NagibakaFrontend, bots, automation
Lesson
Claude Coding 5 min read

3.1 The first tool is voice input. How to set up Spokenly for voice input in any text field for private offline work

We have finally reached the practical lessons on AI-assisted development. We won't start with basic prompts; instead, we'll make entering them convenient. Beyond speed, voice input has several very cool, non-obvious advantages. Some people are skeptical about this, but I strongly recommend you just try it once, and you will likely find it hard to give up afterward. In addition to dictating prompts, you will be able to dictate any text in any application, such as messengers and email clients.

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Lesson
Claude Coding 8 min read

2.1 Configuring Claude Code to work with OpenRouter, local LM Studio, or a corporate Qwen 3.6 27B model

Today, we’ll install Claude Code and configure it to work with other LLM providers. Of course, you can also use a regular Anthropic cloud subscription, but in this article I want to show how you can connect other models, such as ones that deliver speeds of 1,000 tokens per second! I’ll also explain in detail what challenges may arise and how to deal with them.

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4
Lesson
Claude Coding 4 min read

1.3 Uncensored models (cybersecurity, jokes about Black people and Jews, political analysis, adult sphere)

Today we'll talk a little about the limitations of cloud-based models and how to deal with them. This is about censorship built into a model's reasoning block. The biggest problem with censorship is that it develops and spreads endlessly, and every month you're forbidden from talking and thinking about an ever-growing number of things. And it permeates every area of life. The most disgusting kind of censorship arises because someone might take offense at words. Sometimes I rewatch old movies in which people spoke naturally and were capable of delivering great jokes regardless of gender, age...

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1
Lesson
Claude Coding 7 min read

1.2 Which Models Are Suitable for Coding? A Cheat Sheet on Model Types: Instruct, Thinking, Densed, Multi-modal, MOE, MTP, MLX, Quantization

I kept nagging one of my colleagues to try an LLM for his task of writing code for a fairly large feature. Eventually, he gave in and tried it, after which he complained for a long time and wondered how stupid the neural network was. I did not explain or tell him anything; I thought he would figure it out himself. It turned out that he was using the ChatGPT 4-mini model for coding, which is a very small and dumb model for tasks like that. For this reason, I decided that this article would not be unnecessary.

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7
Lesson
Claude Coding 5 min read

1.1 Introduction. Who is this guide for, and why does it focus on private and enterprise development using LLMs?

Hi, friends! I started a new blog and decided to begin with the most relevant topic today: AI-powered product development. This guide is aimed at a broad audience: regular developers, people just starting their programming journey, and those who have been asleep for the past few years and have not paid much attention to AI. I will try to explain all the important aspects briefly and clearly, and share recipes and tools for writing maintainable, extensible, production-ready code that humans can understand.

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