I do feel people will end up using this for things where a deterministic rule could be used - more effective, faster and cheaper. See this starting to happen at work...'We need AI to solve X....no you don't"
TeMPOraL 1 hours ago [-]
Maybe. The problem of "execute task on a cron" is something I've noticed the industry seems to refuse to solve in general, as if intentionally denying this capability for regular people. Even without AI, it's the most basic block of automation, and is always mysteriously absent from programs and frameworks (at least at the basic level). AI only makes it more useful on "then" side, but reliable cron on "if" side is already useful.
monkeydust 34 minutes ago [-]
Agree. How would you solve this in general, what would be the ingredients? People use things like zapier, n8n, node-red to achieve this today but in many cases are overkill.
bshimmin 20 minutes ago [-]
Honestly, you just need cron (and Ruby/Python/bash/whatever) on an EC2. It's not very fashionable, but it works, will continue to work forever, and costs hardly anything.
dspillett 18 minutes ago [-]
> See this starting to happen at work...'We need AI to solve X....no you don't"
Same. Sometimes it is just people overeager to play with new toys, but in our case there is a push from the top & outside too: we are in the process of being subsumed into a larger company (completion due on April the 1st, unless the whole thing is an elaborate joke!) and there is apparently a push from the investors there to use "AI" more in order to not "get left behind the competition".
monkeydust 6 minutes ago [-]
Its self perpetuating, I was talking to CEO of a Series A level B2B SaaS company here in UK recently. Most of the propspects his sales team are hitting are re-allocating their wallets to only looking for products that use AI on back of senior management pushing them to do so.
This company already does some pretty cool stuff with statistics for forecasting but now they are pivoting their roadmap to bake in GenAI into their offering over some other features that would be more valuable to their clients.
beefsack 21 minutes ago [-]
I feel this would be more useful for tasks like "Check website X to see if there are any great deals today". Specifically, tasks that are loosely defined and require some form of intuition.
comboy 57 minutes ago [-]
People are loading huge interpreted environments for stuff that can be done from the command line. Run computations on complex objects where it could be a single machine instruction etc. The trend has been around for a long time.
aledevv 3 minutes ago [-]
[dead]
javiercr 43 minutes ago [-]
I've recently switched from GitHub Copilot Pro to Claude Code Max (20x). While Claude is clearly superior in many aspects, one area where it falls short is remote/cloud agents.
Yesterday, I spent the entire day trying to set up "Claude on the web" for an Elixir project and eventually had to give up. Their network firewall kept killing Hex/rebar3 dependency resolution, even after I selected "full" network access.
The environment setup for "on the web" is just a bash script. And when something goes wrong, you only see the tail of the log. There is currently no way to view the full log for the setup script. It's really a pain to debug.
The Copilot equivalent to "Claude on the web" is "GitHub Copilot Coding Agents," which leverages GitHub Actions infrastructure and conventions (YAML files with defined steps). Despite some of the known flaws of GitHub Actions, it felt significantly more robust.
"Schedule task on the web" is based on the same infrastructure and conventions as "Claude on the web", so I'm afraid I'm gonna have the same troubles if I want to use this.
nickandbro 4 hours ago [-]
I feel like we are just inching closer and closer to a world where rapid iteration of software will be by default. Like for example a trusted user makes feedback -> feedback gets curated into a ticket by an AI agent, then turned into a PR by an Agent, then reviewed by an Agent, before being deployed by an Agent. We are maybe one or two steps from the flywheel being completed. Or maybe we are already there.
chatmasta 3 hours ago [-]
I love everything about this direction except for the insane inference costs. I don’t mind the training costs, since models are commoditized as soon as they’re released. Although I do worry that if inference costs drop, the companies training the models will have no incentive to publish their weights because inference revenue is where they recuperate the training cost.
Either way… we badly need more innovation in inference price per performance, on both the software and hardware side. It would be great if software innovation unlocked inference on commodity hardware. That’s unlikely to happen, but today’s bleeding edge hardware is tomorrow’s commodity hardware so maybe it will happen in some sense.
If Taalas can pull off burning models into hardware with a two month lead time, that will be huge progress, but still wasteful because then we’ve just shifted the problem to a hardware bottleneck. I expect we’ll see something akin to gameboy cartridges that are cheap to produce and can plug into base models to augment specialization.
But I also wonder if anyone is pursuing some more insanely radical ideas, like reverting back to analog computing and leveraging voltage differentials in clever ways. It’s too big brain for me, but intuitively it feels like wasting entropy to reduce a voltage spike to 0 or 1.
throwaw12 17 minutes ago [-]
> I love everything about this direction except for the insane inference costs.
If this direction holds true, ROI cost is cheaper.
Instead of employing 4 people (Customer Support, PM, Eng, Marketing), you will have 3-5 agents and the whole ticket flow might cost you ~20$
But I hope we won't go this far, because when things fail every customer will be impacted, because there will be no one who understands the system to fix it
mastermage 2 hours ago [-]
I mean theoretically if there are many competitiors the costs of the product should generally drop because competition.
Sadly enough I have not seen this happening in a long time.
eksu 2 hours ago [-]
This is the wrong way to see it. If a technology gets cheaper, people will use more and more and more of it. If inference costs drop, you can throw way more reasoning tokens and a combination of many many agents to increase accuracy or creativity and such.
Leptonmaniac 3 hours ago [-]
I think that as a user I'm so far removed from the actual (human) creation of software that if I think about it, I don't really care either way.
Take for example this article on Hacker News: I am reading it in a custom app someone programmed, which pulls articles hosted on Hacker News which themselves are on some server somewhere and everything gets transported across wires according to a specification. For me, this isn't some impressionist painting or heartbreaking poem - the entity that created those things is so far removed from me that it might be artificial already.
And that's coming from a kid of the 90s with some knowledge in cyber security, so potentially I could look up the documentation and maybe even the source code for the things I mentioned; if I were interested.
slopinthebag 2 hours ago [-]
Art is and has always been about the creator.
vntok 4 minutes ago [-]
Take a walk in any museum, I'm pretty sure you'll react to some of the art displayed there and find it cool before you read the name of the artist.
theredbeard 2 hours ago [-]
We haven’t been inching closer to users writing a half-decent ticket in decades though.
aembleton 51 minutes ago [-]
Maybe the agent can ask the user clarifying questions. Even better if it could do it at the point of submission.
heavyset_go 2 hours ago [-]
Feedback loops like that would be an exercise in raising garbage-in->garbage-out to exponential terms.
It's the "robots will just build/repair themselves" trope but the robots are agents
TeMPOraL 42 minutes ago [-]
Yes. Next they'll want nanobots that build/repair themselves.
Oh wait. That's already here and is working fine.
jvuygbbkuurx 3 hours ago [-]
Tusted user like Jia Tan.
mindwok 43 minutes ago [-]
I think Anthropic will launch backend hosting off the back of their Bun acquisition very soon. It makes sense to basically run your entire business out of Claude, and share bespoke apps built by Claude code for whatever your software needs are.
edf13 2 hours ago [-]
Or perhaps we end up where all software is self evolving via agents… adjusting dynamically to meet the users needs.
PeterStuer 48 minutes ago [-]
The "user" being the one that's in charge of the AI, not the person on the receiving end.
eru 2 hours ago [-]
Instead of having a trusted user, you can also do statistics on many users.
(That's basically what A/B testing is about.)
tuo-lei 2 hours ago [-]
The missing piece for me is post-hoc review.
A PR tells me what changed, but not how an AI coding session got there: which prompts changed direction, which files churned repeatedly, where context started bloating, what tools were used, and where the human intervened.
I ended up building a local replay/inspection tool for Claude Code / Cursor sessions mostly because I wanted something more reviewable than screenshots or raw logs.
slopinthebag 3 hours ago [-]
What kind of software are people building where AI can just one shot tickets? Opus 4.6 and GPT 5.4 regularly fail when dealing with complicated issues for me.
withinboredom 3 hours ago [-]
Not just complicated, but even simple ones if the current software is too “new” of a pattern they’ve never seen before or trained on.
slopinthebag 3 hours ago [-]
I dunno if Rust async or native platform API's which have existed for years count as new patterns, but if you throw even a small wrench in the works they really struggle. But that's expected really when you look at what the technology is - it's kind of insane we've even gotten to this point with what amounts to fancy autocomplete.
victorbjorklund 2 hours ago [-]
Of course not all tickets are complex. Last week I had to fix a ticket which was to display the update date on a blog post next to the publish date. Perfect use case for AI to one shot.
thin_carapace 3 hours ago [-]
i dont see anyone sane trusting ai to this degree any time soon, outside of web dev. the chances of this strategy failing are still well above acceptable margins for most software, and in safety critical instances it will be decades before standards allow for such adoption. anyway we are paying pennies on the dollar for compute at the moment - as soon as the gravy train stops rolling, all this intelligence will be out of access for most humans. unless some more efficient generalizable architecture is identified.
heavyset_go 2 hours ago [-]
> as soon as the gravy train stops rolling, all this intelligence will be out of access for most humans. unless some more efficient generalizable architecture is identified.
All Chinese labs have to do to tank the US economy is to release open-weight models that can run on relatively cheap hardware before AI companies see returns.
Maybe that's why AI companies are looking to IPO so soon, gotta cash out and leave retail investors and retirement funds holding the bag.
PeterStuer 2 hours ago [-]
They could still eliminate relatively cheap hardware.
thin_carapace 2 hours ago [-]
i was under the impression that we were approaching performance bottlenecks both with consumer GPU architecture and with this application of transformer architecture. if my impression is incorrect, then i agree it is feasible for china to tank the US economy that way (unless something else does it first)
heavyset_go 54 minutes ago [-]
I think it just needs to be efficient or small enough for companies to deploy their own models on their hardware or cloud, for more inference providers to come out of the woodwork and compete on price, and/or for optimized models to run locally for users.
Regarding the latter, smaller models are really good for what they are (free) now, they'll run on a laptop's iGPU with LPDDR5/DDR5, and NPUs are getting there.
Even models that can fit in unified 64GB+ memory between CPU & iGPU aren't bad. Offloading to a real GPU is faster, but with the iGPU route you can buy cheaper SODIMM memory in larger quantities, still use it as unified memory, eventually use it with NPUs, all without using too much power or buying cards with expensive GDDR.
Qwen-3.5 locally is "good enough" for more than I expected, if that trend continues, I can see small deployable models eventually being viable & worthy competition, or at least being good enough that companies can run their own instead of exfiltrating their trade secrets to the worst people on the planet in real-time.
m00x 3 hours ago [-]
Several fintechs like Block and Stripe are boasting thousands of AI-generated PRs with little to no human reviews.
Of course it's in the areas where it doesn't matter as much, like experiments, internal tooling, etc, but the CTOs will get greedy.
slopinthebag 3 hours ago [-]
I don't think anybody is doubting its ability to generate thousands of PR's though. And yes, it's usually in the stuff that should have been automated already regardless of AI or not.
thin_carapace 2 hours ago [-]
these companies contribute to swathes of the west's financial infrastructure, not quite safety critical but critical enough, insane to involve automation here to this degree
slopinthebag 3 hours ago [-]
Even in webdev it rots your codebase unchecked. Although it's incredibly useful for generating UI components, which makes me a very happy webslopper indeed.
thin_carapace 1 hours ago [-]
im grateful to have never bothered learning web dev properly, it was enlightening witnessing chat gpt transform my ten second ms paint job into a functional user interface
hyperionultra 2 hours ago [-]
"Trusted user" also can be an Agent.
bredren 3 hours ago [-]
What you're describing is absolutely where we're headed.
But the entire SWE apparatus can be handled.
Automated A/B testing of the feature. Progressive exposure deployment of changes, you name it.
overfeed 41 minutes ago [-]
> I feel like we are just inching closer and closer to a world where rapid iteration of software will be by default.
There's a lots of experimentation right now, but one thing that's guaranteed is that the data gatekeepers will slam the door shut[1] - or install a toll-booth when there's less money sloshing about, and the winners and losers are clear. At some point in the future, Atlassian and Github may not grant Anthropic access to your tickets unless you're on the relevant tier with the appropriate "NIH AI" surcharge.
1. AI does not suspend or supplant good old capitalism and the cult of profit maximization.
tossandthrow 3 hours ago [-]
I think the Ai agent will directly make a PR - tickets are for humans with limited mental capacity.
At least in my company we are close to that flywheel.
_puk 3 hours ago [-]
Tickets need to exist purely from a governance perspective.
Tickets may well not look like they do now, but some semblance of them will exist. I'm sure someone is building that right now.
No. It's not Jira.
tossandthrow 2 hours ago [-]
Yes, so my point is that PRs act as that governance layer - with preview environments, you can see the complexity and risk of the change etc.
Gigachad 3 hours ago [-]
The agents have even more limited capacity
eru 2 hours ago [-]
At the moment, maybe. But it's growing.
Gigachad 1 hours ago [-]
Even so they would probably still benefit from intermediate organisational steps.
eru 1 hours ago [-]
For a while, sure.
MattGaiser 3 hours ago [-]
I am already there with a project/startup with a friend. He writes up an issue in GitHub and there is a job that automatically triggers Claude to take a crack at it and throw up a PR. He can see the change in an ephemeral environment. He hasn't merged one yet, but it will get there one day for smaller items.
I am already at the point where because it is just the two of us, the limiting factor is his own needs, not my ability to ship features.
jondwillis 3 hours ago [-]
Why doesn’t he merge them?
m00x 3 hours ago [-]
Must be nice working on simple stuff.
yieldcrv 3 hours ago [-]
We do feedback to ticket automatically
We dont have product managers or technical ticket writers of any sort
But us devs are still choosing how to tackle the ticket, we def don't have to as I’m solving the tickets with AI. I could automate my job away if I wanted, but I wouldn't trust the result as I give a degree of input and steering, and there’s bigger picture considerations its not good at juggling, for now
charcircuit 4 hours ago [-]
Then sets up telemetry and experiments with the change. Then if data looks good an agent ramps it up to more users or removes it.
eranation 3 hours ago [-]
Um, we are already there...
gowthamgts12 4 hours ago [-]
interesting to see feature launches are coming via official website while usage restrictions are coming in with a team member's twitter account - https://x.com/trq212/status/2037254607001559305.
If you read the replies to the second, you’ll see an engineer on Claude Code at Anthropic saying that it is false.
Someone spread FUD on the internet, incorrectly, and now others are spreading it without verifying.
stingraycharles 4 hours ago [-]
To me it makes perfect sense for them to encourage people to do this, rather than eg making things more expensive for everyone.
The same as charging a different toll price on the road depending on the time of day.
simianwords 2 hours ago [-]
I remember when I tried to set something up with the ChatGPT equivalent like "notify me only if there are traffic disruptions in my route every morning at 8am" and it would notify me every morning even if there was no disruption.
theredbeard 2 hours ago [-]
This is because for some reason all agentic systems think that slapping cron on it is enough, but that completely ignores decades of knowledge about prospective memory. Take a look at https://theredbeard.io/blog/the-missing-memory-type/ for a write-up on exactly that.
scottmcdot 2 hours ago [-]
Me too. It doesn't have ability to alert only on true positive. I has to also alert on true negative. So dumb
worldsayshi 1 hours ago [-]
This doesn't seem to hard to solve except for the ever so recurring llm output validation problem. If the true positive is rare you don't know if the earthquake alert system works until there's an earthquake.
Grok has had this feature for some time now. I was wondering why others haven't done it yet.
This feature increases user stickiness. They give 10 concurrent tasks free.
I have had to extract specific news first thing in the morning across multiple sources.
iBelieve 4 hours ago [-]
Looks like I'm limited to only 3 cloud scheduled tasks. And I'm on the Max 20x plan, too :(
"Your plan gets 3 daily cloud scheduled sessions. Disable or delete an existing schedule to continue."
But otherwise, this looks really cool. I've tried using local scheduled tasks in both Claude Code Desktop and the Codex desktop app, and very quickly got annoyed with permissions prompts, so it'll be nice to be able to run scheduled tasks in the cloud sandbox.
Here are the three tasks I'll be trying:
Every Monday morning: Run `pnpm audit` and research any security issues to see if they might affect our project. Run `pnpm outdated` and research into any packages with minor or major upgrades available. Also research if packages have been abandoned or haven't been updated in a long time, and see if there are new alternatives that are recommended instead. Put together a brief report highlighting your findings and recommendations.
Every weekday morning: Take at Sentry errors, logs, and metrics for the past few days. See if there's any new issues that have popped up, and investigate them. Take a look at logs and metrics, and see if anything seems out of the ordinary, and investigate as appropriate. Put together a report summarizing any findings.
Every weekday morning: Please look at the commits on the `develop` branch from the previous day, look carefully at each commit, and see if there are any newly introduced bugs, sloppy code, missed functionality, poor security, missing documentation, etc. If a commit references GitHub issues, look up the issue, and review the issue to see if the commit correctly implements the ticket (fully or partially). Also do a sweep through the codebase, looking for low-hanging fruit that might be good tasks to recommend delegating to an AI agent: obvious bugs, poor or incorrect documentation, TODO comments, messy code, small improvements, etc.
I ran all of these as one-off tasks just now, and they put together useful reports; it'll be nice getting these on a daily/weekly basis. Claude Code has a Sentry connector that works in their cloud/web environment. That's cool; it accurately identified an issue I've been working on this week.
I might eventually try having these tasks open issues or even automatically address issues and open PRs, but we'll start with just reports for now.
A trivial way to rack up hundreds of dollars in API costs, sure.
But you can set up a claude -p call via a cronjob without too much hassle and that can use subscriptions.
zmmmmm 3 hours ago [-]
i'm missing something basic here .... what does it actually do? It executes a prompt against a git repository. Fine - but then what? Where does the output go? How does it actually persist whatever the outcome of this prompt is?
Is this assuming you give it git commit permission and it just does that? Or it acts through MCP tools you enable?
jngiam1 3 hours ago [-]
MCP tools. We're doing some MCP bundling and giving it here, pretty cool stuff.
tossandthrow 3 hours ago [-]
We use to do do automated sec audits weekly on the code base and post the result on slack
zmmmmm 3 hours ago [-]
so is slack posting an MCP tool it has? or a skill it just knows?
tossandthrow 3 hours ago [-]
In Claude it is a "connector" which is essentially an mcp tool.
mkagenius 3 hours ago [-]
This is a bit restrictive, doesn't take screenshots. So you can't "say take screenshots of my homepage and send it to me via email"
It doesnt allow egress curl, apart from few hardcoded domains.
I have created Cronbox in the cloud which has a better utility than above.
Did a "Show HN: Cronbox – Schedule AI Agents" a few days back.
Is this free? I don’t see pricing info. I guess just a way to make you forget that you’re spending money on tokens?
weird-eye-issue 4 hours ago [-]
You don't spend money on tokens. It is a subscription.
lucgagan 4 hours ago [-]
Here goes my project.
hydroweaver87 3 hours ago [-]
What were you working on?
MeetRickAI 2 hours ago [-]
[dead]
jngiam1 3 hours ago [-]
This is powerful. Combined with MCPs, you can pretty much automate a ton of work.
esperent 2 hours ago [-]
Can you give some examples?
adobrawy 5 minutes ago [-]
That feature was silent launched about week ago for me.
I use it to:
- perform review of latest changes of code to update my documentation (security policies, user documentation etc.)
- perform review to latest changes of code, triage them, deduplicate and improve code - I review them, close them with comments for over-engoneering / add review for auto-fix
- perform review of open GitHub issue with label, select the one with highest impact, comment with rationale, implement it and make pull request - I wake up and I have a few pull request to fix issues that I can approve /finish in existing Claude Code thread
I want also use it to:
- review recent Sentry issues, make GitHub issues for the one with highest priority, make pull request with proposed fix - I can just wake up and see that some crash is ready to be resolved
Limit of 3 scheduled jobs is pretty impactful, but playing with it give me a nice idea on how I can reduce my manual work.
Rendered at 08:56:22 GMT+0000 (Coordinated Universal Time) with Vercel.
Same. Sometimes it is just people overeager to play with new toys, but in our case there is a push from the top & outside too: we are in the process of being subsumed into a larger company (completion due on April the 1st, unless the whole thing is an elaborate joke!) and there is apparently a push from the investors there to use "AI" more in order to not "get left behind the competition".
This company already does some pretty cool stuff with statistics for forecasting but now they are pivoting their roadmap to bake in GenAI into their offering over some other features that would be more valuable to their clients.
Yesterday, I spent the entire day trying to set up "Claude on the web" for an Elixir project and eventually had to give up. Their network firewall kept killing Hex/rebar3 dependency resolution, even after I selected "full" network access.
The environment setup for "on the web" is just a bash script. And when something goes wrong, you only see the tail of the log. There is currently no way to view the full log for the setup script. It's really a pain to debug.
The Copilot equivalent to "Claude on the web" is "GitHub Copilot Coding Agents," which leverages GitHub Actions infrastructure and conventions (YAML files with defined steps). Despite some of the known flaws of GitHub Actions, it felt significantly more robust.
"Schedule task on the web" is based on the same infrastructure and conventions as "Claude on the web", so I'm afraid I'm gonna have the same troubles if I want to use this.
Either way… we badly need more innovation in inference price per performance, on both the software and hardware side. It would be great if software innovation unlocked inference on commodity hardware. That’s unlikely to happen, but today’s bleeding edge hardware is tomorrow’s commodity hardware so maybe it will happen in some sense.
If Taalas can pull off burning models into hardware with a two month lead time, that will be huge progress, but still wasteful because then we’ve just shifted the problem to a hardware bottleneck. I expect we’ll see something akin to gameboy cartridges that are cheap to produce and can plug into base models to augment specialization.
But I also wonder if anyone is pursuing some more insanely radical ideas, like reverting back to analog computing and leveraging voltage differentials in clever ways. It’s too big brain for me, but intuitively it feels like wasting entropy to reduce a voltage spike to 0 or 1.
If this direction holds true, ROI cost is cheaper.
Instead of employing 4 people (Customer Support, PM, Eng, Marketing), you will have 3-5 agents and the whole ticket flow might cost you ~20$
But I hope we won't go this far, because when things fail every customer will be impacted, because there will be no one who understands the system to fix it
Sadly enough I have not seen this happening in a long time.
It's the "robots will just build/repair themselves" trope but the robots are agents
Oh wait. That's already here and is working fine.
(That's basically what A/B testing is about.)
A PR tells me what changed, but not how an AI coding session got there: which prompts changed direction, which files churned repeatedly, where context started bloating, what tools were used, and where the human intervened.
I ended up building a local replay/inspection tool for Claude Code / Cursor sessions mostly because I wanted something more reviewable than screenshots or raw logs.
All Chinese labs have to do to tank the US economy is to release open-weight models that can run on relatively cheap hardware before AI companies see returns.
Maybe that's why AI companies are looking to IPO so soon, gotta cash out and leave retail investors and retirement funds holding the bag.
Regarding the latter, smaller models are really good for what they are (free) now, they'll run on a laptop's iGPU with LPDDR5/DDR5, and NPUs are getting there.
Even models that can fit in unified 64GB+ memory between CPU & iGPU aren't bad. Offloading to a real GPU is faster, but with the iGPU route you can buy cheaper SODIMM memory in larger quantities, still use it as unified memory, eventually use it with NPUs, all without using too much power or buying cards with expensive GDDR.
Qwen-3.5 locally is "good enough" for more than I expected, if that trend continues, I can see small deployable models eventually being viable & worthy competition, or at least being good enough that companies can run their own instead of exfiltrating their trade secrets to the worst people on the planet in real-time.
Of course it's in the areas where it doesn't matter as much, like experiments, internal tooling, etc, but the CTOs will get greedy.
But the entire SWE apparatus can be handled.
Automated A/B testing of the feature. Progressive exposure deployment of changes, you name it.
There's a lots of experimentation right now, but one thing that's guaranteed is that the data gatekeepers will slam the door shut[1] - or install a toll-booth when there's less money sloshing about, and the winners and losers are clear. At some point in the future, Atlassian and Github may not grant Anthropic access to your tickets unless you're on the relevant tier with the appropriate "NIH AI" surcharge.
1. AI does not suspend or supplant good old capitalism and the cult of profit maximization.
At least in my company we are close to that flywheel.
Tickets may well not look like they do now, but some semblance of them will exist. I'm sure someone is building that right now.
No. It's not Jira.
I am already at the point where because it is just the two of us, the limiting factor is his own needs, not my ability to ship features.
We dont have product managers or technical ticket writers of any sort
But us devs are still choosing how to tackle the ticket, we def don't have to as I’m solving the tickets with AI. I could automate my job away if I wanted, but I wouldn't trust the result as I give a degree of input and steering, and there’s bigger picture considerations its not good at juggling, for now
also, someone rightly predicted this rugpull coming in when they announced 2x usage - https://x.com/Pranit/status/2033043924294439147
Someone spread FUD on the internet, incorrectly, and now others are spreading it without verifying.
The same as charging a different toll price on the road depending on the time of day.
https://grok.com/tasks
Grok has had this feature for some time now. I was wondering why others haven't done it yet.
This feature increases user stickiness. They give 10 concurrent tasks free.
I have had to extract specific news first thing in the morning across multiple sources.
"Your plan gets 3 daily cloud scheduled sessions. Disable or delete an existing schedule to continue."
But otherwise, this looks really cool. I've tried using local scheduled tasks in both Claude Code Desktop and the Codex desktop app, and very quickly got annoyed with permissions prompts, so it'll be nice to be able to run scheduled tasks in the cloud sandbox.
Here are the three tasks I'll be trying:
Every Monday morning: Run `pnpm audit` and research any security issues to see if they might affect our project. Run `pnpm outdated` and research into any packages with minor or major upgrades available. Also research if packages have been abandoned or haven't been updated in a long time, and see if there are new alternatives that are recommended instead. Put together a brief report highlighting your findings and recommendations.
Every weekday morning: Take at Sentry errors, logs, and metrics for the past few days. See if there's any new issues that have popped up, and investigate them. Take a look at logs and metrics, and see if anything seems out of the ordinary, and investigate as appropriate. Put together a report summarizing any findings.
Every weekday morning: Please look at the commits on the `develop` branch from the previous day, look carefully at each commit, and see if there are any newly introduced bugs, sloppy code, missed functionality, poor security, missing documentation, etc. If a commit references GitHub issues, look up the issue, and review the issue to see if the commit correctly implements the ticket (fully or partially). Also do a sweep through the codebase, looking for low-hanging fruit that might be good tasks to recommend delegating to an AI agent: obvious bugs, poor or incorrect documentation, TODO comments, messy code, small improvements, etc.
I ran all of these as one-off tasks just now, and they put together useful reports; it'll be nice getting these on a daily/weekly basis. Claude Code has a Sentry connector that works in their cloud/web environment. That's cool; it accurately identified an issue I've been working on this week.
I might eventually try having these tasks open issues or even automatically address issues and open PRs, but we'll start with just reports for now.
Seems trivial.
But you can set up a claude -p call via a cronjob without too much hassle and that can use subscriptions.
Is this assuming you give it git commit permission and it just does that? Or it acts through MCP tools you enable?
It doesnt allow egress curl, apart from few hardcoded domains.
I have created Cronbox in the cloud which has a better utility than above. Did a "Show HN: Cronbox – Schedule AI Agents" a few days back.
https://cronbox.sh
and a pelican riding a bicycle job -
https://cronbox.sh/jobs/pelican-rides-a-bicycle?variant=term...
I use it to:
- perform review of latest changes of code to update my documentation (security policies, user documentation etc.)
- perform review to latest changes of code, triage them, deduplicate and improve code - I review them, close them with comments for over-engoneering / add review for auto-fix
- perform review of open GitHub issue with label, select the one with highest impact, comment with rationale, implement it and make pull request - I wake up and I have a few pull request to fix issues that I can approve /finish in existing Claude Code thread
I want also use it to: - review recent Sentry issues, make GitHub issues for the one with highest priority, make pull request with proposed fix - I can just wake up and see that some crash is ready to be resolved
Limit of 3 scheduled jobs is pretty impactful, but playing with it give me a nice idea on how I can reduce my manual work.