New stories

The article reports that the United States is planning to fund far-right political forces in Europe, raising concerns about foreign interference in domestic politics and the potential strengthening of populist, nationalist movements across the continent.

With all the SaaSmageddon going on, I am wondering if companies like Anthropic and OpenAI reduced their SaaS usage and developed their own agents to do the work?

I built Crew to help manage multiple AI agents working on the same codebase.

It has two modes:

1. Design mode: Automated Writer ⇄ Reviewer loops to refine ideas into polished design docs

2. Crew mode: Run parallel AI agents (QA, DEV, JANITOR) for continuous code improvement

It's written in Bash and works with Claude CLI, OpenAI's opencode, or Google's Gemini.

Would love feedback from the HN community!

GitHub: https://github.com/garnetliu/crew

The article discusses the use of nextTick() in Vue.js, a function that defers the execution of a callback until the next update cycle. It explains the benefits of using nextTick() and provides examples of how to implement it in Vue.js applications.

While there are many tools like CodeRabbit that automate PR reviews, I noticed that relying entirely on AI to write reviews often led to me paying less attention to my colleagues' code. Therefore, rather than building just another "AI Code Reviewer," I designed HighReview as a "Code Review Tool assisted by AI." The goal is to help humans understand the code context more deeply and conduct reviews more easily, with AI acting as a support system. Additionally, when conducting detailed reviews, I often need to check out the branch locally to examine related code. This process is usually cumbersome (context switching, stashing current work, etc.). I built this tool to resolve these specific pain points and streamline my personal code review workflow.

Key Features - No Separate Login Required: Utilizes your local gh cli and local AI Agent. - Independent Review Environment: Checks out the target project into a directory separate from your current working local repository (allows for project-level reuse without disrupting your workflow). - Context-Aware AI Pre-review: Extracts related code using Tree-sitter to provide the AI with broader context, resulting in more comprehensive reviews. - Code Navigation: Supports code navigation within the Diff editor using Tree-sitter (I initially attempted this with LSP but pivoted to Tree-sitter). - Rich Analysis Features: Provides issue detection, explanatory diagrams, refactoring suggestions, side-effect analysis, and semantic analysis.(Note: Continuous prompt tuning is required for optimal results.) - Interactive AI Assistant: supports Q&A where you can ask the AI Assistant specific questions referencing the review results.

plz feedback. have fun. Thank you.

The article discusses the recent changes in the Git version control system, including improvements to the commit graph generation, bug fixes, and performance enhancements. The updates aim to make Git more efficient and user-friendly for developers.

The article explores the idea of 'unautomating' the economy, suggesting that a focus on human-scale production and decentralized decision-making can lead to a more sustainable and equitable economic system. It argues for a shift away from large-scale automation and centralized control towards a more localized, community-driven approach to economic activities.

I built Gettorr because I wanted a way to stream legal torrents (like Linux ISOs or Archive.org content) on my Chromebook without needing to install heavy clients like uTorrent.

It uses WebTorrent under the hood to handle the P2P connections in the browser. I focused on making the UI as minimal as possible—just paste a magnet link and start streaming.

I’d love to get your feedback on the streaming performance and if you run into any issues with different browser versions!

The article discusses a new study that suggests statins, commonly prescribed drugs to lower cholesterol, are safer than previously believed. The study found that the risks of side effects associated with statins are much lower than previously reported.

The article discusses the growing controversy around the use of a phonics-based reading instruction method called 'structured literacy' or 'the science of reading,' which an increasing number of states are attempting to implement in schools, despite concerns from some educators and advocates.

The article argues that AI tools will not significantly boost developer productivity, and that the industry's expectations around the impact of AI are overly optimistic. It suggests that while AI can assist in certain tasks, human creativity and problem-solving skills remain essential for software development.

I’m posting this analysis to the YC community because I value the technical rigor here, and I need a sanity check on a platform that is aggressively marketing itself right now: BTDUex.

For context, I spent the first two decades of my career in enterprise IT systems administration, dealing with server infrastructure, database integrity, and network security before shifting to full-time independent trading. I’ve survived the dot-com vaporware era, the 2008 financial meltdown, and every crypto winter since Mt. Gox. My "sysadmin gut check" for systemic risk is highly attuned, and BTDUex is currently triggering every alarm bell I have.

I’ve been auditioning their operations from the outside in, looking past the polished React framework of their frontend. I believe what we are looking at is not a legitimate fintech disruptor, but a sophisticated, modern iteration of a financial "honey pot," disguised by a high-latency Web3 wrapper.

Here is my technical breakdown of why the BTDUex architecture appears fundamentally fraudulent, specifically focusing on its critical failure point: the withdrawal logic.

1. The "Withdrawal Logic" Anomaly (The Architectural Smoking Gun) In any legitimate fintech architecture—whether centralized finance (CeFi) like Coinbase or decentralized finance (DeFi) like Uniswap—withdrawal logic follows a standard pattern: transaction fees, gas costs, or taxes are netted internally from the user's existing asset balance within the database or smart contract before the remaining funds are broadcast to the blockchain or wired to a bank.

When a user attempts to withdraw significant capital (often "profits" generated on the platform's simulated interface), the request is flagged by a backend "compliance" layer. The user is then informed via API response or support ticket that to "unblock" the withdrawal, they must deposit an additional external sum (often cited as a 15%-30% "tax" or "verification fee") via fresh USDT.

The Technical Implication: From a database integrity and systems standpoint, requiring external liquidity to unlock existing internal database entries is absurd.

If the user has $10,000 in their account and owes a $500 fee, a functional system executes Balance = Balance - Fee and sends the remaining $9,500.

BTDUex's requirement for a new inbound transaction to release an existing balance suggests that the internal ledger balance is disconnected from real, available liquidity.

This mechanism is the defining characteristic of a Ponzi scheme in its exit phase, or what’s known in security circles as a "pig-butchering" scam. The backend isn't connected to real liquidity pools; it's likely just a local ledger showing simulated numbers. The request for a "fee" is functionally a ransom demand to release data that has no real value behind it.

2. The "Wrapper Company" Pattern BTDUex appears to be a classic "wrapper company." They have invested heavily in the user interface layer—slick mobile responsiveness, real-time charting visualizations—to build immediate trust. However, the backend operations seem to be a black box operating in a regulatory vacuum.

If you attempt to trace their orders to an on-chain settlement or cross-reference their operating entities with major regulatory API endpoints (NFA, FCA, ASIC), you will find zero footprint. They are operating with the frontend aesthetics of a Tier-1 exchange but the backend compliance structure of a burner phone.

3. Operational Opacity as a Feature Furthermore, there is a noticeable pattern of convenient "system maintenance" events that lock users out during periods of high market volatility. While every platform has technical debt and downtime, the timing and lack of transparent, technical post-mortems from BTDUex suggest intentional throttling of user activity rather than legitimate infrastructure scaling issues.

Worried about reproducible builds? Let OpenAI generate your source code at compile time.

Built mostly for the meme, but maybe there's something there...?

The article discusses Ensemble, an open-source machine learning library that provides a unified interface for using various ensemble learning algorithms. It highlights Ensemble's features, including support for parallel processing, hyperparameter tuning, and model selection, making it a versatile tool for machine learning practitioners.

Twenty is an open-source site generation tool that allows users to create static websites from markdown files. It provides a flexible and customizable approach to building and managing websites, with features like templates, plugins, and built-in web server support.

The article discusses the increasing prices of memory chips, leading to higher costs for Raspberry Pi boards and other electronics. This is attributed to supply chain issues and increased demand for memory in various industries.

The article discusses the celebration of Di Day, a day dedicated to honoring the contributions of open-source software. It highlights the importance of open-source software and the positive impact it has on technology and society.

AI generated personal affirmations for all life situations that play even when your phone is locked. Help after breakup

I built an MCP server that connects Claude and ChatGPT to the Google Tag Manager API. You can create tags, triggers, variables, audit containers, and publish changes through natural conversation.

  Try it now (no install needed):
  - Claude.ai: Settings → Connectors → Add https://mcp.gtmeditor.com
  - Claude Code: claude mcp add -t http gtm https://mcp.gtmeditor.com
  - ChatGPT: Add MCP integration at platform.openai.com/apps with URL https://mcp.gtmeditor.com

  It authenticates with your Google account via OAuth 2.1, so your credentials are never stored on the
   server.

  What you can do:
  - "Create a GA4 event tag for form submissions"
  - "Audit this container for issues and duplicates"
  - "Set up ecommerce tracking for purchases"
  - "Publish the changes we just made"

  It supports all GTM entity types including server-side containers (clients, transformations). There
  are 40+ tools covering full CRUD, versioning, publishing, built-in variable management, and
  Community Template Gallery imports.

  Some things I learned building this:

  Google's API has undocumented behaviors that took a while to figure out. Transformation types
  (tf_allow_params, tf_exclude_params, tf_augment_event) aren't documented anywhere — I discovered
  them through trial and error. Each type uses different parameter table keys, and passing an unknown
  type returns HTTP 500 instead of 400. The autoEventFilter field on click/form triggers is silently
  dropped by the API (returns 200 OK but doesn't persist).

  I also built a companion repo with LLM-optimized GTM API documentation
  (https://github.com/paolobietolini/gtm-api-for-llms) — structured as an installable skill for Claude
   Code and Codex, so the AI knows the correct parameter formats, validation rules, and workflow
  patterns.

  Built with Go, deployed as a single Docker container. The MCP protocol makes it work across Claude
  and ChatGPT without any client-specific code.

 /s Thank you for your attention to this matter

X API has launched a new pay-per-use pricing model, allowing developers to use the API without commitment and only pay for the resources they consume.