Up to now few weeks, a number of “autonomous background coding brokers” have been launched.
- Supervised coding brokers: Interactive chat brokers which are 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 just ship off to work autonomously via a complete job. Code will get created in an surroundings spun up completely for that agent, and often leads to 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 can assist you look behind the scenes and draw your individual conclusions, adopted by a few of my very own observations.
The duty
We now have 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 situation:
Precise:
What I wished from the agent:
Immediate: Once we create the filter labels on the dashboard, we create human readable labels based mostly on the classes we've got. "client-research" is became "Shopper-Analysis", "deliveryManagement" into "DeliveryManagement". Enhance the sophistication of the "category-to-human-readable" logic in order that the labels are showing to the consumer as "Shopper Analysis" and "Supply Administration"
This job is
- Comparatively small
- A typical “cosmetics” job that’s not tremendous pressing and may get deprioritised time and again
Agent logs
I’m sharing the detailed logs right here with the intention to get an impression of what’s going on beneath the hood.
Right here’s what the logs view seems like in Codex:
Amassing data first
The primary 17 log entries have been all about studying AGENTS.md and README.md:
- “I must verify the AGENTS.md within the repository root for directions.”
- seems for AGENTS.md, however I had truly referred to as it AGENT.md, which led to some forwards and backwards till it figured that out
- reads README.md
- Appears to be like at .pre-commit, finds a take a look at setup
The next tables record 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 certain 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 manner too quick to characterize the complete “considering” the mannequin will need to have been going via.
Trying to find the related code with a number of grep
| Message | Command (samples) | Notes |
|---|---|---|
| I must 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 mission. | ||
| Grep output is very large 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’m wondering 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 believe the logic may be lacking, so I’ll verify _navigation_items and different modules for classes. | grep -R "human" app -n | head |
|
| I believe 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 as a consequence of hyphen or camelCase; I’ll take 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 the way classes are formatted, specializing in hyphens and camelCase. | grep -R "classes" -n app | head |
|
| Time to attempt a brand new search! | grep -R "shopper" -n app | head |
|
| I’ll take a better take a look at the prompts within the take a look at information. | grep -R "classes:" -n app/exams | head |
Why? |
| It seems just like the take a look at 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 within the ui folder – it discovered the CSS beforehand, and is now searching for current code that it could reuse to resolve 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 would like a perform to transform tags like “client-research” to “Shopper 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 would like. |
It now finds a spot within the current perform’s implementation:
| Message | Command (samples) | Notes |
|---|---|---|
| I see that hyphens aren’t dealt with by the perform. I would like to regulate it for hyphens. | ||
| I’ll modify toReadableText to deal with hyphens, guaranteeing correct capitalization and spacing. Let’s verify exams! | It truly didn’t verify any exams | |
| I’ll verify _dynamic_data_renderer.js to look at toReadableText and modify it for hyphen-case. | ||
| I’ll verify exams/_sidebar.take a look at.js to evaluation the associated classes there. | ||
| I’ll verify different information to see if toReadableText seems anyplace. | ||
| I’ll verify if _sidebar or others include a toReadableText perform. |
Replace the take a look at for the perform that it desires to alter:
| Message | Command (samples) | Notes |
|---|---|---|
| I’ll regulate the perform to deal with hyphen-case, then replace exams to mirror that. | ||
| I’ll verify the take a look at file after line 36 to make sure hyphen-case is roofed. | ||
| I’ll scroll via traces 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 exams for hyphen-case and replace toReadableText, together with modifying index.js for classes. | ||
| I’ll regulate _dynamic_data_renderer.js and index.js to make use of toReadableText and replace exams. | git standing --short |
You may configure some surroundings 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 basis of ‘ui’ and take away any pointless Yarn 4 entries. | ||
| I’ll take a look at the commit historical past to see if these .yarn information have been added later. | git log --oneline -n 1 |
|
| I’ll evaluation 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 seems 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 mandatory updates now. | sed -n '1,30p' ... |
|
| I’m going so as to add a hyphen to the mandatory 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 regulate the _dynamic_data_renderer exams. | ||
| I would like to exchange {tag} with {toReadableText(tag)} for higher rendering. | ||
| I’ll check out the variations to higher perceive the modifications. | git diff |
|
| I’ll evaluation the modifications in index.js to see what’s been modified. | ||
| I’ll add a brand new take a look at for hyphenated circumstances in _dynamic_data_renderer.take a look at.js. | ||
| I’ll think about inserting a take a look at 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 evaluation the logs to collect extra data. |
Making an attempt to run the exams – unsuccessfully:
| Message | Command (samples) | Notes |
|---|---|---|
| I’ll run the yarn exams to verify if all the pieces’s working high quality. | ||
| Assessments may’ve been cached or want community—output’s empty, so I’ll verify the log. | ||
| The lockfile isn’t up to date. I’ll attempt working ‘yarn set up’ for the reason that surroundings permits it. | ||
| The surroundings 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 exams failed. | ||
| The error occurs as a result of Yarn 4 depends on .yarn and .yarnrc, which we eliminated. | ? | |
| It seems 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 title. | ? | |
| 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 believe switching to npx vitest run may repair the error. Let’s attempt that. | ||
| The output is lengthy—now I’ll seize the final abstract traces. | Error: Not carried out: window.getComputedStyle(elt, pseudoElt) |
|
| The output is just too lengthy, so I’ll extract the important thing factors for a abstract. |
Occurring a tangent about establishing the venv, which is completely pointless as a result of it solely plans modifications for frontend code:
| Message | Command (samples) | Notes |
|---|---|---|
| The exams failed as a consequence of case variations, however now I’ll activate the digital surroundings. | AGENTS.md incorporates 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 seems just like the .venv listing is lacking. Let’s evaluation AGENT’s directions fastidiously. | ||
| The surroundings appears offline, however there may 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 exams with the present setup, however I’ll attempt pytest anyway. |
Gave up on the exams, now wrapping up the modifications:
| Message | Command (samples) | Notes |
|---|---|---|
| Assessments failed as a consequence of lacking dependencies. Now, I’ll verify standing and proceed with committing. | ||
| I believe the .yarnrc.yml was left over from a earlier yarn set up. Eradicating it. | ||
| I’ll seize the related file traces 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 traces round these modifications now. | ||
| It’s time to finalize the PR message and confirm the commit. | ||
| UI exams failed as a consequence of surroundings points. I’ll reference the final failure traces. Accomplished! |
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 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 plenty of seemingly extra refined code search mechanisms carried out, 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 continues to be fairly easy, however doing textual content search with grep is the only potential.
It looks as if the instrument creators have discovered that this easy search continues to be the simplest in spite of everything – ? Or they’re making some type of trade-off right here, between simplicity and effectiveness?
The distant dev surroundings is vital for these brokers to work “within the background”
Here’s a screenshot of Codex’s surroundings configuration display (as of finish of Might 2025). As of now, you may configure a container picture, surroundings variables, secrets and techniques, and a startup script. They level out that after the execution of that startup script, the surroundings won’t have entry to the web anymore, which might sandbox the surroundings and mitigate a few of the safety dangers.
For these “autonomous background brokers”, the maturity of the distant dev surroundings that’s arrange for the agent is essential, and it’s a difficult problem. On this case e.g., Codex didn’t handle to run the exams.
And it turned out that when the pull request was created, there have been certainly two exams failing due to regression, which is a disgrace, as a result of if it had identified, it will have simply been capable of repair the exams, it was a trivial repair:
This specific mission, Haiven, truly has a scripted developer security internet, within the type of a fairly elaborate .pre-commit configuration. () It will be best if the agent may execute the complete pre-commit earlier than even making a pull request. Nevertheless, to run all of the steps, it will must run
- Node and yarn (to run UI exams and the frontend linter)
- Python and poetry (to run backend exams)
- 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, in fact.
Determining a clean expertise to spin up simply the fitting surroundings 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 spite of everything we do that in CI pipelines on a regular basis. But it surely’s additionally not trivial, and in the mean time my impression is that surroundings maturity continues to be a difficulty in most of those merchandise, and the consumer expertise to configure and take a look at the surroundings setups is as irritating, if no more, as it may be for CI pipelines.
Resolution 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 all the pieces). Though this was a comparatively easy job and answer, turns on the market have been high quality variations between the outcomes.
Excellent news first, the brokers got here up with a working answer each time (leaving breaking regression exams apart, and to be sincere I didn’t truly run each single one of many options to verify). I believe this job is an effective 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 elements that differed by way of high quality of the answer:
- Discovery of current code that could possibly be reused: Within the log right here you’ll discover that Codex discovered an current element, 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 a further place that ought to use this logic: The staff is at present engaged on a brand new characteristic that additionally shows class names to the consumer, in a dropdown. In one of many 6 runs, the agent truly found that and prompt 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 needs to 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’ve got a number of dimensions of high quality, of issues that we need to “go proper”. Every agent run can “go fallacious” in a single or a number of of those dimensions, and the extra dimensions there are, the much less possible it’s that an agent will get all the pieces achieved the best way we wish it.
Sunk value fallacy
I’ve been questioning – let’s say a staff makes use of background brokers for this kind of job, the varieties of duties which are type of small, and neither necessary nor pressing. Haiven is an internal-facing software, and has solely two builders assigned in the mean time, so this kind of beauty repair is definitely thought-about low precedence because it takes developer capability away from extra necessary issues. When an agent solely type of succeeds, however not totally – by which conditions would a staff discard the pull request, and by which 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 marvel in regards to the tail finish of unprioritised effort we’d find yourself with.
