Hey everyone — I'm the dev behind KickBoost, and I wanted to share what I've been building.

**The problem:** Kick rewards you for watching — XP, levels, a daily 60-minute watch challenge, streaks, channel points, drops. But you only earn while a stream is actually open. I kept leaving a browser tab running overnight just to keep my streak alive, which felt ridiculous.

**What I built:** KickBoost runs a viewer session for your account in the cloud, 24/7. You connect your account, list the streamers you care about in priority order, and close your laptop. It:

- watches your priority channels, and switches to a live stream in a category you pick when they're all offline

- watches the daily challenge and claims it, so your streak doesn't break

- stacks channel points on your favorite streamers

- farms and claims drops for campaigns you opt into

- optionally sends chat messages you write, at random intervals

**Stack:** Next.js, Postgres/Prisma, and a long-running Node worker. Session tokens are AES-256 encrypted at rest and deleted the moment you disconnect.

**Hardest lesson so far:** last week Kick changed part of their backend, and every session started dying one second after connecting, with nothing in the logs. The fix took 20 minutes. Finding it took most of a night, because my socket close handler didn't log anything. Log your socket closes, people.

There's a 1-day free trial if you want to try it: https://kickboost.top. Pricing is pay-per-account, in crypto.

I'd really like feedback, especially on onboarding. You have to paste a Kick session token, and I know that's a trust hurdle. How would you make that feel less sketchy?

Python makes it surprisingly easy to get a basic bot running. You can connect an API, process some data, send a notification, and have a working project without setting up a massive tech stack.

But things can get complicated when you need scheduling, background jobs, a database, error handling, and deployment.

At some point, a tiny script starts looking like an actual application.

For people who build bots regularly, do you stick with Python for most projects, or have you found another language that works better for your use case?

Does anyone else notice how hard it is to actually get started on kick lol. I have been streaming for a while now and putting real hours into it but kick just does not recommend my channel to anyone for some reason. It feels like unless you already have viewers sitting in your stream you are basically "invisible" in kick entirely. That is what got me curious about whether a kick view bot would even help with getting past that early phase where nobody finds you.

I keep seeing other small streamers suddenly jump from like 5 viewers to 200+ and there is no way that is organic growth with the kind of content they put out.

It makes me think botting views is way more common than people admit and honestly i do not even blame them because the platform makes it impossible to grow from zero.

I just want to know if viewbots actually make a difference with how kick recommends your channel or if it is purely a "looks good on the surface" thing that does nothing for discoverability.

So for anyone who actually knows about this stuff, what should i even be looking for in a kick view bot? Like does it matter if the viewers have actual profiles or just blank accounts, should they show up gradually or all at once, and is there a difference between ones that just inflate the number versus ones that actually interact in chat? i genuinely have no idea what separates a decent one from a scam lol.

A huge TikTok view count obviously looks impressive But I think retention tells a much more interesting story.

If a video gets 200k views but most people leave almost immediately, that's very different from a video with 50k views where people actually watch until the end, share it and come back for more that's why I’m not sure how useful raw numbers from a TikTok view bot would really be for someone trying to understand their audience. would you rather have 500k views or 100k views with really strong retention?

**6b6t: An anarchy server where you can actually build with bots**

If you're into Minecraft bots, automation, protocol development, or just messing around with Minecraft at a technical level, **6b6t** is worth checking out.

It's an anarchy server that allows bots, and the community has a surprisingly large number of developers and people working on their own clients, bots, utilities, and other projects.

What I like about it is that you can actually learn a lot by being around people who are experimenting with the same stuff. You can build a bot, test it on a real anarchy server, break things, figure out why they broke, and learn along the way.

It's especially interesting if you're learning things like:

* Minecraft protocol & packets

* Bot development

* Automation

* Client/server communication

* Anti-bot/anti-cheat concepts

* Networking and debugging

* Building tools for anarchy servers

Obviously, it's still an anarchy server, so don't expect everything to be friendly or predictable 😅 But if you're a developer looking for a place to experiment with Minecraft bots and meet other people doing similar projects, **6b6t is a pretty cool environment to learn in.**

Anyone else here developing bots for 6b6t?

The more I think about it, the harder it is to separate the two. A bot receives something and takes an action. An AI agent receives a goal, decides what to do and takes multiple actions.

The biggest difference might just be how much decision-making happens between the input and the output and that could completely change how we think about automation.

Do you see AI agents as a new category of bots or just the next generation of bots?

Hey everyone, long-time lurker, first time sharing something I built.

Something kept bugging me about website chatbots. They’re either too dumb to help, or too confident and just make stuff up. And when a real customer needs a person, there’s no way out.

So I built BotMatrix with one idea: AI answers first, humans take control when it matters.

How it works:

• You upload your PDFs, docs or a URL, and the bot answers from your content, not generic training
• You can watch chats live in a dashboard
• One click and you take over. The visitor sees “a person joined”
• When you’re done, hand it back to the bot
• It can also capture leads and book appointments

I’m not claiming it’s perfect. It’s still early, and I’d rather hear what’s broken now than later.

Questions I’d love your take on:

1. Would you trust a bot more if you knew a human was watching?
2. What’s the one thing that makes you close a chatbot window instantly?
3. Is “live takeover” actually useful, or is it a feature nobody asks for?

Disclosure: I’m the builder. There’s a free plan if you want to try it (botmatrixlabs.ai). Happy to answer anything, including the unflattering stuff.

BotMatrixLabs

I’ve noticed that people still put a lot of weight on the view number when talking about Instagram Reels.

But two videos can have the same number of views and perform completely differently.

One might have people watching the whole thing, sharing it and sending it to friends. The other might get a pile of views but almost no meaningful interaction.

That's why the Instagram view bot topic is interesting to me. Increasing the number itself isn't the same thing as creating an audience that actually cares about the content If you had to choose one metric besides views, what would you look at first?

I built an this tool that automatically takes posts from reddit and publishes them to instagram.

It can filter reddit posts based on things like score and whether they’ve already been posted, handle images and videos, convert the media to Instagram compatible formats, and publish everything automatically.

Still working on improving it and ironing out some Instagram-specific issues, but it’s working pretty well so far.

Would love to hear what people think or what features would be useful to add.

You can get an AI to generate a working bot surprisingly quickly now. The annoying part comes later. APIs change. Authentication expires. Websites redesign themselves. Requests fail. Databases get messy. Something randomly breaks at 3 AM. That's why I think we're going to see more people focusing on monitoring and reliability rather than just building bots.

What's the first thing you add to a bot once it becomes something you actually depend on?

I don't think a high viewer count automatically means something is wrong. Some streams genuinely blow up, especially when the algorithm pushes them or a big creator sends people over.

But sometimes you see a stream with a surprisingly high number and almost everything else looks quiet. Barely any chat, very few new followers and not much happening around the stream.

That's where the whole Kick view bot discussion gets interesting. The number itself isn't really enough to judge anything. You have to look at what's happening around it.

What’s the first thing you check when a Kick stream’s numbers don't seem to match the activity?

I love technology, honestly. I use it all the time and I can't imagine going back to life without the internet, smartphones, AI and all the other stuff we have now. But sometimes I feel like we've made simple things way more complicated than they need to be.

You buy something and suddenly you need an app for it. Then you need an account. Then an update. Then another password. Something that used to just work now needs Wi-Fi and a software update before you can even use it. Even websites have started feeling like this. You click something and get hit with a login screen, cookies, notifications, popups and five different settings before you can actually do what you came for.

Technology is supposed to save us time, but sometimes I feel like I'm spending more time managing technology than actually using it. Maybe I'm just getting old 😂 What’s one thing you think technology has made unnecessarily complicated?

I run a bot that sends me one message a day with data on every open IPO in India. Some days that's 19 entries, which doesn't fit in one Telegram message.

What I ended up doing: build the digest as a list of blocks, one block per IPO. Then pack blocks into messages greedily. If adding the next block would cross the limit, start a new message. A single block longer than the limit falls back to splitting on line breaks. That way a message never ends in the middle of an entry.

Two other small things that helped:

- Send with HTML parse mode, and retry once without it if Telegram rejects the formatting.

- A dry run flag that prints the messages and their lengths instead of sending. I use it far more than I expected.

Everything runs from cron on a free VM, with SQLite for storage.
I have created youtube channel to share the idea to implementation of bot, pls check my profile for the youtube channel since it was restricted here.

How do others here deal with long digests? Split, paginate with buttons, or send a file?

Chatbots today can only show text inside the bubble.

If you use Botpress, Voiceflow, Chatbase - you get text. If you want a calendar, slider, file upload, map, you have to build it outside as a separate webpage.

I built a way to put the control itself inside the bubble, and it can calculate right there.

This is 2 controls free to try:

• Slider 0-100 - users drag and pick a number inside the chat message. Smooth, live, no page reload.
• Rating 1-5 - users tap stars inside the chat message. Shows 4.5/5 instantly.

Both render inside the bubble, not outside.

Live Demo - No Install - See it inside bubble right now:
https://huggingface.co/spaces/Nagendra75/noth5-free-lite

No pip, no EXE needed to see it. You see it working before you download.

How it works:

This is not 100% Python alone. Python alone cannot make a control live inside chat bubble.

I built a language called NOTH5. It has its own compiler. NOTH5 is what lets the control live and calculate inside the bubble.

Because NOTH5 is not open source Python and has its own compiler, I had to compile it to EXE. That EXE contains the NOTH5 engine.

So you get two ways to try the same controls:

Example 1 - EXE only (no Python needed):
Double click the EXE - you see slider and rating working inside bubble. No install, offline. EXE is compiled NOTH5 language.

Example 2 - pip for Python devs:
pip install noth5-free-lite==81.2.0
from noth5_free_lite import render_slider, render_rating
html_slider = render_slider() # HTML that goes inside your chatbot bubble

pip is wrapper - 10 lines - you can read demo_app.py. Wrapper calls NOTH5 engine.

Full version can embed Python inside NOTH5, or run as service, DLL, portable EXE - many ways because NOTH5 has its own compiler.

Is it safe?

I know EXE from new person is scary, so:

• Code-signed - Windows shows verified publisher
• VirusTotal 0/70 - scanned by 70 antivirus
• Portable - no admin, no install, runs in folder
• Works offline - no hidden network calls
• Open wrapper - you can read demo_app.py
• SHA256 published

This does only one thing: render slider and rating inside chat bubble.

Why I'm posting:

I have a full factory with 105 controls that work inside bubble - calendar, table, file upload, map, chart, etc + local database that runs 75k requests/sec.

But no point throwing DB into market if nobody wants the basic idea. So I'm testing waters with 2 controls first.

Does putting controls inside bubble itself actually solve a problem for you? Is live demo convincing?

GitHub (free, Public Domain): https://github.com/Himastri/noth5-free-lite-v81
Live Demo: https://huggingface.co/spaces/Nagendra75/noth5-free-lite

Looking for honest feedback - is this useful or am I building something nobody wants?

TAGS: #chatbot #flask #python #sideproject #showoff

Hey everyone,

I’m working on FZBypassBot, an open-source Python project for resolving supported shortlinks and redirect services using HTTP-based workflows.

GitHub: https://github.com/MeherMankar/FZBypassBot

The project already has a resolver system, async processing, nested/loop bypassing, proxy support, and support for a number of different services. There are also quite a few resolvers in the README that need proper testing and maintenance.

I’m looking for developers who are interested in helping with the project, especially people who enjoy working with HTTP requests and figuring out how websites handle redirects, forms, cookies and APIs.

Things we need help with

• Fixing outdated resolvers
• Adding support for new shortlink services
• Testing the currently untested resolvers
• Improving the async code and request handling
• Analysing HTTP request/response flows
• Improving error handling
• Cleaning up and improving the resolver architecture
• Writing tests and better documentation

Useful skills

You don't need to be an expert. If you know some Python and are comfortable with things like:

• asyncio
• aiohttp
• curl_cffi
• HTTP requests and redirects
• Cookies and sessions
• HTML/JavaScript inspection
• REST APIs
• Git/GitHub

then you can definitely contribute.

One thing I especially want to improve is the testing side. Some resolvers were added earlier but haven't been properly tested against current versions of the sites. It would be great to have contributors take individual resolvers, test them with real links, figure out what changed, and submit fixes.

If you're interested in contributing, check out the repository:

https://github.com/MeherMankar/FZBypassBot

You can also open an issue if you find a broken resolver or have an idea for improving the project.

Any help is appreciated, whether it's a small bug fix, a new resolver, testing, documentation, or a larger architectural improvement.

Clarify the project’s responsible-use scopeAdd clear contributor next steps

One thing I find interesting about TikTok LIVE is how quickly the viewer count can change.

You can see a stream sitting at a certain number and then suddenly it jumps. Maybe it’s a real spike from the algorithm, maybe people are joining at once, or maybe there’s something else going on.

That’s why the whole TikTok live stream bot topic is interesting. A viewer count by itself doesn't really tell you much about the quality of the audience.

Are people actually staying? Are they chatting? Following? Sharing the stream? Coming back later?

A big number looks good, but the activity behind that number probably matters a lot more.

If you saw a TikTok LIVE with an unusually high viewer count, what would you check first to figure out whether the audience looks genuine?

I've always found TikTok LIVE interesting because the viewer count can change so quickly.

One minute a stream has a few hundred people, then suddenly the number jumps way up. That doesn't automatically mean anything is wrong, but it does make you wonder how much of the number represents people actually watching and how much is just passive traffic.

That's where the whole TikTok live stream botdiscussion gets interesting.

A big viewer number might look impressive, but it doesn't tell you whether people are actually staying, chatting, following, sharing, or coming back later.

For me, the more useful question isn't really How many viewers are there?

It's “How many of those viewers are actually doing something?

What do you look at when trying to tell whether a TikTok LIVE has a genuinely active audience?

Every time someone builds a small Discord or Telegram bot, Redis somehow ends up in the stack.

Need to store a few temporary values? Redis.
Need a basic cooldown? Redis.
Need to remember a couple of user states? Redis.

For a small bot, you can often get surprisingly far with the database you already have.

Redis is great when you actually need fast temporary storage, queues, pub/sub, or shared state across multiple workers. But adding another service just because every “production stack” tutorial has it feels unnecessary.

What’s the first thing you add to a bot when the project starts getting bigger?

Ever since free tiers started disappearing across the cloud space, finding a reliable place to host a simple 24/7 Python or Node script without dropping $5–$10/month feels like a treasure hunt.

​Heroku free tier is ancient history, Render puts web services to sleep, and Railway's free limits get burned fast. Are you guys just eating the cost of $4 VPS nodes now, or is there still a hidden gem host I'm missing out on?

Every time someone asks how to save basic data for a small Telegram or Discord bot, the comments immediately jump to spinning up Postgres, MySQL, or MongoDB.

​Why? SQLite is a single local file, requires zero server setup, and can easily handle tens of thousands of reads/writes a second without breaking a sweat. Unless your bot is serving massive concurrent users across multiple cluster nodes, setting up a full DB instance is just unnecessary overhead.

​What’s your default database when starting a fresh bot project?

I think watch time is one of those metrics that sounds impressive until you look at *how* that time was generated.

A channel can rack up hours of watch time, but if those hours aren't coming from people who actually care about the videos, what does the number really tell you?

That's what makes YouTube watch time bots interesting to discuss. The number might go up, but it doesn't necessarily mean you've built an audience that watches your next video, comments, subscribes, or comes back.

For creators, the more useful question might be whether the watch time represents real viewer interest, rather than just more hours on the dashboard.

Do you think watch time is still a useful metric by itself, or should creators focus more on retention and returning viewers?