Habr AI
AI news source. Articles are auto-selected and adapted by Hamidun News editors.
Latest publications
OpenAI and Anthropic shift language model pricing metrics: in 2026, task cost matters
OpenAI and Anthropic are changing LLM pricing rules: in 2026, tracking token price alone is no longer enough for businesses — calculating the full cost of solving a specific task is necessary.
Claude Code Turned into BABOK AI-Analyst: Assistant Conducts Interviews and Gathers Requirements
Based on Claude Code, they built an AI-assistant for business analysis following BABOK v3: it helps conduct interviews, gather requirements, avoid skipping steps, and document artifacts.
Claude Code and Codex: how to reduce token losses with three markdown files
Claude Code and Codex often spend most of their context on repeated project navigation; this can be solved with a hierarchy of a global map, CLAUDE.md, and memory of past sessions.
LM Studio and Qwen: How Local LLMs Handle Coding on MacBook M4 Pro
The author tested local Qwen, Gemma and other models for coding via LM Studio on MacBook M4 Pro: they are already viable in chat mode, but noticeably lag behind cloud solutions in agent mode.
Qwen 3.5 on MacBook Pro: Comparing Eight Local Servers for Team Workflows
The author tested eight MLX servers on MacBook Pro M2 Max with Qwen 3.5 35B, revealing that nearly all solutions significantly lose speed under parallel requests.
Selectel: AI doesn't take away jobs, but makes entering the profession significantly harder
Selectel describes a new labor market around AI: vacancies don't disappear, but it's harder for juniors to enter the profession, and demand and salaries shift toward those who can work with models.
Habr AI releases guide to ChatGPT, Claude, and mcp for newcomers
Habr AI explains without unnecessary theory the differences between local and cloud models, why to pay for subscriptions, how agents work, and why mcp is becoming the standard.
Joshua Bengio and LawZero: why fear of future AI distracts from today's threats
A text on 'Pascal's wager' in AI explains why fear of hypothetical superintelligence diverts attention from already real threats: surveillance, corporate power, and worker pressure.
Anthropic and Claude Opus 4.7: Actual Token Consumption Exceeded Claimed Figures
An author measured Claude Opus 4.7's new tokenizer and found consumption increased up to 45–47%, contrary to Anthropic's promised 0–35%, directly impacting quota burn, cache, and Max plan depletion rates.
OpenAI releases GPT-Rosalind for biology: capabilities and limits of the new model
OpenAI launched GPT-Rosalind for life sciences tasks and integrated it with a Codex research module, promising to accelerate hypotheses and experiments without manual assembly from dozens of services.
Cursor Security Audit Discovers Four Vulnerabilities in Code Editor Protection, but Authorization Remains Secure
Technical audit of Cursor revealed prototype pollution, a hidden dev field, and internal architecture leaks, but confirmed that subscription verification and premium model access remain server-side.
Anthropic released Opus 4.7, and OpenAI turned Codex into a computer work agent
This week in AI brought several shifts: Anthropic updated Opus 4.7, OpenAI gave Codex computer control, and Google and Baidu unveiled new voice and visual models.
ChatGPT Nailed the Diagnosis in Five Cases, But Failed on Treatment Planning
In a five-case medical comparison, ChatGPT never misdiagnosed the primary condition—but fell noticeably short on practical recommendations, testing, and patient management.
Why LLM Services Ignore Your Instructions and How to Actually Regain Control
Even a detailed prompt doesn't guarantee a compliant response: this article explains why LLMs break format, succumb to injections, and require not just text, but engineering constraints.
Google and OpenAI Hit the Limit: What Happens When the Internet Runs Out of Human Text
Generative AI not only drains website traffic through AI summaries, but also undermines its own training data foundation: the less incentive people have to write, the worse the internet and future models will become.
How Moscow Credit Bank Shows the Evolution of Employee Training in Banking — From Clerks to AI
Moscow Credit Bank traced how banks trained employees from coin verification and business correspondence to personalized onboarding, compliance, and AI assistants.
OpenAI integrates Sky technologies into Codex for Mac and enhances background app management
OpenAI has integrated Sky capabilities into Codex for Mac: the agent now manages multiple applications in the background, uses independent cursors, and handles routine tasks more accurately.
Habr AI Explained How Data-Driven Solution Search Changes Client-Server Architecture
The Habr AI article examines how expert systems with data-driven solution search should structure user interaction locally, on a local network, and over the Internet.
Seedance 2.0 draws attention with hyper-realistic generation of people and scenes
Seedance 2.0 multimodal system accepts text, images, audio and video, outputting nearly cinematic videos that have already sparked debate over deepfake risks.
Claude Code and Codex Are Changing the Rules: Prompts Give Way to Context Engineering
An analysis of Context Engineering reveals why in Claude Code, Codex, and agentic IDEs, it's not the prompt that matters, but how memory, system instructions, tools, and the entire context structure are organized.
Why diffusion models leave seams on 40-megapixel photos and how to give tiles memory
The article examines why tiling breaks 40–150-megapixel frames in diffusion models and what memory mechanisms from video diffusion can be transferred to photos.
Lubomir Gorbatko Introduces Sessa — An Alternative to Transformers and Mamba
Habr published an analysis of the Sessa architecture, where the author attempts to combine the strengths of Transformer and Mamba to better handle long context without losing manageable memory.
Harvard Business Review: how active AI use leads to "brain overheating"
Harvard Business Review describes the AI brain fry effect: the more actively employees rely on Claude, Gemini, and agents, the higher the risk of cognitive fatigue, confusion, and declining decision quality.
Flag Soft: Dali Trial benchmark helped select LLMs by quality, speed, and cost
The Dali Trial benchmark compared LLMs across three criteria important for product implementation: answer quality, processing speed, and total cost.
Habr AI: Instead of Complex Agent Pipelines, Developers Should Embrace Markdown, Git, and Session Memory
Habr published a manifesto against overloaded agent pipelines: the author argues that for complex AI development, sessions, roles, rules, and git matter more than LangChain and vector DB.
opencode-policy Plugin Adds 309 Rules to Protect AI-Agents from Injections and Data Leaks
For the opencode environment, a deterministic filter with 309 regex rules has been proposed: it intercepts prompt injection and dangerous tool calls before access to shell, files, and secrets.
Eltex engineer explained how to run federated learning on edge devices with 256 MB of memory
An Eltex engineer in an article inspired by AiConf breaks down how to apply federated learning on edge devices with less than 256 MB of RAM, where memory becomes the main constraint.
Claude and Ralph: Two Approaches to Building a Complex AI-Enabled DatePicker in Product Development
Using an accessible DatePicker as an example, the authors compared rapid AI drafting via Claude with Ralph's systematic approach, where quality is determined by architecture, tests, and strict constraints.
Habr AI Explained How to Build a Production Agent With Durable State, Steps, and Events
Habr AI published a practical guide to AI-agent architecture: the author recommends storing the execution flow, plan steps, and event logs so the system survives failures and shows transparent progress.
Diasoft explains why junior developers, AI magic, and in-house platforms don't save dev projects
Diasoft debunks three myths of custom software development: mass hiring of junior developers, hope to fully rewrite legacy code with AI, and the idea of quickly building an in-house platform.