AI Lab

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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

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

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

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

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.

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

VibeCoding is cool!!!👌

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

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

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

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

The first AI stack for a small business. Do not start with "AI transformation". Start with 5 simple systems: 1. Customer replies AI drafts answers, finds missing info, suggests next action. 2. Content engine AI turns one idea into posts, scripts, visuals and newsletters. 3. Market research AI tracks competitors, customer pain points and new opportunities. 4. Weekly reports AI turns messy updates into progress, blockers and next steps. 5. Personal assistant AI helps plan the day, summarize notes and remember follow-ups. The goal is not to replace the team. The goal is to remove repetitive thinking from daily work. Simple rule: If a task repeats every week, it should become an AI workflow. Start with one. Then connect the rest. #AI #SmallBusiness #AIWorkflow #Automation #AILab

AbacusAI may be one of the most underrated alternatives to Claude Code and Codex. Not because it is "just another coding agent". Because the idea is different: one subscription -> many top models -> coding agent -> desktop assistant -> app builder -> research -> docs -> image/video tools. The main product is ChatLLM Teams by Abacus.AI. According to Abacus, it gives access to many frontier and open-source models in one place: GPT, Claude, Gemini, Grok, DeepSeek, Kimi, Qwen, GLM, Abacus Smaug and more. Why this matters: Claude Code is mostly the Claude world. Codex is mostly the OpenAI world. AbacusAI tries to become a multi-model workspace where you can switch models, compare outputs and use one platform for more than coding. What it can do: 1. Coding agent and CLI Abacus AI Desktop includes a coding agent, CLI and VS Code extension for code generation, bug fixing and feature work. 2. Multi-model chat Use different models for writing, research, coding, data analysis and reasoning without paying for many separate tools. 3. App builder The Abacus AI Agent can build and host apps, websites, dashboards, APIs, chatbots and internal tools from prompts. 4. Documents and presentations It can generate docs, PowerPoints, reports and business materials. 5. Data analysis Upload CSVs, spreadsheets or docs, analyze them, create charts and extract insights. 6. Image and video generation ChatLLM includes image generation, and video generation is available through Abacus AI Studio with multiple video models. 7. Desktop automation Abacus CoWork can work with local files, docs, spreadsheets, logs and workflows on your computer. 8. Personal agents Abacus Personal Agents can deploy Open Claw or Hermes for persistent agents that work through Telegram, WhatsApp, Slack and other channels. The price angle: Abacus lists ChatLLM at $10/month per user, with a $7 first-month promo shown on its pages. That is the interesting part. If you are already paying separately for ChatGPT, Claude, Gemini, image tools, video tools and coding tools, AbacusAI can look much cheaper as one consolidated AI workspace. But there are tradeoffs. Pros: - many models in one place - coding + chat + docs + research + media tools - desktop app, CLI and VS Code workflow - useful for vibe coding and fast prototypes - good for teams that want one shared AI workspace - cheaper than stacking many separate subscriptions - can connect to systems like Google Drive, Slack, Confluence, Gmail and calendars Cons: - not always the same as using each native product directly - advanced usage can hit limits, credits or rate limits - some features depend on Abacus' own wrapper and platform UX - serious repo work still needs testing against Claude Code, Codex, Cursor and local workflows - pricing and included models can change - for sensitive business code, you still need to check data policy, compliance and admin controls The practical takeaway: Use AbacusAI if you want one affordable place to test many models, build prototypes, run research, create docs and try agentic coding. Use Claude Code or Codex when you want the deepest native experience inside one model ecosystem. The best setup may not be one tool. It may be: AbacusAI for multi-model exploration and fast workflows. Claude Code / Codex for serious engineering loops. GitHub + local tests for verification. AI work is moving from "which chatbot is best?" to "which system gives me the best workflow for the money?" And AbacusAI is worth watching. Sources: https://abacus.ai/chat_llm https://abacus.ai/chat_llm_faq https://desktop.abacus.ai/ https://agent.abacus.ai/ https://personal-agents.abacus.ai/ #AI #AbacusAI #ClaudeCode #Codex #AIAgents #VibeCoding #AIWorkflow

New here? Start with these AI Lab posts. AI Lab is not just another AI news channel. The main idea here is simple: turn AI from a chat window into practical systems for work, business, coding, research, content and automation. If you joined recently, here is the fast map. 1. Build your first personal AI assistant in 30 minutes A simple way to turn ChatGPT, Claude or Gemini into a daily planning and reply assistant. https://t.me/AISystemAgentLab/85 2. One small AI system that saves 5 hours a week How one repeatable loop can turn messy messages into summaries, reply drafts, tasks and follow-ups. https://t.me/AISystemAgentLab/94 3. AI Agent vs Chatbot The real difference between "AI answers" and "AI works toward an outcome". https://t.me/AISystemAgentLab/89 4. MCP in plain English Why Model Context Protocol matters for agents, tools, files, APIs and real workflows. https://t.me/AISystemAgentLab/91 5. RAG in plain English How AI can answer from your real knowledge base instead of only model memory. https://t.me/AISystemAgentLab/93 6. Kimi as an AI work platform Coding, presentations, websites, documents, agents and Kimi Claw in one AI workspace. https://t.me/AISystemAgentLab/87 7. 5 free official AI learning paths Anthropic, OpenAI, Google, Microsoft and DeepLearning.AI: where to start without buying hype. https://t.me/AISystemAgentLab/82 8. AI agents and money Why Robinhood's agentic trading signal matters for finance, business and agent safety. https://t.me/AISystemAgentLab/80 9. AI video tools Kling, Veo, Wan, Higgsfield, Runway, HeyGen, Sora, Hedra, Hailuo and Seedance in one quick map. https://t.me/AISystemAgentLab/90 10. Open Design AI The design layer for AI builders: from idea to page, deck, visual, mockup and launch assets. https://t.me/AISystemAgentLab/78 Best way to use this channel: Do not just read. Pick one post, choose one workflow, and apply it to one real task today. That is where AI starts becoming useful. #AI #AIWorkflow #AIAgents #Automation #AILab

One small AI system that saves 5 hours a week. Most people use AI like Google: ask one question, get one answer, close the chat. The real leverage starts when you turn one repetitive task into a tiny system. Example: incoming messages -> summary -> reply drafts -> tasks -> follow-up reminders You can build this with ChatGPT, Claude, Gemini, Codex, Notion, Google Sheets, Make, Zapier or n8n. Start with one workflow: 1. Collect messy input. 2. Give AI your context and rules. 3. Ask for a structured output. 4. Review before sending. 5. Repeat every day. Do not automate your whole life. Automate one annoying loop first. That is how AI becomes a worker, not just a chat window. #AI #Productivity #AIWorkflow #Automation #AILab