Claude Programming Tutorials & Engineering Articles

Learn how NVIDIA NeMo Switchyard routes AI agent workloads across models using tuning-free and tunable routers that balance model capability, cost, and latency.

Agent Plugins 1.0.0 is a new, vendor-neutral directory specification—backed by Google, Amazon, Microsoft, and others—for packaging Agent Skills and MCP servers into a single portable unit. By standardizing the manifest (plugin.json) and utilizing a fixed directory layout, it eliminates the need for developers to maintain separate wrappers or configurations to support different AI coding agents and IDEs. Google has officially joined as a Core Maintainer and already rolled out support in the Agents CLI and Data Agent Kit, allowing developers to start building and distributing interoperable plugins today.

Google Cloud API Gateway now offers a model routing feature in Public Preview, allowing developers to dynamically route traffic to models like Gemini, Claude, or OpenAI OSS-GPT without hardcoding endpoints or managing open-source proxies. Developers can easily configure these routing rules directly within their OpenAPI 3.x specifications by mapping virtual model names to specific backend targets on a shared host. Once deployed, the Gateway acts as a serverless ingress layer that accepts standard OpenAI-compatible requests, automatically transcodes the payload to the native schema of the target model, and routes the traffic on the fly.

Agent Platform's evaluation service is now generally available, providing developers with a unified engine to measure agent quality consistently across local development experiments and live production traffic. You can evaluate agents using over 20 pre-built metrics, DeepMind-backed adaptive rubrics, or custom code-based and LLM-as-a-judge metrics stored in a centralized, versioned registry. The service integrates directly into existing workflows via the Agent Platform SDK, agents-cli, and ADK, offering built-in user and environment simulators to automate complex multi-turn testing and streamline CI pipelines.

Stripe's Knowledge AI Platform is our versatile AI agent platform built to handle diverse non-coding knowledge work, from quick queries to complex, multi-day projects. By connecting employees to over 1,000 internal tools and skills, it enables secure, enterprise-scale productivity across the organization.

One user turn can contain many model and tool iterations. Any cost inside the repeated region can be paid many times.

Oxide joins Anthropic's Project Glasswing, applying Claude Mythos 5 to find and patch vulnerabilities across its open-source stack, firmware to network.

We have relaunched clickhouse.com/docs on Mintlify, with a redesigned search and Ask AI experience, a docs MCP server, simpler navigation, an interactive API playground, and expanded localization — built for both human readers and the coding agents

NVIDIA Ising Calibration is an open source vision language model (VLM) designed to interpret diagnostic outputs from quantum processors and determine how they…

A behind-the-scenes look at hdx-evals, the open-source framework we built to benchmark the ClickStack MCP server against a raw SQL baseline using deterministic synthetic incidents, sandboxed Claude agents, and blind LLM grading — and why the MCP scored hi

How our LLM gateway uses Thompson sampling over lognormal latency posteriors to pick the fastest, most reliable model route per request

Search and uncover technology trends across 10 billion GitHub events in real time.

This post shows a lightweight metrics layer for ClickHouse using MooseStack, an open source developer agent harness for ClickHouse.

How to remain competitive in the AI era of software engineering

Retention limits, sampling, and metric roll-ups aren't observability best practices - they're workarounds for storage systems that can't handle full-fidelity data, and they're becoming a hard blocker for AI-driven workflows.

A Solutions Architect’s experience building a retail analytics platform with AI agents, real-time dashboards, and full observability on the ClickHouse data platform

otel.fyi is a search-first site for OpenTelemetry Collector docs, making it easy to quickly find and understand configuration for receivers, processors, exporters, and extensions without digging through scattered documentation.

We use clickhousectl to spin up multiple ClickHouse versions side by side and benchmark two recent performance improvements.

ClickHouse 26.5 is here! In this release, we have a record number of performance optimizations, a new `filesystem` table function for querying your local file system with SQL, and more!

What started as an internal sizing tool for ClickStack became ClickCannon: an open-source framework for stress-testing ClickHouse with realistic data and user workloads.

We've had decades to learn what it means to design software and hardware for humans. How do we build experiences where the primary user may now be an LLM?

We've released @clickhouse/rowbinary a Node.js reader and writer for ClickHouse's RowBinary formats. You can import it and call its generic parser like any other library. But it also ships as an Agent Skill: point a coding agent at the bundled `SKILL.md`

Welcome to the July 2026 ClickHouse newsletter, which will round up what’s happened in real-time data warehouses over the last month.

Conductor has evolved from a Gemini CLI extension into a portable plugin, bringing conversational Spec-Driven Development (SDD) to ecosystems like Antigravity CLI and Claude. Rather than relying on strict command sequences, developers can now chat naturally with their AI assistant while it dynamically manages persistent markdown artifacts (like spec.md and plan.md) in the background. This update eliminates workflow friction while ensuring your repository remains a version-controlled, single source of truth for your project's architecture and state across different AI tools.

Developers building video analytics applications across large spaces must track the same object as it moves between camera views. Single-camera 2D tracking…

What if autonomous coding AI agents could push your vision reasoning models above 90% accuracy with almost no manual effort? When adapting vision reasoning…

AI scientists are emerging as a new interface for scientific computing. These agents can read papers, write code, generate hypotheses, call APIs, inspect files…

When building with agents, most guides will give you the happy path - how to do something the best way, without friction. This post is all friction, and how to get through it when things go wrong.

Training a speech AI model to correctly recognize or synthesize clinical terminology is surprisingly difficult. Drug names like Acetaminophen, Amlodipine…

Google has announced the Google Colab Command-Line Interface (CLI), a new tool that allows developers and AI agents to connect local terminals to remote Colab runtimes for frictionless execution. The lightweight CLI enables users to easily request high-powered GPUs, run local Python scripts remotely, and seamlessly retrieve artifact logs or models like fine-tuned Gemma 3 adapters. By integrating directly into standard terminal environments, the tool is highly programmable and ready to be used by AI agents such as Antigravity or Claude Code to manage complex machine learning pipelines.

AI agents are a powerful tool for synthesizing data to accelerate research, summarize information, and help teams make decisions faster.

How our Rust collections library defends against adversarial trait implementations.

Agent harnesses like Claude Code, Codex, and LangChain Deep Agents are excellent orchestrators. They manage sessions, chain tools, execute code…

Autonomous AI agents are becoming more capable. Open models, Model Context Protocol (MCP)-connected tools, and portable skills are also making agents easier to…