Prior to now few weeks, a number of “autonomous background coding brokers” have been launched.
- Supervised coding brokers: Interactive chat brokers which might be pushed and steered by a developer. Create code regionally, within the IDE. Instrument examples: GitHub Copilot, Windsurf, Cursor, Cline, Roo Code, Claude Code, Aider, Goose, …
- Autonomous background coding brokers: Headless brokers that you simply ship off to work autonomously via an entire job. Code will get created in an setting spun up solely for that agent, and normally ends in a pull request. A few of them are also runnable regionally although. Instrument examples: OpenAI Codex, Google Jules, Cursor background brokers, Devin, …
I gave a job to OpenAI Codex and another brokers to see what I can study. The next is a file of 1 specific Codex run, that will help you look behind the scenes and draw your personal conclusions, adopted by a few of my very own observations.
The duty
We’ve got an inner software referred to as Haiven that we use as a demo frontend for our software program supply immediate library, and to run some experiments with totally different AI help experiences on software program groups. The code for that software is public.
The duty I gave to Codex was relating to the next UI concern:
Precise:
What I wished from the agent:
Immediate: After we create the filter labels on the dashboard, we create human readable labels primarily based on the classes we now have. "client-research" is changed into "Consumer-Analysis", "deliveryManagement" into "DeliveryManagement". Enhance the sophistication of the "category-to-human-readable" logic in order that the labels are showing to the person as "Consumer Analysis" and "Supply Administration"
This job is
- Comparatively small
- A typical “cosmetics” job that’s not tremendous pressing and would possibly get deprioritised time and again
Agent logs
I’m sharing the detailed logs right here to be able to get an impression of what’s going on below the hood.
Right here’s what the logs view appears to be like like in Codex:
Accumulating data first
The primary 17 log entries have been all about studying AGENTS.md and README.md:
- “I have to verify the AGENTS.md within the repository root for directions.”
- appears to be like for AGENTS.md, however I had truly referred to as it AGENT.md, which led to some backwards and forwards till it figured that out
- reads README.md
- Seems at .pre-commit, finds a check setup
The next tables listing the remainder of the log messages verbatim. After every of these messages, the agent executed a command, for a few of them I added that precise command for context. I’m positive that the log messages are simply summaries of the tokens that have been truly happening behind the scenes, as a result of the messages are means too quick to characterize the complete “considering” the mannequin should have been going via.
Trying to find the related code with plenty of grep
| Message | Command (samples) | Notes |
|---|---|---|
| I have to seek for “category-to-human-readable” to find the place to make modifications for the frontend labels. | grep -R "human readable" -n | |
| I’ll search for any mentions of “class” within the challenge. | ||
| Grep output is huge due to node_modules; I’ll restrict it to src as an alternative. | ||
| I’ll seek for “to human” within the src listing to search out related references. | ||
| I’ll open and verify index.js to see what’s inside. | ||
| I’m checking if the category-to-human-readable transformation is dealt with in _navigation_items or elsewhere. | ||
| I’m going to search for “human readable” to get extra information on the subject. | grep -R "human-readable" -n ui/src | head | |
| I ponder if there’s a perform for changing classes into one thing extra readable. | ||
| Filtering the search to simply the “src” folder to keep away from node_modules noise. | second time it’s working into this, didn’t ‘keep in mind’ | |
| I’ll search for a perform like “toHumanReadable”. Let’s see what I discover. | ||
| I’m checking the entire repo in case the logic is within the backend or a library. | grep -R "Human" -n | head | |
| I’ll restrict the scope to app/ and ui/src to keep away from the massive node_modules folder. | third time it’s working into this, didn’t ‘keep in mind’ | |
| I feel the logic could be lacking, so I’ll verify _navigation_items and different modules for classes. | grep -R "human" app -n | head | |
| I feel it’s time to look a bit deeper. Let’s dive in and discover. | grep -R "human" app | wc -l | To “look deeper”, it searches for “human” once more, however pipes it into wc as an alternative of head? |
Lastly, it’s getting nearer! The labels have been beforehand crudely capitalized through CSS, it finds that
| Message | Command (samples) | Notes |
|---|---|---|
| I’m checking for references to “capitalize” or class transformation within the frontend. | Output: | |
| I’ll verify across the Tag part in index.js. | ||
| Tag show capitalizes phrases incorrectly resulting from hyphen or camelCase; I’ll have a look at filter classes. |
Now it’s beginning to verify for extra related code within the app folder, the place the backend is. It doesn’t discover something, which is right, there’s nothing related there
| Message | Command (samples) | Notes |
|---|---|---|
| I’ll verify the repo for a way classes are formatted, specializing in hyphens and camelCase. | grep -R "classes" -n app | head | |
| Time to strive a brand new search! | grep -R "consumer" -n app | head | |
| I’ll take a better have a look at the prompts within the check information. | grep -R "classes:" -n app/assessments | head | Why? |
| It appears to be like just like the check information has restricted classes. I’ll verify the docs for any variations. | grep -R "client-research" -n | |
| I’ll begin by opening the information to take a better look. | sed -n '1,100p' ui/src/app/_navigation_items.js |
Now it’s going again to looking out within the ui folder – it discovered the CSS beforehand, and is now on the lookout for present code that it could possibly reuse to unravel the duty. That’s nice, as a result of we certainly have already got an identical perform, and it finds it:
| Message | Command (samples) | Notes |
|---|---|---|
| I want a perform to transform tags like “client-research” to “Consumer Analysis” for filters. | grep -R "to.*Readable" -n ui/src | head | |
| I’m opening the toReadableText perform inside _dynamic_data_renderer.js to discover it. | ||
| I’m transferring via the web page to get the small print I want. |
It now finds a niche within the present perform’s implementation:
| Message | Command (samples) | Notes |
|---|---|---|
| I see that hyphens aren’t dealt with by the perform. I want to regulate it for hyphens. | ||
| I’ll modify toReadableText to deal with hyphens, making certain correct capitalization and spacing. Let’s verify assessments! | It truly didn’t verify any assessments | |
| I’ll verify _dynamic_data_renderer.js to look at toReadableText and modify it for hyphen-case. | ||
| I’ll verify assessments/_sidebar.check.js to assessment the associated classes there. | ||
| I’ll verify different information to see if toReadableText seems wherever. | ||
| I’ll verify if _sidebar or others include a toReadableText perform. |
Replace the check for the perform that it desires to vary:
| Message | Command (samples) | Notes |
|---|---|---|
| I’ll modify the perform to deal with hyphen-case, then replace assessments to replicate that. | ||
| I’ll verify the check file after line 36 to make sure hyphen-case is roofed. | ||
| I’ll scroll via strains 60 to 120 to look at the remainder of the file. | ||
| I’m scrolling the remaining to seize all of the related data. | ||
| I’ll add assessments for hyphen-case and replace toReadableText, together with modifying index.js for classes. | ||
| I’ll modify _dynamic_data_renderer.js and index.js to make use of toReadableText and replace assessments. | git standing --short |
You possibly can configure some setting startup instructions in Codex, I had configured that to be yarn set up, which led to the next:
| Message | Command (samples) | Notes |
|---|---|---|
| There are untracked .yarn/ and .yarnrc information. I’ll verify and clear them up. | ||
| I’ll verify the foundation of ‘ui’ and take away any pointless Yarn 4 entries. | ||
| I’ll have a look at the commit historical past to see if these .yarn information have been added later. | git log --oneline -n 1 | |
| I’ll assessment the repository’s .gitignore to verify if Node modules are excluded. | grep yarn .gitignore | |
| I see no entry for .yarn or .yarnrc. I’ll verify and take away them if wanted. | cat ui/.gitignore | |
| I’ll verify if I can take away .yarn or .yarnrc information since they shouldn’t be dedicated. | ||
| It appears to be like like yarn.lock modifications have been made. Time to reset to HEAD. |
Precise code modifications:
| Message | Command (samples) | Notes |
|---|---|---|
| Time to change the code. I’ll start the required updates now. | sed -n '1,30p' ... | |
| I’m going so as to add a hyphen to the required a part of the code. | ||
| I’m going to make modifications to the index.js file now. | ||
| I’ll import toReadableText and begin utilizing it within the code. | ||
| I’ll replace index.js to import toReadableText and modify the _dynamic_data_renderer assessments. | ||
| I want to interchange {tag} with {toReadableText(tag)} for higher rendering. | ||
| I’ll check out the variations to higher perceive the modifications. | git diff | |
| I’ll assessment the modifications in index.js to see what’s been modified. | ||
| I’ll add a brand new check for hyphenated circumstances in _dynamic_data_renderer.check.js. | ||
| I’ll think about inserting a check after line 35. |
Operating our code linter subsequent, good:
| Message | Command (samples) | Notes |
|---|---|---|
| I’ll format the code utilizing Prettier as instructed. | cd ui && npx prettier -w ... | Prettier is talked about within the AGENTS.md. It appears to run prettier efficiently, although not one of the information have been modified |
| I’ll assessment the logs to collect extra data. |
Attempting to run the assessments – unsuccessfully:
| Message | Command (samples) | Notes |
|---|---|---|
| I’ll run the yarn assessments to verify if every thing’s working advantageous. | ||
| Checks would possibly’ve been cached or want community—output’s empty, so I’ll verify the log. | ||
| The lockfile isn’t up to date. I’ll strive working ‘yarn set up’ because the setting permits it. | ||
| The setting is offline, so yarn set up can’t be run, however I see a node_modules folder. | ||
| I see node_modules are already put in. I’ll verify the log for why assessments failed. | ||
| The error occurs as a result of Yarn 4 depends on .yarn and .yarnrc, which we eliminated. | ? | |
| It appears to be like like .yarnrc.yml isn’t tracked. I’ll additionally verify .yarn for monitoring. | ||
| I’m double-checking the bundle.json to see if “haiven-ui” is the proper identify. | ? | |
| I’ll verify the Node model to verify if it’s 18 or 20 by working node -v. | bizarre, the node model laid out in bundle.json is 22.6 | |
| I feel switching to npx vitest run might repair the error. Let’s strive that. | ||
| The output is lengthy—now I’ll seize the final abstract strains. | Error: Not applied: window.getComputedStyle(elt, pseudoElt) | |
| The output is simply too lengthy, so I’ll extract the important thing factors for a abstract. |
Occurring a tangent about organising the venv, which is completely pointless as a result of it solely plans modifications for frontend code:
| Message | Command (samples) | Notes |
|---|---|---|
| The assessments failed resulting from case variations, however now I’ll activate the digital setting. | AGENTS.md comprises directions to activate venv for the Python backend, however we’re within the frontend right here, so… | |
| Hmm, the .venv isn’t right here. I ought to verify if it wants creation or already exists. | ||
| It appears to be like just like the .venv listing is lacking. Let’s assessment AGENT’s directions fastidiously. | ||
| The setting appears offline, however there could be a script to arrange dependencies regionally. | ||
| I can’t run “poetry set up” offline, however I’ll verify the .cursor folder for dependencies. | ||
| I can’t run backend assessments with the present setup, however I’ll strive pytest anyway. |
Gave up on the assessments, now wrapping up the modifications:
| Message | Command (samples) | Notes |
|---|---|---|
| Checks failed resulting from lacking dependencies. Now, I’ll verify standing and proceed with committing. | ||
| I feel the .yarnrc.yml was left over from a earlier yarn set up. Eradicating it. | ||
| I’ll seize the related file strains for the citations now. | ||
| I’ll get the encompassing line vary for the modifications in index.js. | nl -ba ui/src/pages/index.js | sed -n '12,28p' | |
| I’ll seize the related strains round these modifications now. | ||
| It’s time to finalize the PR message and confirm the commit. | ||
| UI assessments failed resulting from setting points. I’ll reference the final failure strains. Carried out! |
Right here is the complete pull request created by Codex.
Observations
Brute textual content search
I discovered it fascinating to see that Codex, and many of the different coding assistants I’m utilizing, are resorting increasingly more to easy textual content search to search out related code. Within the log above you see how Codex goes via a bunch of search phrases with grep, to search out related items of code (“human”, “human readable”, “humanReadable”, …). The explanation why I discover it fascinating is as a result of there have been a variety of seemingly extra refined code search mechanisms applied, like semantic search over codebase indices with vectors / embeddings (Cursor, GH Copilot, Windsurf), or utilizing the summary syntax tree as a place to begin (Aider, Cline). The latter remains to be fairly easy, however doing textual content search with grep is the only attainable.
It looks as if the instrument creators have discovered that this easy search remains to be the best in any case – ? Or they’re making some form of trade-off right here, between simplicity and effectiveness?
The distant dev setting is vital for these brokers to work “within the background”
Here’s a screenshot of Codex’s setting configuration display screen (as of finish of Might 2025). As of now, you’ll be able to configure a container picture, setting variables, secrets and techniques, and a startup script. They level out that after the execution of that startup script, the setting is not going to have entry to the web anymore, which might sandbox the setting and mitigate among the safety dangers.
For these “autonomous background brokers”, the maturity of the distant dev setting that’s arrange for the agent is essential, and it’s a tough problem. On this case e.g., Codex didn’t handle to run the assessments.
And it turned out that when the pull request was created, there have been certainly two assessments failing due to regression, which is a disgrace, as a result of if it had identified, it could have simply been in a position to repair the assessments, it was a trivial repair:
This specific challenge, Haiven, truly has a scripted developer security internet, within the type of a fairly elaborate .pre-commit configuration. () It could be best if the agent might execute the complete pre-commit earlier than even making a pull request. Nevertheless, to run all of the steps, it could have to run
- Node and yarn (to run UI assessments and the frontend linter)
- Python and poetry (to run backend assessments)
- Semgrep (for security-related static code evaluation)
- Ruff (Python linter)
- Gitleaks (secret scanner)
…and all of these must be out there in the fitting variations as nicely, after all.
Determining a easy expertise to spin up simply the fitting setting for an agent is vital for these agent merchandise, if you wish to actually run them “within the background” as an alternative of a developer machine. It isn’t a brand new drawback, and to an extent a solved drawback, in any case we do that in CI pipelines on a regular basis. But it surely’s additionally not trivial, and in the meanwhile my impression is that setting maturity remains to be a difficulty in most of those merchandise, and the person expertise to configure and check the setting setups is as irritating, if no more, as it may be for CI pipelines.
Answer high quality
I ran the identical immediate 3 instances in OpenAI Codex, 1 time in Google’s Jules, 2 instances regionally in Claude Code (which isn’t totally autonomous although, I wanted to manually say ‘sure’ to every thing). Although this was a comparatively easy job and resolution, turns on the market have been high quality variations between the outcomes.
Excellent news first, the brokers got here up with a working resolution each time (leaving breaking regression assessments apart, and to be trustworthy I didn’t truly run each single one of many options to verify). I feel this job is an efficient instance of the kinds and sizes of duties that GenAI brokers are already nicely positioned to work on by themselves. However there have been two facets that differed when it comes to high quality of the answer:
- Discovery of present code that may very well be reused: Within the log right here you’ll discover that Codex discovered an present part, the “dynamic information renderer”, that already had performance for turning technical keys into human readable variations. Within the 6 runs I did, solely 2 instances did the respective agent discover this piece of code. Within the different 4, the brokers created a brand new file with a brand new perform, which led to duplicated code.
- Discovery of an extra place that ought to use this logic: The workforce is presently engaged on a brand new characteristic that additionally shows class names to the person, in a dropdown. In one of many 6 runs, the agent truly found that and instructed to additionally change that place to make use of the brand new performance.
| Discovered the reusable code | Went the additional mile and located the extra place the place it must be used |
|---|---|
| Sure | Sure |
| Sure | No |
| No | Sure |
| No | No |
| No | No |
| No | No |
I put these outcomes right into a desk as an instance that in every job given to an agent, we now have a number of dimensions of high quality, of issues that we need to “go proper”. Every agent run can “go improper” in a single or a number of of those dimensions, and the extra dimensions there are, the much less probably it’s that an agent will get every thing performed the best way we would like it.
Sunk price fallacy
I’ve been questioning – let’s say a workforce makes use of background brokers for this sort of job, the sorts of duties which might be form of small, and neither necessary nor pressing. Haiven is an internal-facing software, and has solely two builders assigned in the meanwhile, so this sort of beauty repair is definitely thought-about low precedence because it takes developer capability away from extra necessary issues. When an agent solely form of succeeds, however not totally – wherein conditions would a workforce discard the pull request, and wherein conditions would they make investments the time to get it the final 20% there, despite the fact that spending capability on this had been deprioritised? It makes me surprise concerning the tail finish of unprioritised effort we’d find yourself with.
