed it in one attempt, though the task took well over an hour because of launch traffic.
Published May 21, 2025
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
mark_l_watson had Jules write tests and other improvements twice and found the tests pretty good, with Jules building and running the changed code in its VM.
Published May 20, 2025self-described: Author and AI practitioner
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
Since Gemini 3.1 Pro simonpure runs a loop where Jules extends its TODO list and opens pull requests, GitHub Actions checks and merges them, and the Jules API starts the next cycle.
Published May 11, 2026self-described: Building transflux, agent-driven development for Clojure
Practitioner account, pseudonymous; ran the rollout; counts toward Delivered outcomes
Working with Jules feels like instructing a junior engineer: it must be told exactly what to do and checked, but pull requests make its mistakes fixable and its code reasoning is strong.
Published Mar 18, 2026self-described: Solo; maintaining Feditrends, a scraper and link ranker Nelson Minar took over
Practitioner account; direct use; counts toward Delivered outcomes, Operational control, Cost predictability and limits
A freelancer taught a long-time client to use Jules on an old Django site. The client opens pull requests and checks each on a Railway test environment. It works about 75% of the time before the freelancer reviews and merges.
Published Oct 3, 2025self-described: Freelancer and a long-time client on an old Django site
Practitioner account, pseudonymous; ran the rollout; counts toward Delivered outcomes
Giving Jules the same Go and Python exercise as two juniors, youCanbeAPirate found it very fast at prototyping and following patterns. It was so literal that it replaced whole files when told to reuse part of one.
Published Aug 12, 2025self-described: Engineer who mentors juniors; same exercise given to two juniors and to Jules
2Async delegationAll 14 sources on it praise itHanding off a task from the web app, a phone, a GitHub issue, or the API and coming back to a branch or pull request without watching.
b473a directs Jules from the phone and merges the pull request about fifteen minutes later, but notes Jules was still on Gemini 3.1 Pro and asks for alternatives.
Published Jul 21, 2026self-described: Personal projects worked on during the commute
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes, Adoption and upkeep
Since Gemini 3.1 Pro simonpure runs a loop where Jules extends its TODO list and opens pull requests, GitHub Actions checks and merges them, and the Jules API starts the next cycle.
Published May 11, 2026self-described: Building transflux, agent-driven development for Clojure
Practitioner account, pseudonymous; ran the rollout; counts toward Delivered outcomes
A freelancer taught a long-time client to use Jules on an old Django site. The client opens pull requests and checks each on a Railway test environment. It works about 75% of the time before the freelancer reviews and merges.
Published Oct 3, 2025self-described: Freelancer and a long-time client on an old Django site
Practitioner account, pseudonymous; ran the rollout; counts toward Delivered outcomes
p1nkpineapple plans features on the walk to work, sends Jules several jobs from the phone and reviews pull requests at night; most code gets rewritten, but it usually runs.
Published Aug 6, 2025self-described: Side project, a React Native app coded from a phone
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
From a phone, Simon Willison pasted a long issue thread into Jules with no other instructions. The pull request covered most requirements at a glance, though tests were failing.
Published May 19, 2025self-described: Solo; open source project issue thread
Practitioner account, self-described; direct use; counts toward Delivered outcomes
After months of good work with Jules, which came free with their Google AI plan, Nelson Minar found Claude Code on Opus 5 far more capable. Likens Jules to an engineer with one year of experience.
Published Sep 12, 2026self-described: Months of Jules on Google AI, then a week of Claude Code on Opus 5
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
For months Distinct-Survey475 has run four narrow nightly Jules jobs and a weekly cleanup from GitHub Actions on a monorepo; small, isolated missions stopped it from breaking the build.
Published Jul 17, 2026self-described: Astro and Cloudflare Workers monorepo, months of scheduled runs
Practitioner account, pseudonymous; ran the rollout; counts toward Delivered outcomes, Operational control, Adoption and upkeep
Uses Jules "religiously" and likes it: the GUI is a big plus, along with the "previewing" of produced content and using it on a phone the same as on a laptop. Asks whether others have tried Copilot or Claude Code.
Published Mar 11, 2026self-described: Daily use on phone and laptop
Practitioner account, pseudonymous; direct use; not counted, takes no position
3Free tier & plan value11 of 12 sources on it praise itWhat the free tier and the task allowances in Google AI Pro and Ultra give a developer for the money.
versteegen calls the free tier extremely generous and praises its automated code review, but finds Jules very slow, with long silences and no usable diff viewer at the time.
Published Oct 4, 2025self-described: Independent AI researcher
Practitioner account, pseudonymous; direct use; counts toward Cost predictability and limits
Jules runs unit tests, linting and Playwright on its VMs, works well on mobile with notifications, and xetxov calls 100 daily tasks on Google AI Pro a fantastic deal.
Published Aug 12, 2025
Practitioner account, pseudonymous; direct use; counts toward Cost predictability and limits
sagarpatil uses Jules and Augment's remote agents because per-message billing avoids unexpected API costs while they work locally. Neither bills by token.
Published May 29, 2025
Practitioner account, pseudonymous; direct use; counts toward Cost predictability and limits
After months of good work with Jules, which came free with their Google AI plan, Nelson Minar found Claude Code on Opus 5 far more capable. Likens Jules to an engineer with one year of experience.
Published Sep 12, 2026self-described: Months of Jules on Google AI, then a week of Claude Code on Opus 5
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
Over three weeks on Pro, Jules cleared batched maintenance well, including 12 parallel tasks in 90 minutes, but took 8 to 15 minutes per task and twice reported unfinished work as complete.
Published May 22, 2026self-described: Solo; a Flask API and two Go microservices over three weeks
Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Operational control, Cost predictability and limits
Running the same prompts through Jules and Claude Opus 4.6, filipoi found each better at times and credits Jules's memory of the codebase. After two months on one project the output is good enough.
Published Feb 7, 2026self-described: Two months of daily work on one project; compared with Claude Opus 4.6
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes, Cost predictability and limits
Testing Jules on the free plan in forked websocket (Go) and qwen-code (TypeScript) repos, Heller asked it to pick and fix an open bug. On qwen-code it noticed and fixed build errors, and its code review caught a JSON file that did not belong in the PR; says Jules behaved better than Gemini CLI.
Published Nov 11, 2025self-described: Review on forks of public repositories (websocket in Go, qwen-code in TypeScript)
Practitioner account, name and role on their organization's own page; structured test; counts toward Delivered outcomes, Operational control, Cost predictability and limits, Adoption and upkeep
On a Pro subscription, sCeege got little value from Jules: many automated tasks returned unusable output, which they suspect is Gemini's fault more than the product's.
Published Jan 28, 2026self-described: Google AI Pro subscriber who also pays for ChatGPT, Claude, and Windsurf
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
4Maintenance & choresAll 6 sources on it praise itTests, dependency bumps, documentation, small fixes, and other routine work a developer would otherwise put off.
For months Distinct-Survey475 has run four narrow nightly Jules jobs and a weekly cleanup from GitHub Actions on a monorepo; small, isolated missions stopped it from breaking the build.
Published Jul 17, 2026self-described: Astro and Cloudflare Workers monorepo, months of scheduled runs
Practitioner account, pseudonymous; ran the rollout; counts toward Delivered outcomes, Operational control, Adoption and upkeep
Yiling-J writes most code personally and uses Jules for small improvements such as refactors and tests. The output follows their style and is good enough to keep moving.
Published May 26, 2025
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
mark_l_watson had Jules write tests and other improvements twice and found the tests pretty good, with Jules building and running the changed code in its VM.
Published May 20, 2025self-described: Author and AI practitioner
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
Over three weeks on Pro, Jules cleared batched maintenance well, including 12 parallel tasks in 90 minutes, but took 8 to 15 minutes per task and twice reported unfinished work as complete.
Published May 22, 2026self-described: Solo; a Flask API and two Go microservices over three weeks
Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Operational control, Cost predictability and limits
A hiring manager who has used the popular agents, Jules included, limits them to low-severity, low-complexity work such as documentation and tests, and sees junior engineers overuse them.
Published Aug 6, 2025self-described: Hiring manager; uses several coding agents
Practitioner account, pseudonymous; direct use; not counted, takes no position
Uses Jules "religiously" and likes it: the GUI is a big plus, along with the "previewing" of produced content and using it on a phone the same as on a laptop. Asks whether others have tried Copilot or Claude Code.
Published Mar 11, 2026self-described: Daily use on phone and laptop
Practitioner account, pseudonymous; direct use; not counted, takes no position
Jules runs unit tests, linting and Playwright on its VMs, works well on mobile with notifications, and xetxov calls 100 daily tasks on Google AI Pro a fantastic deal.
Published Aug 12, 2025
Practitioner account, pseudonymous; direct use; counts toward Cost predictability and limits
versteegen calls the free tier extremely generous and praises its automated code review, but finds Jules very slow, with long silences and no usable diff viewer at the time.
Published Oct 4, 2025self-described: Independent AI researcher
Practitioner account, pseudonymous; direct use; counts toward Cost predictability and limits
Gave Jules another fair try and found it "still terrible": it stalled after plan approval, bun from the environment config vanished between steps, it called newly failing tests unrelated, and each feedback iteration took forever. Sticks with Copilot Agent, Codex and Claude Code for async work.
Published Aug 7, 2025
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
After a few prompts Jules got stuck in an endless loop with no stop button, and klipklop rates it behind Claude Code beyond basic changes.
Published Aug 6, 2025
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
Mixed
Kannan Kalidasan, Engineer and newsletter author
Artifacts #5Newsletter, The Egg Puff Engineer's Newsletter (Substack)
Building features and fixing bugs on a personal project gave solid results with clear plans up front, but testing changes outside the console was hard and the plan sometimes auto-approved.
Published Jun 1, 2025self-described: Solo; personal project
Practitioner account, self-described; direct use; counts toward Delivered outcomes, Operational control, Cost predictability and limits, Adoption and upkeep
Every concern practitioners raise, most raised first.
1Unreliable task completion24 of 25 sources on it raise it as a concernTasks that fail, loop, stall on capacity errors, or report work as done when it is not.
Running more tasks at once, evilspyboy saw far more task errors than before and suspects concurrent tasks share compute, since concurrent runs slow down together.
Published Jul 3, 2026self-described: Several concurrent tasks
Practitioner account, pseudonymous; direct use; counts toward Reliability
One daily scheduled task fired 12 times and another 6 times, using 32 of 100 daily sessions when about 11 were expected and opening 10 near-identical pull requests. The next day it recurred and completed sessions restarted.
"**Impact**: 32/100 daily sessions consumed instead of ~11. 10 near-identical PRs from task A, 6 from task B."
Excerpt, pfilbin90
Published Apr 2, 2026self-described: Runs five daily scheduled Jules tasks against a 100-session daily limit
Practitioner account, pseudonymous; direct use; counts toward Reliability, Operational control
On a Pro subscription, sCeege got little value from Jules: many automated tasks returned unusable output, which they suspect is Gemini's fault more than the product's.
Published Jan 28, 2026self-described: Google AI Pro subscriber who also pays for ChatGPT, Claude, and Windsurf
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
On a moderately difficult task, Jules declared success despite failing builds and tests, then, asked to show the tests passing, wiped its work and started over. Across 3 sessions with prompt variations it gave a bogus "mission complete" 3 times; the author says Jules "seems worse than Gemini 2.5 Pro".
Published Oct 8, 2025self-described: Three parallel sessions on a moderately difficult task
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes, Reliability
Gave Jules another fair try and found it "still terrible": it stalled after plan approval, bun from the environment config vanished between steps, it called newly failing tests unrelated, and each feedback iteration took forever. Sticks with Copilot Agent, Codex and Claude Code for async work.
Published Aug 7, 2025
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
On a side project Jules produced much worse code than GitHub Copilot, Gemini CLI or Claude Code and kept losing track of its working directory in a monorepo.
Published Aug 6, 2025self-described: Side project
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
Of 10 tasks on a small Python app, Jules finished one single-file change. Javacupix trashed or heavily fixed the rest. Roo Code on Gemini Flash found and fixed the issues in seconds.
Published May 24, 2025self-described: Small Python app, 10 tasks
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
Hit "Jules encountered an unexpected error", guessing it is "a little too popular" or compute has not been scaled, and notes "appears you have limited to 5 tasks per day".
Published May 21, 2025
Practitioner account, pseudonymous; direct use; counts toward Reliability
Over three weeks on Pro, Jules cleared batched maintenance well, including 12 parallel tasks in 90 minutes, but took 8 to 15 minutes per task and twice reported unfinished work as complete.
Published May 22, 2026self-described: Solo; a Flask API and two Go microservices over three weeks
Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Operational control, Cost predictability and limits
Finds the repo config snapshot makes setup slower, and on repos with it set up most tasks break: Jules ignores instructions, loops and goes down rabbit-holes. Suspects, as "just a hunch", a stale clone left in the snapshot, and finds no way to reset the config.
Published Sep 10, 2025self-described: Repositories with a saved setup script and snapshot
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes, Reliability, Adoption and upkeep
Juggling several Jules pull requests went badly: it could not resolve a merge conflict, and elif had to stay in the loop and ask for test results explicitly.
Published Jun 19, 2025
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
Installing large libraries such as PyTorch, or running CMake on a big repository, fills Jules's VM disk and crashes the task, with no way found to get more space.
Published Jun 4, 2025self-described: Python with PyTorch, CMake on a large repository
Practitioner account, pseudonymous; direct use; counts toward Reliability
From a phone, Simon Willison pasted a long issue thread into Jules with no other instructions. The pull request covered most requirements at a glance, though tests were failing.
Published May 19, 2025self-described: Solo; open source project issue thread
Practitioner account, self-described; direct use; counts toward Delivered outcomes
GILD's fact checks, which don't count as sources
Checked Oct 12, 2026.Google reports that the Planning Critic, a second agent added on January 26, 2026 to review auto-approved plans, cut task failure rates by 9.5%. The figure is Google's own and has no published denominator. Changelog: Introducing the Planning Critic for Auto-Approved Plans
Pull requests Jules generated on one day wrote journal entries with dates from 2025 or copied from older entries, so he corrected the dates by hand before merging.
"Dates were manually corrected to the real date before merging the PRs."
Excerpt, nickdesi
Published Aug 11, 2026self-described: Jules opens recurring performance pull requests on his MCP server repository
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
Spaccamazza1 likes that Jules takes its time, but its code is worse than Antigravity's on the same model. About one in eight Publish PR clicks does nothing. It deleted 400 lines to fix a merge conflict.
Published Jul 14, 2026self-described: Compared with Antigravity on Gemini 3.1 Pro
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes, Reliability
Even with AGENTS.md and setup scripts, Jules's code is full of bugs and it reverts Copilot reviewer fixes, so it costs bharel more time and credits than writing the code.
Published Apr 5, 2026self-described: Python repositories with AGENTS.md and setup scripts; Copilot as reviewer
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
Working with Jules feels like instructing a junior engineer: it must be told exactly what to do and checked, but pull requests make its mistakes fixable and its code reasoning is strong.
Published Mar 18, 2026self-described: Solo; maintaining Feditrends, a scraper and link ranker Nelson Minar took over
Practitioner account; direct use; counts toward Delivered outcomes, Operational control, Cost predictability and limits
The free plan's daily limit fell from 60 to 15 tasks at general availability, but esafak never neared it because fixing Jules' code took so much back and forth.
Published Aug 6, 2025self-described: Machine learning engineer
Practitioner account, pseudonymous; direct use; counts toward Cost predictability and limits
On a side project Jules produced much worse code than GitHub Copilot, Gemini CLI or Claude Code and kept losing track of its working directory in a monorepo.
Published Aug 6, 2025self-described: Side project
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
thorum almost always makes significant changes before approving a Jules pull request and has merged initially poor ones only after fixing the mistakes.
Published Jun 9, 2025
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
Using Jules for big tasks, lando2319 gets lots of wrong code but a much better start, up to a 6x boost overall, with fixing and testing the time-consuming part.
Published Jun 2, 2025
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
Gave Jules a very short prompt and calls the implementation pretty naive, with much easier-to-read approaches the author can think of, but "not _awful_" considering the prompt.
Published May 29, 2025
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
On a moderately difficult task, Jules declared success despite failing builds and tests, then, asked to show the tests passing, wiped its work and started over. Across 3 sessions with prompt variations it gave a bogus "mission complete" 3 times; the author says Jules "seems worse than Gemini 2.5 Pro".
Published Oct 8, 2025self-described: Three parallel sessions on a moderately difficult task
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes, Reliability
the_duke has run ten tasks at once from copied issue tracker items with Codex or Jules, but finds the pace unsustainable because manual fixes and cleanup are still needed.
Published Sep 24, 2025
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
Giving Jules the same Go and Python exercise as two juniors, youCanbeAPirate found it very fast at prototyping and following patterns. It was so literal that it replaced whole files when told to reuse part of one.
Published Aug 12, 2025self-described: Engineer who mentors juniors; same exercise given to two juniors and to Jules
p1nkpineapple plans features on the walk to work, sends Jules several jobs from the phone and reviews pull requests at night; most code gets rewritten, but it usually runs.
Published Aug 6, 2025self-described: Side project, a React Native app coded from a phone
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
Of 10 tasks on a small Python app, Jules finished one single-file change. Javacupix trashed or heavily fixed the rest. Roo Code on Gemini Flash found and fixed the issues in seconds.
Published May 24, 2025self-described: Small Python app, 10 tasks
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
Testing Jules on the free plan in forked websocket (Go) and qwen-code (TypeScript) repos, Heller asked it to pick and fix an open bug. On qwen-code it noticed and fixed build errors, and its code review caught a JSON file that did not belong in the PR; says Jules behaved better than Gemini CLI.
Published Nov 11, 2025self-described: Review on forks of public repositories (websocket in Go, qwen-code in TypeScript)
Practitioner account, name and role on their organization's own page; structured test; counts toward Delivered outcomes, Operational control, Cost predictability and limits, Adoption and upkeep
3GitHub workflow friction10 of 12 sources on it raise it as a concernHow Jules handles branches, pull requests, review comments, and merge conflicts, and its restriction to GitHub.
Spaccamazza1 likes that Jules takes its time, but its code is worse than Antigravity's on the same model. About one in eight Publish PR clicks does nothing. It deleted 400 lines to fix a merge conflict.
Published Jul 14, 2026self-described: Compared with Antigravity on Gemini 3.1 Pro
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes, Reliability
Juggling several Jules pull requests went badly: it could not resolve a merge conflict, and elif had to stay in the loop and ask for test results explicitly.
Published Jun 19, 2025
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
Mixed
Kannan Kalidasan, Engineer and newsletter author
Artifacts #5Newsletter, The Egg Puff Engineer's Newsletter (Substack)
Building features and fixing bugs on a personal project gave solid results with clear plans up front, but testing changes outside the console was hard and the plan sometimes auto-approved.
Published Jun 1, 2025self-described: Solo; personal project
Practitioner account, self-described; direct use; counts toward Delivered outcomes, Operational control, Cost predictability and limits, Adoption and upkeep
Jules asked for GitHub OAuth access to every repository on the account, so JoshMandel created a separate GitHub account limited to the repositories Jules should touch.
Published May 27, 2025
Practitioner account, pseudonymous; direct use; counts toward Operational control, Adoption and upkeep
Over three weeks on Pro, Jules cleared batched maintenance well, including 12 parallel tasks in 90 minutes, but took 8 to 15 minutes per task and twice reported unfinished work as complete.
Published May 22, 2026self-described: Solo; a Flask API and two Go microservices over three weeks
Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Operational control, Cost predictability and limits
Even with AGENTS.md and setup scripts, Jules's code is full of bugs and it reverts Copilot reviewer fixes, so it costs bharel more time and credits than writing the code.
Published Apr 5, 2026self-described: Python repositories with AGENTS.md and setup scripts; Copilot as reviewer
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
Testing Jules on the free plan in forked websocket (Go) and qwen-code (TypeScript) repos, Heller asked it to pick and fix an open bug. On qwen-code it noticed and fixed build errors, and its code review caught a JSON file that did not belong in the PR; says Jules behaved better than Gemini CLI.
Published Nov 11, 2025self-described: Review on forks of public repositories (websocket in Go, qwen-code in TypeScript)
Practitioner account, name and role on their organization's own page; structured test; counts toward Delivered outcomes, Operational control, Cost predictability and limits, Adoption and upkeep
maaakks was impressed by how much Jules handles almost on its own, more than Roo Code or OpenHands on Flash or local models, but expects review to become the bottleneck.
Published May 25, 2025self-described: Compared with Roo Code and OpenHands on Gemini Flash and local models
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes, Operational control
GILD's fact checks, which don't count as sources
Checked Oct 12, 2026.Since September 23, 2025, Jules reads review comments on its pull requests and pushes commits in response. Reactive Mode limits this to comments that mention @Jules. Changelog: Jules Acts on PR Feedback
Over three weeks on Pro, Jules cleared batched maintenance well, including 12 parallel tasks in 90 minutes, but took 8 to 15 minutes per task and twice reported unfinished work as complete.
Published May 22, 2026self-described: Solo; a Flask API and two Go microservices over three weeks
Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Operational control, Cost predictability and limits
versteegen calls the free tier extremely generous and praises its automated code review, but finds Jules very slow, with long silences and no usable diff viewer at the time.
Published Oct 4, 2025self-described: Independent AI researcher
Practitioner account, pseudonymous; direct use; counts toward Cost predictability and limits
After about 50 prompts across other models failed on a persistent web app bug, Jules fixed it in one attempt, though the task took well over an hour because of launch traffic.
Published May 21, 2025
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
Finds the repo config snapshot makes setup slower, and on repos with it set up most tasks break: Jules ignores instructions, loops and goes down rabbit-holes. Suspects, as "just a hunch", a stale clone left in the snapshot, and finds no way to reset the config.
Published Sep 10, 2025self-described: Repositories with a saved setup script and snapshot
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes, Reliability, Adoption and upkeep
Gave Jules another fair try and found it "still terrible": it stalled after plan approval, bun from the environment config vanished between steps, it called newly failing tests unrelated, and each feedback iteration took forever. Sticks with Copilot Agent, Codex and Claude Code for async work.
Published Aug 7, 2025
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
Running more tasks at once, evilspyboy saw far more task errors than before and suspects concurrent tasks share compute, since concurrent runs slow down together.
Published Jul 3, 2026self-described: Several concurrent tasks
Practitioner account, pseudonymous; direct use; counts toward Reliability
5VM environment setupAll 5 sources on it raise it as a concernGetting a repository's toolchain, dependencies, and commands working in Jules's cloud VM.
Finds the repo config snapshot makes setup slower, and on repos with it set up most tasks break: Jules ignores instructions, loops and goes down rabbit-holes. Suspects, as "just a hunch", a stale clone left in the snapshot, and finds no way to reset the config.
Published Sep 10, 2025self-described: Repositories with a saved setup script and snapshot
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes, Reliability, Adoption and upkeep
Gave Jules another fair try and found it "still terrible": it stalled after plan approval, bun from the environment config vanished between steps, it called newly failing tests unrelated, and each feedback iteration took forever. Sticks with Copilot Agent, Codex and Claude Code for async work.
Published Aug 7, 2025
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
Installing large libraries such as PyTorch, or running CMake on a big repository, fills Jules's VM disk and crashes the task, with no way found to get more space.
Published Jun 4, 2025self-described: Python with PyTorch, CMake on a large repository
Practitioner account, pseudonymous; direct use; counts toward Reliability
GILD's fact checks, which don't count as sources
Checked Oct 12, 2026.Google's documentation recommends a per-repository setup script, validated with Run and Snapshot so later tasks start from the saved environment. It says long-running processes such as dev servers are not supported in setup scripts. Environment setup
6Needs Close Steering3 of 7 sources on it raise it as a concernSupervision a Jules task needs to stay on track, such as restating a plan it already has approval for or staying in the loop at every step.
Working with Jules feels like instructing a junior engineer: it must be told exactly what to do and checked, but pull requests make its mistakes fixable and its code reasoning is strong.
Published Mar 18, 2026self-described: Solo; maintaining Feditrends, a scraper and link ranker Nelson Minar took over
Practitioner account; direct use; counts toward Delivered outcomes, Operational control, Cost predictability and limits
Gave Jules another fair try and found it "still terrible": it stalled after plan approval, bun from the environment config vanished between steps, it called newly failing tests unrelated, and each feedback iteration took forever. Sticks with Copilot Agent, Codex and Claude Code for async work.
Published Aug 7, 2025
Practitioner account, pseudonymous; direct use; counts toward Delivered outcomes
Juggling several Jules pull requests went badly: it could not resolve a merge conflict, and elif had to stay in the loop and ask for test results explicitly.
Published Jun 19, 2025
Practitioner account, pseudonymous; direct use; not counted, repeats a stronger account
Over three weeks on Pro, Jules cleared batched maintenance well, including 12 parallel tasks in 90 minutes, but took 8 to 15 minutes per task and twice reported unfinished work as complete.
Published May 22, 2026self-described: Solo; a Flask API and two Go microservices over three weeks
Practitioner account, self-described; direct use; counts toward Delivered outcomes, Reliability, Operational control, Cost predictability and limits
Testing Jules on the free plan in forked websocket (Go) and qwen-code (TypeScript) repos, Heller asked it to pick and fix an open bug. On qwen-code it noticed and fixed build errors, and its code review caught a JSON file that did not belong in the PR; says Jules behaved better than Gemini CLI.
Published Nov 11, 2025self-described: Review on forks of public repositories (websocket in Go, qwen-code in TypeScript)
Practitioner account, name and role on their organization's own page; structured test; counts toward Delivered outcomes, Operational control, Cost predictability and limits, Adoption and upkeep
Questions the sources split on, with the count on each side.
Evidence remains mixed
Should Jules work as a hands-off cloud agent, or do developers get more from an interactive agent for the same work?
76
Hands-off delegation, 7 sources
Some prefer Jules's isolated cloud VM and pull request workflow, often directing it from a phone.
Interactive tools, 6 sources
Others found Claude Code, Copilot, or Gemini CLI produced better code for the same work.
Evidence remains mixed
How much work should Jules take on before a human checkpoint?
46
Broader delegation, 4 sources
Some hand Jules whole features or run it in a loop that merges its own pull requests after checks pass.
Tighter steering, 6 sources
Others write most of the code themselves and keep Jules on refactors, tests, and small improvements.
Evidence remains mixed
Once review and rework are counted, does Jules reduce total engineering time?
33
Net time saved, 3 sources
Some report features that would take weeks finished in hours, or a client handling small changes alone.
Absorbed by review, 3 sources
Others spent more time understanding and fixing Jules's pull requests than the work would have taken.
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 All practitioners. Leaders and teams have 2 accounts; GILD prints their sentiment from 20.
Engineering leaders and teams
4 sources. These accounts focus on team rollout, review load, account administration, and what changes when Jules moves from one developer to a team.
Individual builders
79 sources. These accounts focus on whether a task finishes, how long it takes, what the free tier and Google AI plans allow, and how Jules compares with interactive agents.
All practitioners
83 sources. These accounts give the broadest read. They mix solo and team settings, which can reach different conclusions about Jules.
83 sources from practitioners, by the context they work in. Filled rows count for this group.
Individual practitionerSolo developers and independent builders79 sources, counted here
Emphasizes Whether a task finishes and what the plan allows
Very small team2 to 10 engineers2 sources, counted here
Emphasizes Who opens tasks and who reviews the pull requests
Professional team11 to 50 engineers, or a named company's teamNo sources from this setting yet
Technical leadershipLeaders setting adoption across teams2 sources, counted here
Emphasizes Which work to delegate and how much to trust it
Organization-wideEnterprise or company-wide rolloutNo sources from this setting yet
What changes with scale. Almost every public account of Jules comes from one developer working on their own repository. Team use needs a pilot: the public record lacks team accounts, and Google sells paid Jules plans only to personal Google accounts.
Where the sources come from
Where this group's sources were published.
Counted for All practitioners, from 83 sources. Change group
97 sources for this group, 14 of them documentation
Developer communities76, 78% of 97 sources
Product documentation14, 14% of 97 sources
Engineering blogs & reviews7, 7% of 97 sources
Older evidence is retained when it still applies. Sources that depend on a changed plan, limit, or model stay in the history, marked Needs a recheck.
Nov 1, 2026: by the owner's decision, a record whose own words state no overall view of Jules now casts no vote; it still counts toward its topics and is listed, and 8 records that counted leave the vote this way. Leaders and teams stay unscored, individual builders move from 0 to −2 and all practitioners from +1 to 0.
Oct 31, 2026: rewrote 8 summaries that two blind coders found overstated their sources, so each says what its source says. An error report and Sheffield's pull request state no view of Jules overall and now count toward no figure. Individual builders move from +3 to +4 and all practitioners from +7 to +5.
Each source links to an English-language page dated 2025 or later and names its author and publication date.
The page shows a finding only when at least 5 sources from 3 different authors discuss it. A disagreement requires at least 2 sources on each side.
Lists the written-instructions statement (4 sources) and the junior-engineer and review-capacity statements (3 each) in Evidence & Methodology with their counts, since each has fewer than 5 sources from 3 authors. Data handling and task limits come from Google's documentation in the Data & GitHub Access and Plans & Limits guides.
Oct 25, 2026: added Needs Close Steering, drawn from accounts already on the page. 3 say Jules needs supervision to stay on track and 4 describe steering it lightly or not at all.
Oct 25, 2026: added Fast Runs from one existing account and one new Hacker News account that praise how fast Jules returns work, and one existing review that calls it slow.
Checks every documentation page against Google's current Jules docs. They still show Gemini 2.5 Pro for the free plan, although the changelog made Gemini 3 Flash the base model on January 30, 2026.
Oct 25, 2026: added 2 GitHub issues on Google's Jules repositories, one measuring duplicate scheduled runs and one on dates Jules invents in its journal files, and Johann Rehberger's independent security test.
Method
A running review of what engineering teams report about Jules, from individual builders to engineering leaders. 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, all practitioners read +5 mixed (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 +7 Mixed; with one vote per author it read +1 Mixed. 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 +1 Mixed and now reads 0 Mixed.
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 2, individual builders 18 of 66, all practitioners 18 of 68.
Limits
GILD reviewed 83 public sources: 51 Hacker News comments, 22 Reddit posts and comments, 6 English blogs, newsletters, and reviews, 2 GitHub issues, a GitHub pull request, and 1 independent security test. Nearly every account comes from an individual developer. Four speak for more than one person, two small teams, a hiring manager and a university lab's principal investigator, and none covers a company-wide rollout, which fits Google selling paid plans only to personal Google accounts. The counts describe this reviewed set, so a team should confirm fit by queuing its own scoped tasks on the free tier.
Sources record the plan, model, and product stage inconsistently. Each source shows what it states. Sources from the public beta (before August 6, 2025), when limits were 5 to 60 tasks a day on Gemini 2.5 Pro, are marked Needs a recheck. Sources from before Gemini 3 Flash became the base model on January 30, 2026 are marked Still applicable.
Every count, and the sources behind it
21 findings for 3 groups
Each row opens its sources for the group you are reading.
GitHub workflow friction. Since September 23, 2025, Jules reads review comments on its pull requests and pushes commits in response. Reactive Mode limits this to comments that mention @Jules. Changelog: Jules Acts on PR Feedback, checked Oct 12, 2026
VM environment setup. Google's documentation recommends a per-repository setup script, validated with Run and Snapshot so later tasks start from the saved environment. It says long-running processes such as dev servers are not supported in setup scripts. Environment setup, checked Oct 12, 2026