Habr AI
AI news source. Articles are auto-selected and adapted by Hamidun News editors.
Latest publications
How AI is changing SOC architecture: why correlation rules are no longer enough
A SOC can no longer rely only on correlation rules: modern attacks are quieter, longer, and more complex, so AI is increasingly taking over noise filtering and context gathering.
Telegram chats became a stable lead generation channel with a 5,000-ruble AI bot
An agency built an AI bot that monitors open business chats on Telegram, filters spam, and finds client requests, generating 15–22 qualified leads a month at a cost of about 5,000 rubles.
SberZdorovye: neural network non-determinism is a pipeline failure, not a model property
A SberZdorovye architect argues that with fixed data and environment, a neural network must produce a single result, and discrepancies usually point to errors in the code, hardware, or pipeline.
Nano Banana, Qwen, and ChatGPT compared on image generation quality
In a new comparison of image generators, four models, including Nano Banana, Qwen, and ChatGPT, were tested on the same prompts to see which handles real visual tasks better.
Habr AI: why LLM hallucinations look less like a mathematical bug and more like a human lapse
Habr AI has published a column arguing that LLM hallucinations should be viewed not only as an engineering defect, but also as a repetition of typical human reasoning failures.
Qdrant and Hybrid RAG: corporate document search without the cloud or leaks
Hybrid RAG combines semantic and exact search so companies can find answers in archives of PDFs, scans, and spreadsheets locally, without sending data to the cloud.
Directum proposed workflow agents as a practical path for introducing AI into business processes
Directum described a workflow agent model for business processes: AI operates under predefined rules within the corporate environment and is already cutting contract review time from 30 to 5 minutes.
Data Science in digital manufacturing: how enterprises collect data and reduce defects
Data Science turns fragmented manufacturing data into a tool for quality control, predictive maintenance, and process optimization across the product's digital thread.
Claude and the illusion of honesty: why people trust chatbots more than their own judgment
A column about Claude and “absolutely honest” prompts shows how easily people mistake a bot’s confident tone for expertise and begin delegating their own judgment to the machine.
Wildberries explained how to train AI agents through reflection, interviews, and a God-agent
A Wildberries engineer described a set of practices for working with AI agents: splitting context, conducting an interview before a task, reflecting after execution, and using a separate God-agent to tune the system.
Google NotebookLM can be turned into a personal mentor on any topic in five minutes
The guide shows how to build a personal mentor in Google NotebookLM from books, articles, and videos to get advice on your own tasks and learn faster from verified sources.
Evan Armstrong: why the context layer is changing the economics of enterprise software and hiring
Technology analyst Evan Armstrong argues that with the arrival of AI agents, value is shifting from standard SaaS applications to the context layer, where a company’s processes, access rights, and logic are stored.
Putin orders a state plan for AI as Russian business shuts down 90% of pilots
Russia is hardening its AI strategy: authorities are preparing a national plan and rules for neural networks, regions are scaling health services, and 90% of corporate pilots still never make it to production.
Why AI tools speed up code delivery but also inflate bugs and technical debt
Teams are increasingly getting a rapid boost in code output from AI, but with it come more defects, longer review queues, and new technical debt that can easily slip into production.
SimpleOne explained why vibe coding speeds up releases but hurts code and code review
SimpleOne broke down the benefits and risks of vibe coding: AI speeds up product releases and hypothesis testing, but also brings technical debt, harder code review, and dependence on external models.
Habr AI suggested using news sentiment as a trading signal for the crypto market
Habr AI described an approach in which shifts in sentiment across news and social media are used as a trading signal for the crypto market instead of classic indicators tied to price history.
How to use Deep Research in ChatGPT, Gemini, and Perplexity to find topics
Habr has published a practical guide on how to use Deep Research in ChatGPT, Gemini, or Perplexity to compile a list of viral topics in 10–15 minutes and filter them for your audience.
Google, Kling, and Yandex: where to generate AI video for free in 2026 and what limits apply
A review of free AI video generation services shows where you can create a video without paying, how many attempts Google, Kling, Luma, and others provide, and what you have to give up in return.
Habr AI: eight common complaints about AI models — from hallucinations to agent failures
Habr AI published an analysis of eight common complaints about AI models: from confident hallucinations and excessive initiative to expensive subscriptions, agent chaos, and the dangerous anthropomorphizing of chatbots.
Reg.Oblako: generative AI has entered its 1997 internet phase, and the window for entry is narrowing
In a column, Reg.Oblako CIO Evgeny Martynov compared the stage of generative AI to the internet in 1997 and explained why 2026–2027 will determine who integrates AI into their product and who remains in pilots.
AI lowered the barrier to entry in development — but technical debt has not disappeared
AI made it possible to build applications without deep technical knowledge, but the direct “task → code” approach quietly accumulates vulnerabilities and technical debt that surface too late.
zymi framework proposes building AI agents like a dbt project with YAML and event sourcing
Habr described zymi, an experimental framework where multi-agent pipelines are defined with YAML configs and all agent actions are recorded to an event-sourced data bus.
BotHub compiled 15 AI services for code, images, video, music, and everyday work
BotHub released a roundup of 15 AI services — from Cursor and Firebase Studio to Suno and Kling AI — and showed how the AI market is fragmenting into narrow task-specific tools.
Cloud.ru named five boring tasks that Big Tech is already handing over to AI assistants at scale
Cloud.ru compiled five categories of corporate routine that businesses are already handing over to AI: from support and code to legal search, infosec analysis, and ad content.
Goldman Sachs tracks job losses from AI and warns of falling demand
Goldman Sachs has begun calculating net monthly job losses from AI, and the main risk is no longer just layoffs, but that the economy may run short of buyers.
Habr AI explained why artificial intelligence is broader than neural networks and how its types are classified
In a new explainer, Habr AI reminds readers that neural networks are only one class of AI, alongside semantic networks, expert systems, and emergent models.
BetBoom: AI agents are changing development and forcing engineers to relearn
AI agents are becoming part of real-world development: they speed up reviews and routine work, but at the same time raise security requirements and deepen teams' dependence on cloud platforms.
Generator Video PRO topped the ranking of Russian video generation services in 2026
In a comparison of video generation services available in Russia, Generator Video PRO took first place, with the main criteria being operation without VPN, payment with Russian bank cards, sound, and clip length.
How a Claude-based Telegram assistant eased the CEO's load and took on part of the team's work
A small SaaS team integrated a Claude-based AI assistant into its work Telegram chat, gave it access to code, CRM, and GitHub, and over three months cut response times for managers from hours to seconds.
AI agents instead of vibe coding: how an autonomous pipeline takes a task to PR
The analysis explains that vibe coding breaks down because of context loss, not weak models, and proposes a pipeline where agents plan the task, debate in review, and send a ready PR.