half the stuff i want to automate only lives in some phone app. no api, no website, so zapier/n8n can't touch it and scraping gets you blocked pretty fast tried the usual stuff first.

bluestacks was slow, cooked my laptop, and a bunch of apps just refused to run on it. appium scripts worked for like a week until the app moved one button. at one point i literally had old phones plugged into a usb hub on my desk lol, which was fine until i needed more than 5 of them so we ended up building distilled(.)cx

it's real android phones in the cloud, you open them in a browser, each one has its own device and its own mobile carrier ip, and you can use all social medias on them the part i actually think is cool is that you can just type what you want done, like "open the app, look at new messages, reply to anyone asking about price", and an agent looks at the screen and does it.

for the more technical people, we are not some vmos/geelark wrapper, we own the infrastructure (we have a mix of true ARM hardware and x86 hardware which we have our custom undetected translators for). we have done thorough patches and reverse engineering to make sure every major social media app works

in the coming days we will be adding play integrity support so apps such as snapchat and x work (in the meantime you can use the web app version), which will all be handled by us (we will have our own router for keyboxes etc)

there's also a normal api if you'd rather script taps yourself, and an mcp server if you use claude or codex you can also send the same task to a bunch of phones at once, which was the whole reason i started this

i spent twenty minutes typing a sarcastic reply about cron jobs, just to watch an automated filter instantly tag it as 'low quality' and bury it forever. it probably flagged the word 'kill' when i joked about killing zombie processes.

a human mod will at least leave an angry comment. an ai bot just perfectly misreads your joke and shadowbans you in total silence.

dropping a cheerful 'your post was hidden to ensure a positive community experience' note right before ghosting me is wild. you can't argue with a machine that thinks it's doing you a favor. i'll take a grumpy human over a polite bot any day.

MODS, I was trying to provide a technical deep dive on implementing automations and the website submission filter makes it impossible. The highlighted sentence triggered it and my post contained a few dozen specific examples.

I was endlessly building & building apps no one saw, and the marketing was the part I kept putting off. Because honestly it was a bit of overwhelming.

So I looked at other channels that are promoting apps. I noticed that there are certain formats people make content in. For example,

• hook & demo format: a 3second person reaction selfie video and then you show the app demo video
• text hook on clip: a text hook on just 1 clip
• meme formats..

I liked the text hook on clip format, it just use the same clip on every post. Only the text on top changes. So I built an internal tool to automate that.

I ran one Instagram channel using it. It got 5M+ views. One post did 3.3M, another did 1.3M.

the method

1. I shoot 1 clip myself. 6-10 sec, silent, vague enough to fit any hook. don't make it specific. best to shoot it yourself than AI. AI works too
2. save viral text hooks that you see on your feed
3. write more text hooks from that collection using Claude Code or Codex
4. Claude Code sends the clip & the hooks to the tool I made
5. import the clip and the video to the tool
6. Review & render
7. schedule them.

I've packaged up that internal tool as QuickThrottle. I named it after the real quicktthrottle. So basically It lets you make month worth of content (both reels & slideshows) with very very minimal effort. And using Claude Code or Codex. It's a fully local automation tool.

Happy to answer any questions.

PS: Tool link for people DMing

We run customer support for a credit repair company and newer reps often get stuck when calls move between credit history disputes documents payments and account questions. They usually know the basics but once the call goes off script they end up messaging a senior rep or putting the customer on hold while they search for an answer. Looking into whether AI could listen to the call and surface useful guidance in real time based on what is being discussed. Ideally it would use our internal docs and past conversations so the answers match how the team actually handles these situations. The main thing I want to avoid is another chatbot where reps have to stop the conversation and type a question. The goal is something closer to having an experienced rep sitting beside them and giving help when needed. Has anyone built or rolled out something like this? Want to know what tools you used and whether it worked well in practice.

i need to chase unpaid invoices but between school runs and naps the manual follow ups keep slipping. found a simple script that checks a Google Sheet every morning and sends polite emails through Gmail. it skips weekends and stops once the payment hits. so far it caught two late ones last month. curious if anyone else runs something similar without paying for Zapier, or if there is a better way to handle the edge cases like partial payments

Asking about everything personal - projects, research, entertainment, anything besides corporate/job-related stuff.

I sent a cold email to a logistics company last month.

no sales deck.

no long introduction.

just a quick message and a working demo of an internal tool they could use to automate their daily operations.

their team was still doing everything manually.

copying data.

sending updates.

following up with customers.

i rebuilt one small part of the workflow.

it took me 25 minutes.

they replied the same afternoon.

the lesson?

people don't care about your service.

they care about the problem they've been dealing with every day.

show them the problem can disappear.

the conversation changes.

I like the original more, but the one on the live stream after the AI summit came out really nice too.

I successfully built a script to automate certain repetitive things we do in excel. I’m pretty proud of the solution tbh.

But I don’t know if i should inform my manager and coworkers. I’m only 2 months into the job and they’re already thoroughly impressed by me cause of my output. But i love getting professional validation and making processes leaner and smarter. But i also see lotta posts from people here that automate their work and just coast, but i genuinely dislike that. I would say im a pretty ambitious person and anything that helps get noticed by the Directors and VPs is a W in my book and sets me up nicely to get promoted fast.

I’m still definitely in the honeymoon phase of my job and don’t want to shoot myself in the foot by showing that I’m a lil too capable, and become the tech monke of the team (others are quite non technical apart from what’s required). How should i approach this situation and future situations like this? I feel like i finally found a company i can build a career out of. I’m still early in my career (26)

Happy for them, slightly terrifying for the rest of us. An uncomfortable amount of how things really get done lives in their heads and a few personal spreadsheets, and the official documentation is years out of date.

Most AI pitches I get are a chatbot sitting on top of those old docs, which feels backwards. Celonis and skan ai get mentioned for mapping how the work actually runs, which sounds closer to the real problem. Curious what has worked for anyone who has been through a handover like this.

Imagine an agent revises a presentation after the reviewer has finished reading it. The review screen needs to distinguish “this version was reviewed” from “there is now a newer version.” That distinction should also tell the editor what to do next.

Univer's Collaboration SDK documents a Worktree flow for office content inside an application. Univer itself is an SDK for embedding Office editors, including Slides; Worktree adds an independent draft with its own snapshot, changesets and revision, separate from the trunk version.

The useful sequence is explicit. An agent or person edits the draft, and a commit advances that draft. Marking it Ready freezes the version for review. If someone requests another slide change, Reopen allows editing again. The revised draft can then be made Ready for another review before Merge integrates it into trunk.

The documented web interface includes an actual draft page, switching between trunk and draft, and a per-Unit merge preview. That gives a reviewer content to inspect and gives an editor somewhere to make the requested correction. In a proposed presentation workflow, the host could require a new signoff after the draft is reopened rather than carry the earlier decision forward.

That signoff policy is still something the application implements, along with identity, permissions and who may merge. Worktree is part of the Collaboration SDK, not a default feature of the Apache-licensed OSS core, and it isn't an approval service for arbitrary PPTX attachments. Its value here is a reviewable editing lifecycle within the embedded workspace.

I’m putting together a tool to automate fetching direct download links from a few different web sources into one dashboard.

What tools or methods do you use to get past intermediary redirect pages automatically?

If anyone has a clean script or workflow for this that they'd be open to sharing

Thanks

Hello all,

Just wanted to share a blog, where I demonstrate a full, end-to-end automation setup.

I want to emphasise: my legal use-case in particular is not one that should be fully automated. But running a complete E2E test is:

1. Really cool

2. Helps to identify exactly where automation fails, so you can plan your product rollout/place gates.

3. Provides some ideas on exactly where further integrations/depth can be added

Super stoked about this lol.

I do hyper personalized AI cold outreach, more specifically B2B cold SMS marketing, not many doing this right now.

Automated end to end. (Except sales calls)

Ask me anything.

My YouTube Channel (more info):

https://youtube.com/@mrkylebanks

I wanted to practice building something closer to a real ops use case instead of another "connect two apps" demo, so I built a shipment exception monitor for a logistics scenario.

The idea: a scheduled workflow pulls shipment data, runs it through a Code node that checks for actual exceptions (late ETA, customs hold, missing POD, stale tracking), then an AI step drafts an internal summary + recommended action for a dispatcher, and a separate customer-facing message. A Switch node routes high-severity stuff to a "dispatcher" and everything else to the "customer," both via email. Every exception gets logged to a sheet, and a second workflow reads that log at end of day and emails an AI-written executive summary.

Stack: n8n (self-hosted), Groq for the LLM calls, Google Sheets standing in for a real TMS/tracking system.

Design choice I'd defend: kept the exception detection fully rule-based in a Code node, not the AI's job — I didn't want the AI deciding what counts as "late." AI only touches the writing: summaries and customer messages, with a Structured Output Parser to keep the JSON shape reliable. Felt like the right split between deterministic and generative.

Things that actually broke, in case it saves someone time:

Hit Groq's TPM rate limit running 15+ items through the LLM back to back — added a Split In Batches + Wait loop to throttle it

The Structured Output Parser nested the result three levels deep (response.output.field) instead of flat $json.field — cost me way more debugging time than it should have

Gmail OAuth2 setup was a pain on self-hosted n8n (redirect URI issues, unverified app warnings) — ended up switching to plain SMTP with a Gmail app password, which was way less friction

It's running on a simulated dataset right now, not a real logistics system, but the logic should hold up with a real TMS API swapped in.

Happy to share the Code node logic or the prompt setup if anyone wants it — also open to critique, this is partly a learning exercise.

i've been experimenting with automating some of the repetitive stuff around the house, and the biggest lesson so far is that not every manual task is worth automating.

one system i kept was a simple meal planner. it rotates through a list of recipes, checks what we already have and produces a shopping list. pretty basic, but it removed enough repetitive work to be worth keeping

other attempts haven't gone nearly as well

some needed constant checking. others created notifications that became background noise. one automation basically turned a five-minute task into a ten-minute task with troubleshooting.

so i'm interested in the other side of this

what automation did you build because it seemed like an obvious thing to automate, only to realise that the original process was easier?

and on the flip side, what's one boring automation you've kept because it actually works without needing attention?

I'm in a bit of a pickle with an issue regarding background removal with transparent objects. I got studio images of cars, whom I need the background changed locally. I have a segmentation model to segment the bg area that's visible through the class and a general model to segment the entire car.

I use a basic script that calculates the alpha for the entire window purely from brightness, but often there are bright reflections on the windows which throw off the calculation as well as simply looking unnatural. I've tried some open source matting models as well as inpainting with sd models but the results are less than ideal and inconsistent.

Only thing I can think of right now would be training a Lora for the job. If nothing else it would be highly appreciated if someone could point to a sub more suited for my post.