Prior to now few weeks, a number of “autonomous background coding brokers” have been launched.
- Supervised coding brokers: Interactive chat brokers which can be pushed and steered by a developer. Create code domestically, within the IDE. Device 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 by means of a complete job. Code will get created in an setting spun up completely for that agent, and often leads to a pull request. A few of them are also runnable domestically although. Device examples: OpenAI Codex, Google Jules, Cursor background brokers, Devin, …
I gave a job to OpenAI Codex and another brokers to see what I can be taught. The next is a report of 1 specific Codex run, that will help 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 inside utility known as Haiven that we use as a demo frontend for our software program supply immediate library, and to run some experiments with completely different AI help experiences on software program groups. The code for that utility is public.
The duty I gave to Codex was concerning the next UI situation:
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 "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 isn’t tremendous pressing and would possibly get deprioritised many times
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 appears like in Codex:
Accumulating info first
The primary 17 log entries have been all about studying AGENTS.md and README.md:
- “I must test the AGENTS.md within the repository root for directions.”
- appears for AGENTS.md, however I had truly known as it AGENT.md, which led to some backwards and forwards 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 method too quick to signify the total “considering” the mannequin should have been going by means of.
Looking for the related code with numerous 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 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 test 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 lookup “human readable” to get extra data on the subject. | grep -R "human-readable" -n ui/src | head | |
| I ponder if there’s a operate for changing classes into one thing extra readable. | ||
| Filtering the search to only the “src” folder to keep away from node_modules noise. | second time it’s operating into this, didn’t ‘keep in mind’ | |
| I’ll search for a operate 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 big node_modules folder. | third time it’s operating into this, didn’t ‘keep in mind’ | |
| I believe the logic is perhaps lacking, so I’ll test _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 test across the Tag part in index.js. | ||
| Tag show capitalizes phrases incorrectly because of hyphen or camelCase; I’ll take a look at filter classes. |
Now it’s beginning to test for extra related code within the app folder, the place the backend is. It doesn’t discover something, which is appropriate, there’s nothing related there
| Message | Command (samples) | Notes |
|---|---|---|
| I’ll test the repo for the way classes are formatted, specializing in hyphens and camelCase. | grep -R "classes" -n app | head | |
| Time to strive 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 knowledge. | grep -R "classes:" -n app/assessments | head | Why? |
| It appears just like the take a look at knowledge has restricted classes. I’ll test 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 actually reuse to resolve the duty. That’s nice, as a result of we certainly have already got an identical operate, and it finds it:
| Message | Command (samples) | Notes |
|---|---|---|
| I would like a operate to transform tags like “client-research” to “Shopper Analysis” for filters. | grep -R "to.*Readable" -n ui/src | head | |
| I’m opening the toReadableText operate inside _dynamic_data_renderer.js to discover it. | ||
| I’m shifting by means of the web page to get the small print I would like. |
It now finds a niche within the present operate’s implementation:
| Message | Command (samples) | Notes |
|---|---|---|
| I see that hyphens aren’t dealt with by the operate. I would like to regulate it for hyphens. | ||
| I’ll modify toReadableText to deal with hyphens, making certain correct capitalization and spacing. Let’s test assessments! | It truly didn’t test any assessments | |
| I’ll test _dynamic_data_renderer.js to look at toReadableText and modify it for hyphen-case. | ||
| I’ll test assessments/_sidebar.take a look at.js to assessment the associated classes there. | ||
| I’ll test different information to see if toReadableText seems anyplace. | ||
| I’ll test if _sidebar or others include a toReadableText operate. |
Replace the take a look at for the operate that it needs to alter:
| Message | Command (samples) | Notes |
|---|---|---|
| I’ll modify the operate to deal with hyphen-case, then replace assessments to replicate that. | ||
| I’ll test the take a look at file after line 36 to make sure hyphen-case is roofed. | ||
| I’ll scroll by means of traces 60 to 120 to look at the remainder of the file. | ||
| I’m scrolling the remainder to seize all of the related info. | ||
| 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 may 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 test and clear them up. | ||
| I’ll test the foundation 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 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 test and take away them if wanted. | cat ui/.gitignore | |
| I’ll test if I can take away .yarn or .yarnrc information since they shouldn’t be dedicated. | ||
| It appears 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 would like to exchange {tag} with {toReadableText(tag)} for higher rendering. | ||
| I’ll check out the variations to raised 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 take a look at for hyphenated instances in _dynamic_data_renderer.take a look at.js. | ||
| I’ll contemplate inserting a take a look at after line 35. |
Working 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 assemble extra info. |
Making an attempt to run the assessments – unsuccessfully:
| Message | Command (samples) | Notes |
|---|---|---|
| I’ll run the yarn assessments to test if the whole lot’s working effective. | ||
| Checks would possibly’ve been cached or want community—output’s empty, so I’ll test the log. | ||
| The lockfile isn’t up to date. I’ll strive operating ‘yarn set up’ for the reason that 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 test 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 like .yarnrc.yml isn’t tracked. I’ll additionally test .yarn for monitoring. | ||
| I’m double-checking the bundle.json to see if “haiven-ui” is the proper identify. | ? | |
| I’ll test the Node model to verify if it’s 18 or 20 by operating node -v. | bizarre, the node model laid out in bundle.json is 22.6 | |
| I believe switching to npx vitest run might repair the error. Let’s strive that. | ||
| The output is lengthy—now I’ll seize the final abstract traces. | 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 establishing the venv, which is completely pointless as a result of it solely plans modifications for frontend code:
| Message | Command (samples) | Notes |
|---|---|---|
| The assessments failed because of 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 test if it wants creation or already exists. | ||
| It appears just like the .venv listing is lacking. Let’s assessment AGENT’s directions rigorously. | ||
| The setting appears offline, however there is perhaps a script to arrange dependencies domestically. | ||
| I can’t run “poetry set up” offline, however I’ll test 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 because of lacking dependencies. Now, I’ll test 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 encircling 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 assessments failed because of setting points. I’ll reference the final failure traces. Performed! |
Right here is the total pull request created by Codex.
Observations
Brute textual content search
I discovered it attention-grabbing 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 by means of a bunch of search phrases with grep, to search out related items of code (“human”, “human readable”, “humanReadable”, …). The explanation why I discover it attention-grabbing 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 continues to be fairly easy, however doing textual content search with grep is the only potential.
It looks like the software creators have discovered that this easy search continues to be the simplest in spite of everything – ? 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 Could 2024). As of now, you may 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 a few of 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 difficult 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 recognized, it might have simply been in a position to repair the assessments, it was a trivial repair:
This specific mission, Haiven, truly has a scripted developer security web, within the type of a fairly elaborate .pre-commit configuration. () It might be excellent if the agent might execute the total pre-commit earlier than even making a pull request. Nevertheless, to run all of the steps, it might must 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 need to be accessible in the suitable variations as effectively, after all.
Determining a clean expertise to spin up simply the suitable 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 downside, and to an extent a solved downside, in spite of everything we do that in CI pipelines on a regular basis. However it’s additionally not trivial, and in the meanwhile my impression is that setting maturity continues to be a difficulty in most of those merchandise, and the consumer expertise to configure and take a look at the setting 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 domestically in Claude Code (which isn’t totally autonomous although, I wanted to manually say ‘sure’ to the whole lot). 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 believe this job is an efficient instance of the kinds and sizes of duties that GenAI brokers are already effectively positioned to work on by themselves. However there have been two points that differed when it comes to high quality of the answer:
- Discovery of present code that might be reused: Within the log right here you’ll discover that Codex discovered an present part, the “dynamic knowledge 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 operate, which led to duplicated code.
- Discovery of an extra place that ought to use this logic: The workforce 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 example 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 incorrect” 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 the whole lot completed the best way we wish it.
Sunk value fallacy
I’ve been questioning – let’s say a workforce makes use of background brokers for this kind of job, the kinds of duties which can be form of small, and neither necessary nor pressing. Haiven is an internal-facing utility, and has solely two builders assigned in the meanwhile, so this kind of beauty repair is definitely thought of low precedence because it takes developer capability away from extra necessary issues. When an agent solely form of succeeds, however not totally – by which conditions would a workforce discard the pull request, and by which conditions would they make investments the time to get it the final 20% there, although spending capability on this had been deprioritised? It makes me surprise concerning the tail finish of unprioritised effort we’d find yourself with.
