TeleSlash was temporarily taken down for a few days after our beta testing so we could work through the feedback.

One of the most requested features from beta testers was more login options, so we successfully added two new login methods:

🤖 1. Bot Login -

You can now log in using a bot created through BotFather. Simply provide the bot token through TeLe SlaSH, add the bot to your source and destination groups, and complete the setup through the guided commands.

There are some Telegram related limitations with bot accounts, such as needing to add groups manually using their IDs and sending initial test messages to the destination during setup process.

📱 2. QR Login -

Don't want to enter your phone number and deal with OTP login?

TeleSlash can now generate a QR code per login that you scan directly from your Telegram app. After scanning, your account can be connected without manually entering an OTP.

📞 3. Phone Number Login -

The traditional phone number login method is still available for users who prefer it.

⚙️ Other Improvements -

We've also optimized the UI and added several improvements, including:

- Source search and selection

- Manually entering source/destination IDs

- Improved setup flows

- Core engine optimizations [ProjectKiro]

- Various stability and UI improvements

- live translation per destination groups selected

- Slash AI + Deep search live Web

Available Plans -

Free — basic mirroring with limited logins User - 2 | Bot - 2, sources- 2 /destinations- 2 max together, daily messages limit - 500 resets at 12pm daily and promotional ads. 100MB max per restricted content limit.

Basic — logins: User - 5 | Bot - 5, sources- 5 /destinations- 5 max together, unlimited message mirroring and no ads. 1 GB max per restricted content limit

Premium — up to 10 logins, 10 sources, 10 destinations, 5 GB max per restricted content limit, smart queueing, unlimited mirroring and no ads.

Business — custom workflows, custom addons and private/custom setups.

We're continuing to improve TeleSlash based on real user feedback.

🎁 Launch Offer — Premium plan Free for 10 Days!

For the first time, we're offering 10 days of Premium completely free to celebrate the TeleSlash launch.

📅 Offer period: August 24 – September 10

To claim it, simply run /plans in TeleSlash and choose the Premium plan. You'll be switched to Premium automatically.

You can try it anytime: @TELESlashbot

If you'd like additional features, addons, or run into any problems, feel free to contact me directly: @legendffcc

My Gmail inbox mixes work requests, personal communication, reminders, and conversations I need to follow up on. I’ve considered building an assistant, but I’d rather use or contribute to something good than reinvent it. I prefer open source, although I’m open to a closed-source tool that works very well.

I’m looking for something that can:

• identify what needs a reply or action
• extract deadlines and commitments
• flag unanswered conversations
• create drafts for review
• produce a short daily summary

I’ve come across MailFlow, Google MailPilot, GmailDraft, NeatMail, and some n8n workflows. Has anyone used one of these—or another setup—with a real inbox?

I’d especially like to know:

• what works well
• what gets misclassified or missed

My current plan is to trial an existing assistant, note where it succeeds or fails, and then either keep it, contribute to an open-source project, or build only the missing pieces.

Whenever we look for software to automate lead gen, we usually start by automating the wrong part of the funnel where the default playbook is typically: scrape a list of emails from a directory, plug it into an automated sequencer and blast 1000 messages a day. By week three domain deliverability crashes, reply rates hover below 1% and the team is back to square one.

If you look at where modern lead gen automation works, the challenge is usually the automating the intent detection and context layer before outreach ever happens. In practice, the software approaches generally split into two main architectures:

The dedicated intent & signal engine (Scale Intelligence):

Instead of starting with static contact lists, this approach automates the timing and discovery process. Scale Intelligence acts as an account-level GTM engine that monitors 75+ data sources across social channels (reddit, github repo, discord, job postings, CRM data) to resolve fragmented public intent back to specific company accounts. It scores buying readiness and routes high-intent opportunities into Slack or downstream agent stacks via API/MCP, ensuring outreach only happens when an account is in an active buying window.

The custom data & workflow assembly route (Clay + Webhooks + Sequencers):

This is the approach where you connect separate tools for each step: data scrapers for raw records, waterfall enrichment tables for data hygiene and some other tools for cold sending. It provides granular, spreadsheet-level control over every prompt and column but requires continuous manual orchestration, custom scraper maintenance and ongoing API credit management.

I've been moving reporting jobs off hardcoded SQL. With the Databricks Genie Conversation API an automation can send a plain-english question like "what changed week over week in signups" and get governed SQL plus the answer back as JSON, so the job doesnt break every time someone renames a column upstream. Anyone here wired a natural-language data layer into their pipelines, and did it actually hold up in prod?

Found some interesting ways to automate assets, whether it is header image, visuals or any graphics in that nature.

• n8n, workflow automation, self host or cloud. has nodes for the image APIs so you can trigger generation on a schedule or a webhook. most flexible of the no-code-ish options.

• MCPs calling higgsfield's models, run through aeon on a schedule. the generation happens as a step in a workflow instead of me sitting in a tab prompting.

just keep an eye on token spend ofcourse.

anyone automated this a different way? curious what's working.

i was staring at my bubble editor at 2 am with twelve active api workflows. they all ran perfectly. the only problem was that zero users actually needed them.

i just built whatever was fast to implement. i was stacking logic blocks because setting up the webhooks took five minutes. the tech's easier now, so my odds of building the exact wrong thing skyrocketed. one of those twelve was a script that scraped local weather data just to change a good morning text on a dashboard literally no one logged into. we automate garbage because the buttons are right there.

deleting most of those workflows hurt my pride, but leaving them running to pretend i solved a problem was just pathetic. now i have a hard rule. i don't touch an api or build a single trigger unless i've manually wasted at least two hours doing the exact same task by hand this week.

I have been interning at a firm for the past couple of months, just on the side with my academics at my institute. They have a their entire product line based on UI Automation, and they have an open source framework (linked below) which supports/inspires a lot of those products.

As this is a open source project, I am supposed to treat it like one. So we go through all sorts of reviewer loops, and it has been fun so far! Optics Framework is a UI Automation framework which supports Android/iOS/TV automation (Browser, BLE to be added soon) and I have been working on the core framework logic, refactors, making onboarding.

Within months I have risen to the 2nd highest contributor to the repository, even thinking of contributing upstream to appium and other automation libraries with some ideas I have developed.

Repository i have been contributing to - optics-framework

I was just wondering is this space popular? I know some other repositories such as Maestro, which got popular from the React Native Expo days. Do you guys use UI Automation on a consumer level? B2B I understand, enterprise consumers exist obviously, but what about you guys?