HR-агент на Claude Code: создаёт других сотрудников сам по запросу
The video demonstrates setting up a Telegram HR bot using Claude Code, walking through the process of creating a bot via BotFather, obtaining a Telegram user ID, and letting the code automatically generate the HR agent. The presenter shows how the system initializes itself by installing dependencies and launching the bot with minimal manual configuration.
Summary
The transcript covers a practical tutorial on creating an HR agent bot for Telegram using Claude Code. The presenter begins by opening BotFather, Telegram's official bot creation service, to register a new bot and obtain an API token. They deliberately skip explaining the BotFather creation process in detail, treating it as a prerequisite the audience should already know.
Next, the presenter visits the GetID bot to retrieve their personal Telegram user ID, which serves as an identifier for the system. Both the API token from BotFather and the personal Telegram ID are then sent to the newly created bot as configuration inputs.
After sending a 'start' command to the bot, the underlying code automatically begins the setup process — creating necessary files, installing dependencies, and launching the HR bot agent. The presenter notes that the audience needs to wait a few minutes for the automated process to complete. The video ends with a teaser that configuration of the HR employee/agent will follow in subsequent steps.
Key Insights
- The presenter emphasizes using the official BotFather exclusively, stating they see no point in discussing unofficial alternatives for bot creation.
- The system requires two key inputs to initialize: the API token from BotFather and the user's personal Telegram ID obtained from the GetID bot.
- After receiving a 'start' command, the code autonomously handles the entire setup — creating files and installing dependencies — without further manual input from the user.
- The presenter distinguishes that it is 'the code' (not a 'system') that launches the bot, suggesting a specific architectural distinction in how the automation is framed.
- The video is part of a multi-step process; the initial segment only covers bot creation and launch, with HR agent configuration deferred to a later segment.
Topics
Transcript
[0:00] So, first of all, we open botfire in order to create that very bot. I won't dwell on the process of creating the botfather now either. I'll just quickly create a new bot for myself now. The bot can be anything. The main thing is that the official botfire is used , because I don’t see the point in talking about the process of creating a botfire. That is, this is an official botfire, we create a new bot for ourselves. And we send this APKEN, accordingly, to Telegram. We also [0:31] go to this Get ID bot. And here, in the getid bot, we find our ID, uh, that is, your ID number, this identifier. And we send…
Full transcript available for MurmurCast members
Sign Up to AccessMore from Игорь Зуевич
Сравнение Claude Code, Gemini и Codex — тесты на контент, анализ и изображения
The speaker is comparing AI coding assistants — Claude Code, Gemini, and Codex — by testing their ability to create image-generation agents. Each tool is being evaluated on how well it writes prompts and structures sub-agents for text-to-image and image-to-image tasks.
Экономия токенов и контекстного окна: настройка памяти нейросети – Compact сжатие контекстного окна
The transcript explains the 'Compact' command in AI agent sessions, which compresses the entire conversation history to reduce context window usage without switching sessions. It also covers related commands for full history clearing and automatic triggers for compact execution. The speaker recommends configuring automatic notifications or auto-execution when the context window reaches a certain threshold.
Живые скиллы для Claude Code, Gemini и Codex | Как настроить super skills для ИИ агентов
The video explains how to create 'living' or 'super' skills for AI agents like Claude Code, Gemini, and Codex that self-update based on user feedback. The presenter demonstrates how these skills collect feedback after each task, store it in log files, and periodically incorporate that feedback into the skill's core instructions. This approach reduces token consumption and ensures skills continuously improve over time.
Планировщик для ИИ агента: 50 идей и готовые файлы для Claude, Codex и Gemini
The speaker describes their use of a scheduling/routing tool called Routins, which they compare to N8N, to automate daily delivery of curated YouTube videos on topics like Gemini and Claude. The system runs autonomously, collecting videos and generating concise summaries of their content without manual intervention.
Экономия токенов и контекстного окна: настройка памяти нейросети Newchat без потери данных
The transcript explains the Newchat command, which opens a new session while pulling data from previous sessions. It works in conjunction with the checkpoint command, which can be configured to trigger automatically when Newchat is launched. The speaker recommends implementing these commands through skills rather than MD slots for a more professional workflow.