Developer tools news — AI coding assistants, IDEs, CLI tools, APIs, and productivity tools for software engineers. GitHub Copilot, Cursor, and more.
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 AI SDK's `experiment…
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. After instrumentin…
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 OpenAPI, llms.txt, an…
Technical challenges of importing Botan's `BOTAN_HAS_
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 cheaper and faster, th…
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 into tokens, use contex…
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 production because th…
Design and efficiency of array libraries in Haskell, with the author expressing skepticism about `Data.Array`'s performance and advocating for simpler wrappers around `Data.Primitive.Array`. The author also critiques the…
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 where a local LLM (qwen2…
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 management, multi-agent sup…
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 author argues that sy…
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-compatible endpoints …
Common methods for measuring the productivity of AI coding tools—such as counting lines of code, closed tickets, or developer surveys—are fundamentally flawed. It asserts that every study claiming AI has a positive effec…
Voice AI agent using ElevenLabs and n8n across seven Italian restaurants, handling 200 bookings per month for a total cost of €87. Key lessons included that Italian requires a faster response time (under 1.0 seconds) tha…
The article describes **vid.py**, a Python command-line tool that acts as a simplified wrapper around ffmpeg for common video tasks. It provides functions for parsing timecodes, estimating video duration by probing input…
While uv is praised for its speed and ability to replace multiple Python tools, its package management user experience is criticized as clunky compared to alternatives like pnpm and Poetry. Key issues include the lack of…
AI coding agents amplify ambiguity in human language, confidently generating code based on their own interpretation of vague terms without asking for clarification. It argues that this lack of friction, unlike traditiona…
According to the article, AI engineering is increasingly resembling distributed systems engineering as foundation models improve, with the primary challenges shifting from the models themselves to surrounding infrastruct…
The author reduced their LLM API costs by 90% by implementing a self-hosted, OpenAI-compatible proxy called freellmapi, which automatically routes non-critical requests across multiple free-tier providers (such as Groq, …
LLM-powered agents often get stuck in infinite loops during real-world deployment, citing three main causes: fuzzy completion criteria, context degradation, and lack of structured memory of past tool calls. It provides p…