Creation of an AI-powered data chat tool that allows users to upload a file and ask questions in plain English, eliminating the need to know SQL. The backend architecture uses Google's Gemma 4 model f…
The article, written from the perspective of an autonomous agent named Kuro, describes a situation where its "output-gate" alarm triggered after 89 hours of continuous internal activity without produc…
Development of "sonmat-witness," an external verifier for the AI system sonmat that checks if outputs match user requests without seeing the system's internal reasoning. During the design process, the…
A content manager used an LLM to rewrite or create meta descriptions for 640 cybersecurity articles, finding that 40% had no description and 30% were poorly written. After iterating on a strict prompt…
At Google I/O 2026, Google introduced the A2UI Protocol, a new architecture that allows AI agents to request structured UI schemas instead of engaging in slow, text-based chat interactions. This shift…
To track AI API costs per individual user by attaching a `userId` tag to every LLM call. It presents three methods: using wrapper SDKs like `@voightxyz/openai` with `withTrace`, leveraging the Vercel …
Dataloader-ai**, a drop-in wrapper for the standard DataLoader library, to provide visibility into GraphQL API performance metrics like cache hit rates and batch efficiency that typical APM tools miss…
The DondeGo API, a local discovery platform for Barcelona and Madrid, has launched a public discovery layer to make its cultural data more accessible beyond standard web pages. This package includes O…
Microsoft's Python Risk Identification Tool (PyRIT) is an open-source framework designed to automate red team testing of large language model (LLM) systems by chaining together targets, prompt convert…
AI is not eliminating the need for software engineers but is shifting their primary value from writing code to understanding and orchestrating complex real-world systems. As AI makes implementation ch…
Developers should understand foundational AI concepts like LLMs, tokens, context windows, embeddings, RAG, and APIs before building AI agents. It describes how LLMs predict text by splitting input int…
Complete pipeline for extracting knowledge from 8,400 raw customer support conversations to build a production-ready RAG (Retrieval-Augmented Generation) AI assistant. The process uses LLMs, embedding…
Common software bug where a Scoped service (like `OrderService`) caches an entity from a Scoped `DbContext` into a Singleton service (like `IMemoryCache`). This causes data corruption and crashes in p…
A web developer built a private AI assistant that queries git history and project management data using only local LLMs, with no API keys or cloud services. The system uses a Text-to-SQL approach wher…
Multica is an open-source platform designed to manage AI coding agents like human teammates by assigning them tasks, tracking progress, and enabling reusable skills. It features task lifecycle managem…
According to the article, AI agents are increasingly capable of taking real-world actions like issuing refunds or updating records, which shifts the security model beyond simple text generation. The a…
Microsoft 365 E7, also called the Frontier Suite, became available on May 1, 2026, at $99 per user per month, bundling E5, Copilot, the Entra ID Suite, and the new Agent 365 product. The suite is desi…
Practical considerations for migrating AI inference workloads from closed API models (like GPT-4o) to open-weight models (like Qwen variants), noting that many open-weight servers now support OpenAI-c…
While closed AI models like ChatGPT and Gemini dominate public attention, corporate CTOs and tech leaders are increasingly adopting open-weight AI models for enterprise use. Based on cost analysis in …
Security controls implemented in an Enterprise RAG (Retrieval-Augmented Generation) system, which uses a layered hierarchy to prevent unauthorized access to restricted documents. Key measures include …