Quick ask from AI Lab.

AI Lab has grown into a practical AI workflow channel with 5,500+ people here.

If this channel has already given you one useful idea, you can support it with a Telegram boost:

https://t.me/AISystemAgentLab?boost

Boosts help unlock more channel features and make it easier to create better practical AI content:

- short video explainers
- visual workflow maps
- polls and interactive posts
- beginner-friendly AI systems
- tool breakdowns like MCP, RAG, AbacusAI, Kimi, Codex and Claude Code
- practical guides for work, business, creators and builders

No pressure.

But if AI Lab helped you understand one tool, save time, or build one workflow, a boost would genuinely help the channel move faster.

Thank you for being here.

#AI #AILab #AIWorkflow

n8n turns AI into action.

Most people use AI as a chatbot. But real value starts when AI is connected to your daily tools.

n8n connects apps, APIs, databases and AI models into one working system.

Formula:
trigger -> AI step -> action -> report

What can you build?

- customer replies: draft answers, update CRM, notify the team
- content factory: one idea -> posts, scripts, calendar and briefs
- market research: collect sources, competitors and trends into a daily summary
- weekly reports: pull data from Sheets, GitHub, CRM or project tools
- lead qualification: score leads and draft follow-ups
- Telegram bots: route requests to AI, files, tasks or workflows
- internal AI assistants: connect docs, tickets, databases and APIs

The key difference:

ChatGPT can answer.
n8n can make something happen.

Start with one repeated task. Define the trigger, add one AI step, keep approval for risky actions, log results and improve weekly.

https://n8n.io/

#AI #n8n #Automation #AIWorkflow #AIAgents #AILab

I am preparing a practical guide:

How to build your own Telegram bot with vibe coding.

Not a theory post.
Not "learn Python for 3 months first".

A real beginner-friendly walkthrough:

- what bot to build first
- how to create a Telegram bot
- what tools to use
- how to write the first version with AI
- how to connect the bot to Telegram
- how to store prompts and user data
- how to test it
- where to deploy it
- how to avoid the most common beginner mistakes

The goal:

you should be able to go from idea to working Telegram bot without being a professional developer.

This is one of the most useful vibe coding projects for beginners because it teaches:

AI prompting,
APIs,
automation,
deployment,
and real user interaction.

If you want me to publish the full step-by-step guide here, let us unlock it together.

When this post gets 25 reactions, I will publish the full guide in AI Lab.

No vague motivation.
Just a practical build path.

#AI #VibeCoding #TelegramBot #Automation #AILab

Part 1 unlocked.

13 people already reacted to the Telegram bot guide post, so let us start with the first practical part.

What are we building?

A Telegram bot that can answer any user message with an LLM.

The user writes to the bot.
The bot sends the message to an AI model.
The AI model generates a reply.
The bot sends the answer back to the user.
All users and messages are saved to a database.

This is a great first vibe coding project because it teaches the real basics of AI products:

- Telegram Bot API
- LLM API
- database storage
- user tracking
- environment variables
- server deployment
- logs and debugging

The stack:

1. Telegram Bot
This is the interface.
Users talk to the bot in Telegram.

2. OpenRouter
This is the LLM layer.
Instead of connecting only one model, we use OpenRouter so the bot can work with different models: OpenAI, Claude, Gemini, DeepSeek, Kimi and others.

3. Supabase
This is the database.
We store:
- user id
- username
- first name
- language
- message text
- AI reply
- timestamps

Why store data?

Because without a database, the bot is just a chat window.

With a database, you can later add:
- user history
- analytics
- limits
- personalization
- paid access
- admin dashboard
- follow-up messages

4. DigitalOcean
This is where the bot lives online.
Your laptop should not be the server.

We deploy the bot to a small cloud server so it can work 24/7.

Simple architecture:

Telegram user
-> Telegram Bot
-> Node.js app
-> OpenRouter LLM
-> Supabase database
-> Telegram reply

Before writing code, define the first version clearly:

MVP:
- receive any text message
- save user to Supabase
- save incoming message
- send message to OpenRouter
- save AI reply
- send reply back to Telegram
- deploy to DigitalOcean

Do not start with payments, memory, admin panels or complex agents.

First make the basic loop work.

The main lesson:

AI products are not just prompts.

They are systems:

interface -> model -> database -> deployment -> feedback loop

In the next part, we can break this into actual build steps:
BotFather, project setup, Supabase tables, OpenRouter request, Telegram webhook or polling, and DigitalOcean deploy.

If the original unlock post reaches 25 reactions, I will publish the full step-by-step guide.

#AI #VibeCoding #TelegramBot #OpenRouter #Supabase #DigitalOcean #AILab

VibeCoding is cool!!!👌

Quick update.

The Telegram bot guide is almost unlocked.

22 / 25 reactions already.

Only 3 reactions left, and I will publish the full PDF guide:

- BotFather setup
- Claude Code / Codex prompts
- Supabase tables
- OpenRouter LLM setup
- DigitalOcean deployment
- testing checklist
- common errors

If you want the full guide, react to the original post:

https://t.me/AISystemAgentLab/102

No theory.
A practical build checklist.

#AI #VibeCoding #TelegramBot #AILab

The full beginner guide is ready.

How to build your first AI Telegram bot with vibe coding.

Inside the PDF:

- create a bot with @BotFather
- use Claude Code or Codex
- connect Supabase database
- connect OpenRouter LLM
- save users and messages
- deploy the bot to DigitalOcean
- use ready prompts for Codex / Claude Code
- create starter Supabase tables
- debug common errors
- test the bot after deployment

The example bot:

user writes a message -> bot sends it to an LLM -> AI answers -> all users and messages are saved to Supabase.

Download the guide, save it, and use it as a practical build checklist.

#AI #VibeCoding #TelegramBot #OpenRouter #Supabase #DigitalOcean #AILab

Quick feedback request from AI Lab.

If you downloaded the guide and started building your Telegram bot, leave a short comment here:

- what step you are on
- what worked
- where you got stuck
- what you want explained next

Even a small progress update is useful.

If someone manages to launch the first working version, share it here.

We may feature the best beginner success story in the channel.

What to build after this guide?

If you downloaded the Telegram bot guide, do not try to build a giant assistant first.

Build one small bot that solves one clear problem.

5 good first projects:

1. Customer reply bot
User sends a customer message -> bot drafts a polite reply and next action.

2. Lead qualification bot
User sends lead details -> bot scores the lead and suggests a follow-up.

3. Content idea bot
User sends a topic -> bot returns post ideas, hooks and short scripts.

4. Research summary bot
User sends a link or topic -> bot returns summary, key points and action list.

5. Personal task bot
User sends messy thoughts -> bot turns them into tasks, priorities and reminders.

The real lesson:

a useful AI bot is not just a chatbot.

It is a small workflow:

input -> AI -> data -> useful output.

Start with one boring repeated task.
Make the first version work.
Then improve it.

Guide:
https://t.me/AISystemAgentLab/106

#AI #VibeCoding #TelegramBot #Automation #AILab

AI is becoming your work secretary.

At Microsoft Build 2026, Microsoft introduced Scout — a new personal AI agent for work.

The idea is simple:

not another chatbot,
but an agent that understands how you work.

Scout is designed to use tools people already live in, like Teams and Outlook, and help with:

- meeting prep
- schedule conflicts
- routine tasks
- work context
- follow-ups

Why this matters:

The next useful AI may not be the smartest chatbot.

It may be the assistant that quietly removes small daily friction:

What do I need before this meeting?
What changed in this project?
Who needs a reply?
What should I do next?

This is where AI is moving:

from answering questions
to helping manage work.

The practical lesson:

start building small AI systems around repeated work loops.

One task.
One workflow.
One useful assistant.

Original source: Microsoft
https://blogs.microsoft.com/blog/2026/06/02/microsoft-build-2026-be-yourself-at-work/

#AI #AIAgents #Productivity #MicrosoftBuild #AILab

3 starter prompts to build your first AI Telegram bot.

If you opened the guide, the next step is simple:

do not ask AI to "make a bot" in one vague prompt.

Give it small engineering tasks:

1. Define the MVP
Receive user message -> save to Supabase -> send to OpenRouter -> save reply -> answer in Telegram.

2. Create the database
Ask for Supabase tables for users, messages, AI replies and logs.

3. Connect OpenRouter
Ask AI to add model calls, error handling, env variables and saved replies.

The trick:

vibe coding works better when you give AI a clear system, not a vague wish.

Small task.
Clear output.
Review.
Next task.

Guide:
https://t.me/AISystemAgentLab/106

#AI #VibeCoding #TelegramBot #Codex #ClaudeCode #AILab

Quick update from the poll.

So far, the largest share of votes is going to:

Personal task bot.

The poll is still open, so the winner can still change.

But this is already a strong signal.

So the next practical AI Lab task will be based on this direction:

building a personal task bot.

Not a giant "AI assistant for everything".

A small system with one clear job:

- capture a task or request from the user
- understand what needs to be done
- use an LLM
- save the interaction
- turn messy thoughts into tasks
- return a useful next action
- improve the workflow over time

This is the real difference between a chatbot and an AI product.

A chatbot answers.

A useful personal task bot creates a repeatable workflow:

messy message -> structured task -> priority -> deadline -> follow-up

We will break the next build into practical parts:

1. What the bot should do
2. What data it should save
3. How to connect the LLM
4. How to design the first database
5. How to test the first version
6. How to deploy it so it works 24/7

We will start with a simple MVP first.

Then we can show how the same idea can be upgraded with OpenClaw into a more powerful personal AI assistant.

The goal:

after reading the series, you should be able to build your first real AI bot with Codex or Claude Code, even if you are not a professional developer.

Start small.
Build the loop.
Then make it smarter.

Guide:
https://t.me/AISystemAgentLab/106

#AI #AIAgents #TelegramBot #VibeCoding #Codex #ClaudeCode #AILab

Partner program https://t.me/waveobot?start=_tgr_xJEzaeRiNjhi

Personal Task Bot: what exactly are we building?

Not a giant AI assistant.
Not another chatbot that answers everything.

We start with one useful loop:

messy thought -> clear task -> priority -> next action -> follow-up

The MVP:

1. Capture a task
2. Understand the intent
3. Structure the output
4. Save the task
5. Return a useful next action

No calendar sync yet.
No complex agents yet.
No full automation yet.

First we build the loop.

Then we can upgrade it with reminders, daily planning, weekly reviews and eventually OpenClaw.

AI becomes useful when it turns messy input into a structured action.

That is what we will build next.

Guide:
https://t.me/AISystemAgentLab/106

#AI #AIAgents #TelegramBot #VibeCoding #AIWorkflow #AILab

Continuation of the Personal Task Bot series.

In the previous post, we defined what we are building:

a simple Telegram bot that turns messy thoughts into structured tasks.

But if we want this bot to be genuinely useful, it needs memory.

Not vague "AI remembers everything" magic.

Real system memory:

- users
- messages
- tasks
- preferences
- recent context
- memory summary
- privacy commands

I prepared a practical PDF guide:

Build a Personal Task Bot with Memory

Inside:

1. The exact bot architecture
2. The first prompt for Codex / Claude Code
3. Supabase database schema
4. OpenRouter LLM flow
5. How bot memory actually works
6. How to save user preferences and open tasks
7. How to test the bot locally
8. How to deploy it to DigitalOcean

This is the difference between a simple chatbot and a useful AI system.

Download the guide below.

#AI #Codex #ClaudeCode #TelegramBot #Supabase #OpenRouter #VibeCoding #AILab

Next practical track in AI Lab:

OpenClaw.

We started with a simple Personal Task Bot:

message -> database -> LLM -> structured task -> memory

But that is only the first layer.

The next question is bigger:

how do you turn a bot into an always-available AI assistant that can work through Telegram, use tools, keep sessions and operate workflows?

That is why I am preparing a practical OpenClaw guide.

What we will cover:

1. What OpenClaw actually is
2. When it is useful and when it is overkill
3. How to install it step by step
4. How to connect Telegram
5. How workspace, memory, sessions and skills work
6. How to build the first useful workflow
7. How to add safety limits and avoid chaos

The full guide is already in preparation and will be published soon.

If this topic is useful, support the post with a reaction.

Sources:
https://github.com/openclaw/openclaw

#AI #AIAgents #OpenClaw #openclaw #TelegramBot #VibeCoding #AILab

The OpenClaw guide is ready.

Yesterday we talked about moving from a simple AI bot to a real personal assistant.

Now here is the full practical guide:

OpenClaw Practical Guide

Inside:
- what OpenClaw is and why it matters
- how it works as an AI agent gateway
- when to use it instead of a simple Telegram bot
- how to install OpenClaw
- how to connect it to Telegram
- how to use it as a personal AI assistant
- how to set up memory, sessions and safety limits
- common mistakes and first workflow ideas

The main idea is simple:

A chatbot answers.
An AI assistant remembers, routes tasks, uses tools and helps you operate workflows.

This is the next step after building your first Telegram AI bot.

Download the PDF, save it and use it as a practical setup map.

AI Lab will continue turning these tools into simple workflows for real work, business and personal productivity.