News : sketchbook-v8 notebook.

See this website.

News : Update Highlights: The Journey Since Launch | Crimson Desert .

News : Elveran online new event ...

Tool : Grok Connectors

Grok Connectors are deep integrations that allow Grok (the AI assistant developed by xAI) to access and interact with external applications and data sources directly within a conversation. Launched on May 6, 2026, they are available on Grok Web, iOS, and Android for all users.

These connectors enable Grok to read, search, summarize, draft, edit, or perform actions across everyday tools without requiring constant copy-pasting or switching between applications. This transforms fragmented workflows into seamless experiences. For example, Grok can summarize emails, analyze spreadsheets, update calendars, review code repositories, or manage project tasks based on natural-language requests.

News : FINAL FANTASY RESONANCE | Vision – Cloud

Tool : termux and Text User Interfaces demo.

The combination of Termux, Text User Interfaces (TUI), and C using ncurses turns an Android smartphone into an ultra-fast, lightweight, and highly efficient retro development environment. Optimized for lightweight performance, this setup delivers exceptional speed with minimal memory usage directly on mobile devices. Its main strength lies in a seamless hybrid interaction model, perfectly blending traditional keyboard navigation with full touchscreen support for an intuitive mobile coding experience.

In our tui_complete_001.c code, we built a comprehensive suite of C-based TUI controls inspired by classic Turbo Pascal IDEs. Navigation flows naturally through multi-level hierarchical menus with submenus and a top-tab system. The interface features touch-responsive Yes or No confirmation dialogs, temporary red toast alert notifications, and a login form with automatic password masking. For interactive data management, the code integrates a multi-select checklist, a structured data table grid, a scrollable list view, an interactive slider, and a real-time animated progress bar, resulting in a robust and responsive C framework built entirely inside Termux.

Tool : Can you share AdSense links on social media? essential rules.

Navigating Google AdSense Policies: What You Can and Cannot Do on Social Media

If you run a monetized website using Google AdSense, leveraging platforms like Threads, X (Twitter), Facebook, or LinkedIn to drive traffic is a great strategy. However, there is a fine line between legitimate traffic acquisition and policy violations. Understanding the terminology used by Google and how social media promotion affects your AdSense account is essential for long-term success.

1. Key Terminology Explained

To understand Google’s expectations, you first need to get familiar with their core terminology:

• AdSense Policies: Google's strict set of guidelines governing content quality, user experience, and ad implementation.
• Invalid Traffic (IVT): Any clicks or impressions that artificially inflate an advertiser's costs or a publisher's earnings. This includes bot traffic, accidental clicks, or forced/encouraged clicks.
• Traffic Sources: Where your website visitors come from (e.g., Organic Search, Social, Direct, Referral).
• Click Encouragement / Incentivized Clicks: Directly or indirectly asking users to view, click, or interact with ads on your website.

2. What Is ALLOWED (What Google Permits)

Google encourages publishers to grow their audiences across different channels, provided the traffic consists of genuine users.

• Sharing Organic Content Links: You are fully permitted to share links to your monetized blog posts or articles on Threads, Facebook, Instagram (via bio/stories), X, or LinkedIn.
• Running Paid Social Campaigns: You can run legitimate paid ad campaigns on platforms like Meta Ads or LinkedIn Ads to drive targeted traffic to your site, as long as the incoming traffic consists of real humans who actively want to read your content.
• Sharing Value-Driven Teasers: Posting engaging captions, summaries, or infographics that encourage people to click through to read the full story on your website is completely fine.

3. What Is NOT ALLOWED (Strict Violations)

Google’s primary goal is to protect advertisers from paying for low-quality or accidental clicks. Violating these rules can result in ad serving limits or permanent account bans.

• Encouraging Clicks: Asking followers to "Support me by clicking the ads" or "Check out the banners on my page" leads to instant account termination.
• Misleading Captions (Clickbait): Posting a caption or image on social media that promises one thing, but leads to a completely unrelated page stuffed with ads.
• Spamming Groups & Comments: Blasting your link in unrelated comment sections or groups. This brings low-intent traffic that results in accidental clicks and Invalid Traffic (IVT) flags.
• Creating "Click Swaps": Participating in Facebook or Reddit groups where members agree to click on each other's website ads ("Click for Click").

4. The Potential Risk: Low-Intent Social Traffic

Even if you follow all rules, social media traffic behaves differently from Organic Search traffic (SEO):

• Search Engine Visitors (SEO): They actively searched for a problem and came to your site to read the solution. They stay longer and interact naturally with your page.
• Social Media Visitors: They are casually scrolling, click your link on impulse, and often leave within seconds. If they accidentally tap an ad while trying to leave or scroll quickly, Google may mark these as Invalid Clicks and temporarily limit ads on your account.

Best Practices for Promoting Monetized Posts

• Focus on Value: Make sure your social media post clearly describes what the article is about so only genuinely interested users click through.
• Optimize Ad Placement: Ensure your site ads are not placed directly under navigation buttons or headers where mobile social media users might tap them by accident.
• Diversify Traffic: Do not rely 100% on social media traffic. Balance your traffic sources with organic search (SEO) and email newsletters to maintain a healthy AdSense account health score.

News : The Eternal Life of Goldman | What Would I Draw? | THQN Showcase 2026

News : Hello Kitty Island Adventure – Tea Garden DLC Launch Trailer – Nintendo Switch 2.

News : Tom Clancy's Ghost Recon® Wildlands: Official Predator Mission Trailer.

News : Aliens: Fireteam Elite 2 - Co-Op Showcase

Tool : Acode an extensible, powerful and open-source code editor for android.

Acode is a free, open-source Android IDE that combines a professional code editor, a full Alpine Linux terminal, and native support for AI coding agents — Claude Code, OpenAI Codex, and OpenCode. It has 3.6M+ downloads and 5,458+ GitHub stars. Licensed under MIT.

See the official website.

News : Announcement Trailer | Sins of a Solar Empire II: Harbinger Expansion

News : okémon Pokopia – Bubbly Basin Launch Trailer – Nintendo Switch 2.

News : What is Pieces?

News : Ollama upgrade for DeepSeek-V4-Flash-0731 model.

DeepSeek-V4-Flash-0731 is now available on Ollama's cloud. This update substantially enhances the model's agentic capabilities:

ollama run deepseek-v4-flash:0731-cloud

News : First Look: Machines of Beans & Alpacas

News : SideFX and NVIDIA advanced Model Context Protocol.

SideFX and NVIDIA advanced Model Context Protocol (MCP) support for AI agents in Houdini 22’s rigging workflow, highlighted in coverage dated 30 July 2026 tied to SIGGRAPH 2026. SideFX is adding MCP support via an early-preview Apex Script Comfort Package (headed to SideFX Labs). This supplies AI assistants with curated Apex Script syntax, documentation, examples, a Visual Studio Code extension, a Python panel, and a validator. It enables natural-language generation and refinement of procedural character-rigging code that the artist then owns as plain script (no ongoing LLM dependency).

News : Krita 5.3.3 and 6.0.3 were released.

Krita 5.3.3 and 6.0.3 were released on 29 July 2026. These are maintenance releases focused on stability rather than major new features.

They contain numerous bug fixes and improvements, including animation timeline and frame-switching reliability, font loading/handling (vertical metrics, family sorting, duplicates), selection action panel enhancements (including pinning), comic panel editing tool fixes, crash resolutions (text shapes, transforms, null events, combined shapes), metadata handling for XMP/Exif, FFmpeg 7.0+ HDR animation rendering, and various UI adjustments.

Android-specific updates: supporter benefits via Play Store (resource bundle downloads, including paid Digital Atelier, without paywalled features or nags), removal of non-functional animation import/export pending a proper replacement, full-screen handling, and runtime UI scale. Krita 5.3.3 (Qt5-based) is recommended for production work. Krita 6.0.3 (Qt6-based) remains more experimental due to the port.

Downloads are available for Windows, Linux (AppImage), macOS (minimum now 10.15 for 5.3.3), and Android (beta; tablets only for 5.3.3). Source is shared

News : Starsand Island | Full Release Date Announcement Trailer

Tool : UserLAnd - linux on android.

UserLAnd - linux on android. See the android play store.

News : Learn how to play, join the open playtest.

News : Leafy Corner Launch Trailer.

News : Introducing Doriax Engine — A free and open-source game engine with Lua and C++ scripting.

Tool : porteus vbox uefi

after one day works well on 900Mb usb stick ...

News : Figma Motion basics: Motion timeline

News : How Autonomous AI Is Transforming Chip and System Design

News : OBS released new version.

OBS Studio 32.2 is now available!

Lots more quality of life adjustments and code cleanup as we continue to concentrate on user experience, stability, and long term project health.

The biggest change this patch is the overhauled Add Source window.

See the official GitHub project.

Tool : F-Droid vs Google: Security, Open Source Software, and Android Privacy

A comprehensive guide to F-Droid, the open-source Android app store, and its major security and privacy differences compared to the Google ecosystem.

What is F-Droid and why does it matter for Android

F-Droid is an alternative application store for FOSS (Free and Open Source Software) designed for users who want total control over their data and installed mobile apps.

• Total transparency through verifiable source code audited by the global developer community.
• Complete elimination of tracking modules, advertisement networks, and telemetry code.
• Full independence from Google Play Services and mandatory user account sign-ins.
• Direct compilation of APK packages from verified official developer repositories.

Key benefits of using open-source applications from F-Droid

• Zero intrusive advertisements and no hidden in-app purchases or paywalls.
• Advanced protection for personal data privacy and web browsing history.
• Transparent system warnings called Anti-Features for every application entry.
• Reduced battery consumption and system resource usage without background trackers.

The philosophical divide between F-Droid and the Google ecosystem

The fundamental reasons why F-Droid stands as a true alternative to Google Play center around development philosophy and user data rights.

• Google relies on data collection and targeted advertising while F-Droid advocates pure software freedom.
• Google Play forces reliance on proprietary APIs while F-Droid favors open protocols like UnifiedPush.
• F-Droid preserves developer anonymity and user digital sovereignty without central gatekeeping.

Top recommended FOSS applications available on F-Droid

• NetGuard for granular firewall control and internet access blocking on a per-app basis.
• NewPipe for ad-free background video playing without tracking or Google login.
• Aegis Authenticator for secure offline two-factor authentication token management.
• Mull and Fennec for privacy-hardened web browsing powered by Firefox engines.

Conclusion on mobile security and digital freedom on Android

Choosing F-Droid provides a higher standard of cybersecurity and privacy on mobile devices. By relying on open-source applications, you eliminate big-tech dependency and maintain full ownership of your smartphone.

News : Unity 7 announcement.

News : HomeGrown Devlog - Finishing the Main Menu.

News : Corsair Cove - Skull Rock Island | Pirate City Builder

News : Star Trek Online: The Kelvin Timeline Bundle

Tools : ... publicly available 4K visualizations of NASA.

NASA Scientific Visualization Studio is based out of the Goddard Space Flight Center (GSFC), located in Greenbelt, Maryland. The core studio consists of a team of (approximately) 15 visualizers, some of whom have been working with the studio for almost 30 years. The SVS's visualizers specialize in a wide variety of disciplines — astronomy, planetary science, climatology, cartography, and 3D modeling (to name a few) — but are united by a common love of making science accessible.

See the official website.

News : New in Construct 3 r495: 3D rotation, 3D editor improvements & more.

News : Blender 5.2 LTS - Showcase Reel.

Five days ago Blender 3D team comes with this video, about the Blender 5.2 LTD version.

News : How To Set Up Material Quality Levels with the Material Quality Switch Node - UNIGINE 2 Quick Tips

News : Vault Breaker Overview | Marathon

News : The Division 2: Dust Storm Event Trailer

News : Bringing Agent-Ready Simulation Into Blender

News : Scrap Mechanic: 1.0 & Drilling Thunder - Trailer

News : GTA Online: The Kortz Center Heist Now Available

News : Houdini 22 | How to Create Pyro in COPs | Configure Pyro Recipes

Tools : testing LiteRT on static website with codesandbox.io online tool.

This simple project on codesandbox.io creates a responsive web interface for a LiteRT-powered image classifier that enables users to load machine learning models and process images directly within the browser.

News : Spatialography on the VRChat.

Spatialography is a coined term that links Spatial （denoting space） with -graphy （denoting modes of depiction）․ Technologies such as photogrammetry and Gaussian splatting have brought new means to record and reconstruct real-world places․ Just as photography and film evolved from mere documentation into expressive media‚ so too will media that handle space develop techniques that go beyond simple recording․ This world exhibits a series of prototype works created with questions in mind˸ how can these techniques be used as modes of expression? which methods are suited to the format of space? is it possible to make works that seem to speak through space? Spatialography is not a single work title; rather‚ it is a term we use to denote the ongoing practice and inquiry of transforming recorded space into expressive form․

See this online tool application.

See the VRChat for this technologie.

News : Lazarus IDE version 4.8 - 06062026

Lazarus is a Delphi compatible cross-platform IDE for Rapid Application Development. It has variety of components ready for use and a graphical form designer to easily create complex graphical user interfaces.

See the official website.

The last version 4.8 was at 06062026.

News : Build Without Limits on Roblox.

... Today, we’re announcing Build, a new mobile-first creation tab within the Roblox app, and a new suite of AI-powered tools within Studio for creators of every level. On July 28, we’ll begin testing these new agentic tools. With Build and Studio, creators can delegate the parts of development that don’t require their full attention. ...

See the official roblox blogger website.

News : football stadium ruddy

See the official webpage.

Tools : Understanding the hidden productivity trap in modern LLM development.

Today, this post comes with content on how to develop when using development as a tool.

In the context of modern AI and LLM-based software engineering, Yak Shaving has mutated from a traditional infrastructure nuisance into a highly sophisticated, resource-consuming technical trap. Classic yak shaving usually involves deep-diving into OS package dependencies, resolving library conflicts, or rewriting compiler flags just to implement a minor feature. In contrast, AI Yak Shaving operates at the meta-layer of AI orchestration. It is the insidious process of building hyper-complex pipelines, custom routing frameworks, and hyper-optimized vector architectures for the sake of the infrastructure itself, completely isolating the developer from the core product value and functional outcome.

For a Development Manager or Lead Architect, identifying and mitigating this behavior is critical. When engineering velocity drops to zero while architectural diagrams grow exponentially, your team is knee-deep in an AI yak shave. Below is an exhaustive, technical analysis of how this manifests across modern AI development and how to architect your way out of it.

1. The RAG Architecture Rabbit Hole and Vector Store Sprawl

Retrieval-Augmented Generation (RAG) is arguably the most fertile ground for AI Yak Shaving. What should conceptually begin as a straightforward context injection mechanism frequently devolves into an over-engineered distributed database engineering project.

• The Pipeline Trap and Chunking Obsession: Developers often spend weeks isolated in a sandbox environment experimenting with advanced chunking strategies. They build recursive character text splitters, semantic paragraph clusterers, and parent-child document relationships before evaluating if the model actually needs that level of granularity. They write complex mathematical models to determine the absolute perfect overlap percentage (e.g., matching 15% vs 20% tokens), forgetting that modern LLMs possess high structural tolerance for slightly messy or redundant contexts.
• Embedding Over-Engineering: This manifests when days are lost benchmarking text-embedding-3-small against bge-m3, or attempting to fine-tune a custom embedding model on a minuscule corporate dataset. Teams spend precious hours writing internal benchmarking scripts to evaluate vector distance metrics like Cosine Similarity, Euclidean Distance, and Dot Product. They perform these micro-optimizations before verifying if the underlying data has even been properly cleaned, parsed, or structured for consumption.
• Vector Store Sprawl: The developer starts with a simple, in-memory vector database like Chroma or a local FAISS index. Within days, under the premise of future scalability, they migrate to Qdrant, then to Pinecone, and finally to Milvus. The engineering focus shifts completely away from text retrieval and entirely toward tuning HNSW (Hierarchical Navigable Small World) graph parameters, configuring M-values, adjusting ef_construction sizes, and writing complex metadata filtering layers. The task is no longer about answering user queries; it has become a distributed systems infrastructure project.
• The Modern Strategic Reality: The emergence of massive, production-grade Long Context Windows (ranging from 1 Million to over 2 Million tokens in models like Gemini 1.5 Pro) has fundamentally altered this landscape. A significant portion of RAG yak-shaving is now structurally obsolete for early-stage or mid-sized products. Instead of wasting developer cycles building a complex, fragile retrieval pipeline that introduces chunking errors, you can often stream the entire raw documentation, codebase, or dataset directly into the LLM’s context window. This approach leverages the model's native attention mechanism to find information, which is frequently more reliable, drastically faster to deploy, and eliminates weeks of infrastructure maintenance.

2. Model Hopping, Quantization, and Infrastructure Churn

When developers focus on the inference engine rather than the inference logic, they lose sight of the business value.

• The Hardware and Quantization Trap: Engineers spend days trying to squeeze a specific large-parameter open-weights model into a specific local VRAM boundary. They debug complex llama.cpp compilation build flags, benchmark the semantic degradation of 4-bit GGUF quantization versus 8-bit EXL2 configurations, and write custom python drivers to handle model offloading between CPU and GPU.
• Registry and Deployment Misery: The team gets caught up juggling Ollama registry versions, managing local vLLM or Hugging Face TGI (Text Generation Inference) Docker containers, and debugging local KV cache allocations or context shifting logic.
• The Shave: The developer is no longer building features, designing user interfaces, or validating product-market fit. They have inadvertently transitioned into a full-time Inference Engine Operator. They are optimizing system-level memory layouts for a model whose prompt structure could have been re-written or optimized in ten minutes to run flawlessly on an abstracted, managed cloud API.
• The Modern Strategic Reality: Unless your enterprise operates under hard, legally binding offline data privacy mandates, or has reached a scale where API costs strictly justify capital expenditure on dedicated GPU clusters, local-first infrastructure maintenance is a massive velocity sink. Managed serverless APIs abstract away the hardware misery, offering sub-second latencies and auto-scaling capabilities out of the box, allowing your team to focus exclusively on upstream application features.

3. The Illusion of Agentic Over-Orchestration

The industry fascination with autonomous agents has introduced a highly deceptive form of technical debt through frameworks like LangGraph, CrewAI, and AutoGen.

The typical symptom of this shave is the premature construction of hyper-complex state machines, endless circular tool-calling loops, and multi-agent hierarchical frameworks to solve problems that are inherently linear. Developers design Manager Agents that delegate tasks to Writer Agents and Researcher Agents, who then report back to an Editor Agent.

When this system is executed, it inevitably breaks down due to compounding token errors, state mutation bugs, and JSON parsing failures. The developer then spends their entire week writing robust, nested Self-Correction Loops and validation logic to force the agents to format their output correctly. They are debugging the orchestration framework rather than addressing the fact that the original task was too broad or ill-defined for an autonomous agent loop.

The industry is rapidly shifting away from chaotic, non-deterministic agent swarms and moving toward structured, predictable Agentic Workflows. This means abandoning complex, self-correcting autonomous loops in favor of linear, deterministic code pipelines. By utilizing Structured Outputs (forcing the LLM to adhere strictly to a Pydantic schema or JSON schema via constrained grammar at the inference level), you completely bypass the need for tool-output parsing scripts and self-correction loops. If a standard Python script can handle the step-by-step logic, do not use an agent swarm.

4. Breaking Free from Evaluation Paralysis

Evaluation is a critical component of shipping reliable software, but in AI development, it frequently transforms into the ultimate manifestation of procrastination and over-engineering.

Before a single customer has interacted with the application, the engineering team decides they cannot ship without a comprehensive, automated evaluation framework. They begin building a highly intricate LLM-as-a-judge system. This involves writing meta-prompts to evaluate prompt variants, generating synthetic evaluation datasets, and spending weeks analyzing precision, recall, and F1-scores for minor prompt modifications.

The fundamental trap here is that if you do not have actual production users, your synthetic evaluation dataset is merely a reflection of your own internal engineering assumptions. You are optimizing a test suite for a product whose real-world utility has zero validation. The modern approach dictates prioritizing Production Observability over upfront evaluation perfection. Deploying native telemetry tools (such as LangSmith, Phoenix, or OpenInference) allows you to log real user interactions, capture actual system failures, and build a high-fidelity golden dataset based on real-world usage rather than theoretical sandbox hypotheses.

5. The Hidden Cost: Cognitive Debt and Organizational Fatigue

The true damage of AI Yak Shaving is not merely measured in wasted hours or inflated cloud computing invoices; it is measured in the accumulation of Cognitive Debt and the degradation of engineering velocity.

• Context Switching Degradation: When a developer must simultaneously manage vector database indices, debug Docker network configurations for local model hosting, trace state mutations across an agent framework, and write PyQt6 UI wrappers, their capacity for deep focus on the core business problem is completely destroyed.
• The Opaque Black Box: Every meta-layer added to the AI stack introduces an abstraction that conceals underlying bugs. When the application returns a garbage output, the debugging surface area is massive. Is the error caused by a bad prompt, an improper chunking strategy, a vector distance calculation mismatch, an agent routing failure, or a model quantization bug? The system becomes untestable and terrifying to refactor.
• The Loss of Shared Technical Theory: As autonomous loops and complex pipelines multiply, the human development team loses their shared mental model of how the software operates. Engineers become hesitant to modify code for fear of triggering an un-traceable cascade of non-deterministic model failures across the pipeline. Product innovation completely freezes.

6. Strategic Management: The Complexity Budget and Blueprint

To systematically eliminate AI Yak Shaving from your organization, you must enforce a strict, tier-based Complexity Budget for every new feature development cycle:

• Tier 0 (Zero-Abstraction Baseline): Implement the feature using a single, well-structured API call combined with direct Prompt Engineering. Utilize system prompts and few-shot examples. If this satisfies 80% of the target acceptance criteria, development stops here. Do not add code.
• Tier 1 (Deterministic Augmentation): If Tier 0 fails due to context limits or data access, implement a basic context injection (load the file directly into the context window) or a simple, single-index vector lookup. Use native Structured Outputs to ensure predictable data schemas.
• Tier 2 (Orchestrated Complexity): Only when Tier 1 exhibits proven, measurable performance bottlenecks that directly harm the end-user experience are you allowed to introduce advanced architectures like multi-stage prompt chains, custom RAG pipelines, or specialized local model deployments.

As a Development Manager, apply the 60-Minute Zero-Latency Deployment rule. If an engineer cannot take a new product requirement and stand up a crude, functional, end-to-end prototype using a basic API call within 1 hour, your engineering organization is actively shaving a yak. Strip away the frameworks, bypass the infrastructure, eliminate the local registries, and force the system back to its simplest mathematical primitive: an input string, a model call, and an output string. Ship a functional product first, capture real telemetry, and engineer complexity only when driven by hard production data.

News : Meet Kimi K3

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Tools : Sinemarka Bookmark Toolkit | bookmarks, broken links, redirects, and bot-protected pages ...

I'm Bilal Gümüş, a web developer based in Istanbul working under the Sinemarka brand. I build interfaces that feel calm, considered and fast — the kind of software that gets out of the way and lets people do their work.

Sinemarka Bookmark Toolkit is a comprehensive, local-first Firefox extension designed to help users clean, analyze, and reorganize years of accumulated bookmarks. It performs deep scanning of both bookmarks and open tabs, identifying broken links, redirects, bot-protected pages, and timeouts. All operations run entirely on the user's device, with no cloud connection, no account requirement, and no external data transfer. This makes the extension ideal for users who prioritize privacy while managing large bookmark collections.

The extension includes a powerful health-checking system that evaluates each bookmark's HTTP status. It distinguishes between genuinely broken links and benign HTTP-to-HTTPS upgrades, ensuring that functional pages are not mistakenly flagged. Cloudflare or bot-protected pages are marked as protected instead of broken, providing more accurate diagnostics. Long scans can be paused and resumed, and users can configure per-URL timeouts to fine-tune performance.

Organization features are extensive. Users can organize bookmarks by domain, select specific domains for cleanup, find duplicates, and fix redirects in bulk. Broken links can be archived into a dedicated folder, allowing users to revisit them anytime. Individual folders can be renamed, moved, or scanned independently, and the extension supports undoing the last change to prevent accidental data loss. These tools make it possible to transform a chaotic bookmark library into a structured, efficient system.

Import and export capabilities are robust. Users can generate styled HTML reports in their active Firefox theme and language, export bookmarks in browser-importable Netscape HTML format, or choose Markdown and JSON exports. The extension also supports importing bookmarks from HTML files, making it compatible with other browsers and external bookmark managers. This flexibility is valuable for users who migrate between browsers or maintain multiple bookmark archives.

The interface is designed for usability and accessibility. It offers Light, Dark, and Rosé themes, adjustable fonts, and the option to use a side panel or a full-tab interface. The extension is available in English, Türkçe, and Español, making it accessible to a wide international audience. Because everything runs locally, users benefit from fast performance and complete privacy.

• Local-first scanning of bookmarks and open tabs for broken links, redirects, and bot-protected pages.
• Accurate HTTP status detection with special handling for Cloudflare-protected pages and HTTPS upgrades.
• Pause and resume functionality for long scans, with configurable per-URL timeouts.
• Domain-based organization with per-domain selection for targeted cleanup.
• Bulk duplicate detection and redirect fixing for large bookmark collections.
• Archiving of broken links into a dedicated folder for later review.
• Folder-level operations including rename, move, scan, and undo.
• Export options including styled HTML, Netscape HTML, Markdown, and JSON.
• Import support for browser bookmark HTML files.
• Customizable interface with multiple themes and adjustable fonts.
• Full privacy with no backend, no cloud, and no data collection.

Sinemarka Bookmark Toolkit is particularly valuable for users who have accumulated thousands of bookmarks over many years. These collections often contain outdated links, duplicates, and redirects that reduce browsing efficiency. By performing deep analysis and offering advanced cleanup tools, the extension helps users restore order and maintain a healthy bookmark ecosystem. It is especially useful for researchers, developers, content creators, and anyone who relies heavily on bookmarks for daily work.

The extension's ability to scan open tabs alongside bookmarks provides an additional layer of utility. Users can identify broken or redirected pages they currently have open, making it easier to manage active browsing sessions. This feature is helpful for users who work with many tabs simultaneously and need to ensure that all resources remain accessible.

Because Sinemarka Bookmark Toolkit supports exporting structured reports, users can share or archive detailed analyses of their bookmark collections. These reports can be used for documentation, migration, or long-term storage. The availability of Markdown and JSON exports also makes the extension suitable for technical workflows, automation, or integration with external tools.

Overall, Sinemarka Bookmark Toolkit stands out as one of the most advanced bookmark management extensions available for Firefox. Its combination of privacy, performance, deep scanning, flexible organization, and rich export options makes it a powerful solution for both casual users and professionals. By using this extension regularly, users can maintain a clean, organized, and efficient bookmark library that remains useful for years to come.

For users who frequently import bookmarks from multiple browsers, synchronize across devices, or maintain large research archives, Sinemarka Bookmark Toolkit provides a reliable and comprehensive way to manage link health, structure, and long-term accessibility. Its local-first design ensures that all operations are fast, secure, and fully under user control.

• Ideal for researchers, developers, and heavy bookmark users who require long-term stability.
• Suitable for users migrating between browsers or consolidating multiple bookmark archives.
• Provides accurate diagnostics for link health and redirect behavior.
• Supports large-scale cleanup operations without compromising privacy.
• Offers a professional-grade interface with multiple customization options.

With its extensive feature set and privacy-focused architecture, Sinemarka Bookmark Toolkit is a valuable addition to any Firefox installation. It helps users reclaim control over their bookmarks, eliminate clutter, and maintain a clean browsing environment. Whether you are dealing with a few hundred bookmarks or tens of thousands, the extension provides the tools needed to analyze, organize, and preserve your digital resources effectively.

News : What's New in Blender 5.2 LTS! Official Overview

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News : online game procedual Townscaper by Oskar Stålberg.

See this game named Townscaper by Oskar Stålberg artist.

News : D-topia | Launch Trailer

News : Android Studio Quail 2 stable version with multi-task and the Android Studio AI agent.

Android Studio Quail 2 is now stable and ready for you to use in production, bringing a shift to your IDE with concurrent agentic workflows, natively integrated memory leak profiling, and context-aware crash remediation. Whether you are performing a sweeping architectural overhaul, tracing a memory leak, or resolving a critical production crash, Android Studio keeps you anchored in your workspace by reducing manual friction.

In Android Studio Quail 2, we've been hard at work redesigning Agent Mode from the ground up. This new architecture provides better performance, offers more flexibility for decomposing complex tasks, and improves the suite of internal tools the agent uses to do its work.

See the official blog website.

News : The Mound: Omen of Cthulhu | Launch Trailer

News : The Alters: Last Variable | Launch Trailer

News : How to Use Split View in Brave Browser (Underrated Productivity Hack)

News : Battlefield 6 Season 4 Naval Official Gameplay Trailer

News : Blender 5.2 LTS Released - Awesome New Features are Here! by askNK.

News : Assembly language and how hard can be , even on hacking area ...

Because, I work with the assembly programing language you can see these two videos ...

Gedare Bloom - youtube channel.

Daniel Hirsch - youtube channel.

News : Once Human | 2nd Anniversary: Dreamy Maelstrom

News : The Scariest Chart In Electrical Engineering

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News : SAP on Google Cloud | The big picture

Tools : vast the infrastructure layer ...

Vast is the infrastructure layer where AI agents autonomously design, procure, and optimize their own compute. API-native provisioning. Real-time pricing. Per-second billing.

See the official webpage.

Tools : The higgsfield online tools.

A set of tools with artificial intelligence.

See the official website.

News : Actively Exploited LiteLLM Flaw Puts Enterprise AI Gateways At Risk | CVE-2026-42271

News : A New Realtime Geo. Compression Tool Is Here! by askNK

News : You Once Human | 2026 Second Half Preview

News : Spirit City: Lofi Sessions - Magical Library DLC - Teaser Trailer

News : monolith-terrain an interactive, real-time 3D terrain map.

An interactive, real-time 3D terrain map in the style of a vintage USGS topographic sheet, crossed with a sci-fi FUI overlay. Load real-world elevation data for anywhere on Earth, or generate procedural mountain ranges — then explore them with contour lines, hypsometric tinting, survey grids, spot elevations, clickable peak markers, radar scans, and cinematic camera tours.

See the official GitHub project - monolith-terrain.

News : GeoLibre v2.0 demo .

Tools : Total Commander - android application.

The old Total Commander is now on android google play.

News : Mod Spotlight - June 2026 | Farming Simulator 25

News : Glenmara: Still Life Artist Announcement Trailer

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Three.js Water Pro.

Real-time, physically-based ocean rendering for Three.js WebGPU.

See the official website

News : Blender 5.2 LTS - Release Candidate!

Blender 5.2 LTS has reached Release Candidate! 🚀

Now's the time to put it to the test and report any issues. Let's make this release as stable as possible!

See the official website.

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News : LiteRT.js, Google's high performance Web AI Inference from Google

We are excited to announce LiteRT.js, a JavaScript binding of LiteRT for running AI directly inside the web browser. By bringing the trusted on-device inference library LiteRT to the web, web developers can now run ML and AI models with maximum performance entirely locally. This means enhanced user privacy, zero server costs, and ultra-low latency for real-time experiences. For developers with existing .tflite models, LiteRT.js makes deployment to mobile and desktop web browsers smoother than ever, serving as a powerful evolution from TensorFlow.js for executing .tflite models.

See the official webpage.

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News : PointDiT: Pixel-Space Diffusion for Monocular Geometry Estimation

State-of-the-art single-image 3D reconstruction methods often rely on complex hybrid architectures and loss functions, or compress geometry into latent spaces in order to leverage pre-trained latent diffusion models. In this work, we show that such architectural overhead and intricate loss formulations are unnecessary. We introduce a minimalist pixel-space Diffusion Transformer, built on a plain ViT, that operates directly on raw 3D point map patches and is conditioned on image tokens from a pre-trained DINOv3. Unlike existing latent diffusion approaches, we train our diffusion backbone entirely from scratch, eliminating the need for point map tokenizers. Despite its simplicity, our approach surpasses complex latent-based diffusion models while remaining significantly simpler than hybrid alternatives. Notably, it produces sharper geometric structure and is more robust in highly ambiguous regions, such as transparent objects.

See the official huggingface.co website.

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News : Laguna XS 2.1 from Ollama.

Laguna XS 2.1 is a 33B total parameter Mixture-of-Experts model with 3B activated parameters per token designed for agentic coding and long-horizon work on a local machine.

See the official website.

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Tools : simple guide of the most relevant terms, structured as a specialized in development.

Today, with a little help of artificial intelligence I created this a comprehensive synthesis of the most relevant terms, structured as a specialized guide.

In the software development field, jargon and slang are extremely rich, evolving rapidly alongside new technologies.

1. Code Quality and Technical Debt

These terms are used in professional environments to evaluate the state of a codebase and the trade-offs made during development:

• Technical Debt: Decisions made to deliver a feature quickly at the cost of lower quality, which will require additional effort to correct later.
• Code Smell: Symptoms or patterns in the code that suggest a deeper design problem, even if the code is functional.
• Spaghetti Code: Source code with a complex and incomprehensible control structure, often the result of chaotic development.
• Code Rot: The process by which a software system becomes increasingly difficult to maintain and more prone to errors as it is modified over time.
• Maintainability Index: A software metric that measures how easy it is to maintain, modify, and understand a codebase.
• Brittle Code: Code that breaks as soon as you change a single setting or a small part of the input.

2. Slang for Poor Quality (Beyond Slop)

• Boilerplate: Repetitive, standard code that must be written to make a feature work but adds no unique logical value.
• Cargo Cult Programming: The practice of copying and implementing code snippets or design patterns without understanding why they are used.
• Quick and Dirty: A solution implemented rapidly, without a solid structure or maintainability, usually with the intention of being refactored later.
• Kitchen Sink: Code or a project where everything has been added, without a clear direction, resulting in an oversized and unmanageable codebase.
• Hack: An inelegant solution that fixes something for the moment but creates significant risks in the long term.
• Low-effort slop: A slang term borrowed from creative and online communities to describe mass-generated content that lacks added value or attention to detail.

3. Processes, Errors, and Productivity

• Yak Shaving: The situation where you start a simple task but realize you have to solve a minor problem, then another, and another, until you lose hours doing things completely unrelated to the main objective.
• Bikeshedding: The phenomenon where the team spends hours discussing trivial details instead of focusing on the critical architecture of the project.
• Heisenbug: A bug that disappears or changes its behavior when you try to investigate or debug it.
• Race Condition: An error that occurs only under very specific timing conditions, making it extremely difficult to reproduce in a controlled manner.
• Zombie Code: Code that is no longer used by anyone in the application but has not been deleted because programmers are afraid that if they remove it, something will break.
• Rubber Ducking: The method of explaining your code, line by line, to an inanimate object. The act of explaining often helps you find the logical error yourself.

4. The AI Paradigm: Risks and Automation

• Prompt Engineering: Although it has become a technical term, in the programming community it is sometimes used ironically to describe the process of trying to get the AI to produce something useful through repeated trial and error.
• AI-in-the-Middle: The situation where a programmer no longer understands the logical flow of their application because they have delegated too much to an AI assistant, losing control over the code architecture.
• Hallucination: Used to describe code or a model that has a high probability of generating false information, logical errors, or calls to non-existent libraries.
• Stochastic Parrot: A critical term describing language models that repeat statistical patterns without understanding the meaning or context of what they are generating.
• Shadow Code: Code introduced into a project without being fully understood or reviewed.
• Copy-Paste Programming: The practice of taking code without understanding how it works or how it interacts with the rest of the system.

5. AI Yak Shaving (AI Infrastructure Pitfalls)

• The RAG Architecture Rabbit Hole: Instead of a simple context injection, the developer becomes obsessed with chunking strategies, vector distance metrics, and migrating between vector databases.
• Model Hopping: Occurs when the focus shifts to the provider or model architecture rather than the inference logic, spending hours fine-tuning quantization parameters or local registry versions.
• Agentic Over-Orchestration: Getting lost in Agentic Frameworks, building complex state machines and multi-agent hierarchies for a task that is essentially a linear sequence of inputs.
• Evaluation Paralysis: Building systems to evaluate LLM outputs using another LLM before shipping any feature, thereby optimizing the evaluation system instead of validating the product value.

6. Testing and Validation in the AI Era

• Golden Master Testing: A fundamental testing technique originating from the music and film industry. It involves running a system with a set of inputs and capturing the output in a known, correct state. When AI modifies the code, the output is compared to this Master to verify if the changes are safe.
• Mutation Score: A metric that quantifies the AI drift, representing how many changes were required to make the AI-generated code behave like the Golden Master.
• LLM-as-a-Judge: Using a second, distinct AI instance that receives the input, output, and code to evaluate if the output is logically consistent with the requirements.
• Property-Based Testing: Instead of checking for an exact match, the AI is prompted to verify if essential properties hold true.
• Self-Healing Tests: A framework where a failed test triggers the AI-Author again with instructions to rewrite the code based on the specific error, effectively allowing the AI to debug itself.
• Circular Hallucination: The risk that an AI-Judge evaluates the code positively simply because it was trained on the same data as the Author, sharing the same biases or errors.

7. Governance and Structured Logging

• ADRs (Architecture Decision Records): The gold standard for recording decisions; this is where you document a Hack or a Quick and Dirty solution, transparently acknowledging the Technical Debt you are incurring.
• Structured Logs (JSONL): For an AI to learn from development history, logs must be structured rather than stored as unstructured text.
• Remediation Engine: Feeding your structured logs into a more capable AI model using a Meta-Prompt to analyze recurring patterns of logic errors and suggest system prompt updates or coding standards.
• Human-in-the-Loop (HITL): The ultimate safety standard; the developer defines Trust Checkpoints. If a module passes the AI-Judge and Golden Master tests repeatedly, it becomes Trusted Code and is merely monitored rather than re-verified.

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News : Grok Voice Agent Builder Beta.

Voice Agent Builder is now live in beta: a no-code platform for production voice agents with Grok Voice. Every account includes a free phone number. Create a voice agent in under 2 minutes, then call it from your browser.

It’s for operators and developers who want high-volume production voice agents without building the stack from scratch. You get telephony, knowledge retrieval, tools, guardrails, and observability in one place. You can also keep what you already have: bring existing phone numbers, wire your APIs, or connect MCP servers.

Most voice stacks stitch together speech-to-text, a language model, and text-to-speech, often across different providers. Every hop adds latency and new failure modes. Voice Agent Builder is one interface built for Grok Voice, tightly coupled to the model.

See the official website.

Google Apps Script : example of transition from a Google Sheet to a formatted Google Doc.

This script that automates the transition from a Google Sheet to a formatted Google Doc. Here is a breakdown of what this solution does:

Custom Menu Integration: The script adds a Custom Menu directly into your Google Sheet interface. With a single click, you can trigger processes like fetching data or generating reports, making the tool incredibly easy to use without touching the code.

This example is based on this URL : https://www.planetpython.org/opml.xml.

Intelligent Data Processing: It doesn't just copy text; it parses RSS and Atom feeds, extracts titles and links, and prepares them for your document. It intelligently handles the HYPERLINK formulas you use in Sheets, translating them into real, clickable links in your final document.

Automatic Folder Management: One of the most useful features of this script is its ability to keep your Drive organized. Instead of cluttering your root directory, the script automatically identifies the folder where your source spreadsheet is located and creates the new document right there.

Built-in Troubleshooting: I have included logging functionality throughout the code. If a link is malformed or a feed fails to load, the script logs exactly what happened, allowing you to debug issues quickly via the Apps Script Dashboard.

Let's see the source code for Google Apps Scripts:

function onOpen() {
  SpreadsheetApp.getUi()
    .createMenu('Custom Menu')
    .addItem('Read OPML PlanetPython', 'fetchAndProcessFeed')
    .addItem('Download Selected Content', 'downloadSelectedContentWrapper')
    .addItem('Send Sheet via Email', 'sendSheetViaEmail')
    .addToUi();
}

function fetchAndProcessFeed() {
  const dateTime = Utilities.formatDate(new Date(), Session.getScriptTimeZone(), "yyyy-MM-dd_HH-mm");
  const spreadsheet = SpreadsheetApp.getActiveSpreadsheet();
  let sheet = spreadsheet.getSheetByName(dateTime);
  
  if (!sheet) {
    sheet = spreadsheet.insertSheet(dateTime);
  } else {
    sheet.clear();
  }
  
  sheet.appendRow(["Date", "Source", "Title", "Select"]);
  
  const opmlUrl = "https://www.planetpython.org/opml.xml";
  const opmlContent = UrlFetchApp.fetch(opmlUrl).getContentText();
  const opmlDoc = XmlService.parse(opmlContent);
  const outlines = opmlDoc.getRootElement().getChild("body").getChildren("outline");
  
  outlines.forEach(outline => {
    const text = outline.getAttribute("text")?.getValue().replace(/"/g, '""').replace(/[<>&]/g, '') || "";
    const xmlUrl = outline.getAttribute("xmlUrl")?.getValue() || "";
    
    try {
      const feedContent = UrlFetchApp.fetch(xmlUrl).getContentText();
      const feedDoc = XmlService.parse(feedContent);
      const root = feedDoc.getRootElement();
      
      if (root.getName() === "rss") {
        processRssFeed(root, text, xmlUrl, sheet);
      } else if (root.getName() === "feed") {
        processAtomFeed(root, text, xmlUrl, sheet);
      }
    } catch (e) {
      Logger.log(`Error processing feed ${text} (${xmlUrl}): ${e}`);
    }
  });
}

function processRssFeed(root, source, xmlUrl, sheet) {
  const items = root.getChild("channel")?.getChildren("item") || [];
  items.forEach(item => {
    const title = item.getChild("title")?.getValue().replace(/"/g, '""').replace(/[<>&]/g, '') || "";
    const pubDate = item.getChild("pubDate")?.getValue() || "";
    const link = item.getChild("link")?.getValue().replace(/[<>&]/g, '') || xmlUrl;
    sheet.appendRow([
      pubDate,
      `=HYPERLINK("${xmlUrl}", "${source}")`,
      `=HYPERLINK("${link}", "${title}")`,
      ""
    ]);
  });
}

function processAtomFeed(root, source, xmlUrl, sheet) {
  const entries = root.getChildren("entry") || [];
  entries.forEach(entry => {
    const title = entry.getChild("title")?.getValue().replace(/"/g, '""').replace(/[<>&]/g, '') || "";
    const updated = entry.getChild("updated")?.getValue() || "";
    const link = entry.getChild("link")?.getAttribute("href")?.getValue().replace(/[<>&]/g, '') || xmlUrl;
    sheet.appendRow([
      updated,
      `=HYPERLINK("${xmlUrl}", "${source}")`,
      `=HYPERLINK("${link}", "${title}")`,
      ""
    ]);
  });
}

function downloadSelectedContentWrapper() {
  downloadSelectedContent();
}

async function downloadSelectedContent() {
  const dateTime = Utilities.formatDate(new Date(), Session.getScriptTimeZone(), "yyyy-MM-dd_HH-mm");
  const spreadsheet = SpreadsheetApp.getActiveSpreadsheet();
  const sheet = spreadsheet.getActiveSheet();
  const data = sheet.getDataRange().getValues();
  const doc = DocumentApp.create(`Content_${dateTime}`);
  const folderId = DriveApp.getFileById(spreadsheet.getId()).getParents().next().getId();
  DriveApp.getFileById(doc.getId()).moveTo(DriveApp.getFolderById(folderId));
  
  let contentAdded = false;
  const body = doc.getBody();
  
  for (let i = 1; i < data.length; i++) {
    const row = data[i];
    if (row[3] == 1) {
      const sourceMatch = row[1].toString().match(/^=HYPERLINK\("([^"]+)",\s*"([^"]+)"\)$/);
      const source = sourceMatch ? sourceMatch[2] : row[1].toString().replace(/[<>&]/g, '') || "Unknown source";
      const titleMatch = row[2].toString().match(/^=HYPERLINK\("([^"]+)",\s*"([^"]+)"\)$/);
      const title = titleMatch ? titleMatch[2] : row[2].toString().replace(/[<>&]/g, '');
      const link = titleMatch ? titleMatch[1] : "";
      
      Logger.log(`Processing ${title} with link: ${link}`);
      
      try {
        body.appendParagraph(source).setHeading(DocumentApp.ParagraphHeading.HEADING1);
        const titleParagraph = body.appendParagraph(title).setHeading(DocumentApp.ParagraphHeading.HEADING2);
        if (link) titleParagraph.setLinkUrl(link); // Titlu ca hyperlink
        body.appendParagraph(""); // Spațiu între intrări
        contentAdded = true;
        Logger.log(`Added ${title} with link`);
      } catch (e) {
        Logger.log(`Error processing ${title} (${link}): ${e}`);
        body.appendParagraph(source).setHeading(DocumentApp.ParagraphHeading.HEADING1);
        const titleParagraph = body.appendParagraph(title).setHeading(DocumentApp.ParagraphHeading.HEADING2);
        if (link) titleParagraph.setLinkUrl(link);
        body.appendParagraph("");
        contentAdded = true;
      }
    }
  }
  
  if (!contentAdded) {
    Logger.log("No content was added to the document.");
    body.appendParagraph("No content was selected or available.");
  }
}


function sendSheetViaEmail() {
  const spreadsheet = SpreadsheetApp.getActiveSpreadsheet();
  const sheet = spreadsheet.getActiveSheet();
  const sheetName = sheet.getName();
  const data = sheet.getDataRange().getValues();
  
  let htmlContent = `
    <html>
      <head>
        <title>${sheetName}</title>
      </head>
      <body>
        <h1>${sheetName}</h1>
        <table border="1">
          <tr>
            <th>Date</th>
            <th>Source</th>
            <th>Title</th>
            <th>Select</th>
          </tr>
  `;
  
  data.forEach((row, index) => {
    if (index > 0) {
      const date = row[0] || "";
      const sourceMatch = row[1].toString().match(/^=HYPERLINK\("([^"]+)",\s*"([^"]+)"\)$/);
      const sourceUrl = sourceMatch ? sourceMatch[1] : "";
      const sourceText = sourceMatch ? sourceMatch[2] : row[1].toString().replace(/[<>&]/g, '');
      const titleMatch = row[2].toString().match(/^=HYPERLINK\("([^"]+)",\s*"([^"]+)"\)$/);
      const titleUrl = titleMatch ? titleMatch[1] : "";
      const titleText = titleMatch ? titleMatch[2] : row[2].toString().replace(/[<>&]/g, '');
      const select = row[3] || "";
      htmlContent += `
        <tr>
          <td>${date}</td>
          <td><a href="${sourceUrl}">${sourceText}</a></td>
          <td><a href="${titleUrl}">${titleText}</a></td>
          <td>${select}</td>
        </tr>
      `;
    }
  });
  
  htmlContent += `
        </table>
      </body>
    </html>
  `;
  
  const mimetype = "application/epub+zip";
  const containerXml = `
    <?xml version="1.0"?>
    <container version="1.0" xmlns="urn:oasis:names:tc:opendocument:xmlns:container">
      <rootfiles>
        <rootfile full-path="OEBPS/content.opf" media-type="application/oebps-package+xml"/>
      </rootfiles>
    </container>
  `;
  
  const contentOpf = `
    <?xml version="1.0" encoding="UTF-8"?>
    <package xmlns="http://www.idpf.org/2007/opf" unique-identifier="bookid" version="2.0">
      <metadata xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:opf="http://www.idpf.org/2007/opf">
        <dc:title>${sheetName}</dc:title>
        <dc:identifier id="bookid">urn:uuid:${Utilities.getUuid()}</dc:identifier>
        <dc:language>en</dc:language>
      </metadata>
      <manifest>
        <item id="content" href="content.html" media-type="application/xhtml+xml"/>
      </manifest>
      <spine>
        <itemref idref="content"/>
      </spine>
    </package>
  `;
  
  const blobs = [
    Utilities.newBlob("mimetype", "text/plain", "mimetype").setContentType(mimetype),
    Utilities.newBlob(containerXml, "application/xml", "META-INF/container.xml"),
    Utilities.newBlob(contentOpf, "application/xml", "OEBPS/content.opf"),
    Utilities.newBlob(htmlContent, "application/xhtml+xml", "OEBPS/content.html")
  ];
  
  const zipOutput = Utilities.zip(blobs, `Sheet_${sheetName}.epub`);
  
  MailApp.sendEmail({
    to: "catalinfest@gmail.com,catafest@yahoo.com",
    subject: `Sheet activ: ${sheetName}`,
    body: "Vezi atașat sheet-ul activ în format EPUB.",
    attachments: [zipOutput]
  });
}

Tools : Visual Code Ollama extension for developers.

Use Ollama models in VS Code Chat.

The Ollama extension adds models from your running Ollama server to the VS Code model picker.

Ollama 0.17.6 or newer is recommended for cloud model sign-in and richer model metadata. Older Ollama versions may still work for local models.

Requirements

• Visual Studio Code 1.120 or newer
• Ollama installed and running
• At least one local or cloud model available in Ollama

See the official Visual Code with Ollama extension.

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News : Google - View Space Locations by NASA.

I found a map with all view space locations on google by nasauofl@gmail.com.

News : Security - OpenCVE teams can use automations.

We’re excited to introduce a major evolution in how OpenCVE helps teams manage CVEs: Automations.

If you use OpenCVE today, you already know the value of tracking CVEs that match your vendors and products. But as subscriptions grow, so does the noise. Every update, every score change, every new reference can demand attention.

Automations give you control over when, why, and how OpenCVE reacts to the CVEs in your projects.

Vulnerability monitoring is not just about detection. Security, SOC, DevSecOps, and engineering teams need to prioritize, triage, and act without drowning in alerts.

Until now, much of that logic lived inside notification configurations: event filters, CVSS thresholds, delivery rules, all bundled together. That worked, but it was hard to extend. You could notify, but you couldn’t easily assign a CVE, change its status, or build a scheduled digest with the same flexibility.

See the official website.

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