#developer-tools

#developer-tools

Agentic browser tools, an experimental feature, provides agents with a set of tools to read and interact with VS Code's integrated browser. When an agent interacts with a web page, it sees updates to page content and any warnings and errors in the console. The tools work out of the box with no need to install extra dependencies.

If there's one universal experience with AI-powered code development tools, it's how they feel like magic until they don't. One moment, you're watching an AI agent slurp up your codebase and deliver a remarkably sharp analysis of its architecture and design choices. And the next, it's spamming the console with "CoreCoreCoreCore" until the scroll-back buffer fills up and you've run out of tokens.

With C# 14, now you can run a C# file directly from the command line without needing a project or solution file. Until C# 14, we've had to follow a multi-step process to run a minimal .cs file. Not only was this a multi-step process, but it incurred significant additional overhead because you had to create a solution file and a project file to run your application.

My website was not what potential customers would be looking for. Although what the site did was useful, no one in the age of agentic coding was going to use it. Instead, they would want some way to have their coding agent, or their build process, or some other automated thing, use my system.

Most of us do not start from a greenfield idea. We start from an existing codebase, a messy bug, or a design we already agreed on,

From day one, our mission was simple: make it easy and reliable to build in prediction markets. There's no better place to push that mission forward than Polymarket.

For the longest time, Linux was considered to be geared specifically for developers and computer scientists. Modern distributions are far more general purpose now -- but that doesn't mean there aren't certain distros that are also ideal platforms for developers. What makes a distribution right for developers? Although I consider app compatibility, stability, and flexibility to be essential attributes for most any Linux distribution, developers also need the right tools

Today, OpenAI announced GPT-5.3-Codex, a new version of its frontier coding model that will be available via the command line, IDE extension, web interface, and the new macOS desktop app. (No API access yet, but it's coming.) GPT-5.3-Codex outperforms GPT-5.2-Codex and GPT-5.2 in SWE-Bench Pro, Terminal-Bench 2.0, and other benchmarks, according to the company's testing. There are already a few headlines out there saying "Codex built itself," but let's reality-check that, as that's an overstatement.

Portal users can move data between platforms, which Lone Wolf says can reduce duplicate data entry and manual reporting processes. Designers say the system is intended to give real estate professionals a consolidated view of transaction activity, reporting and business analytics. Lone Wolf a 2026 HousingWire Tech100 honoree says the platform also allows brokerages and agents to integrate third-party software and internally developed tools while maintaining control over data access and security settings.

OpenAI has introduced ChatGPT Health, a dedicated section inside ChatGPT focused entirely on personal health. It's more than a themed chat - users can discuss symptoms, interpret lab results, track metrics over time, and get clear explanations of medical terms. A key feature is integration with health and fitness services. Users can connect Apple Health, MyFitnessPal, and similar apps so the AI can analyze sleep, activity, nutrition, and wellness trends.

There's something oddly nostalgic about Caligra's c100 Developer Terminal, yet it feels completely modern at the same time. At first glance, it looks like someone took a pristine keyboard from the early computing era, polished it up, and reimagined it for 2026. But this isn't just a keyboard. It's an entire computer, cleverly disguised as the thing you type on.

Microsoft is pitching a future where AI controls everything on your PC and agents go and do work for you in the background. But before the company gets there, it has to build the tools to make these systems work and convince its own developers that AI is actually capable of achieving these big promises.

Speaking at an all-hands meeting last Thursday, the day after the chipmaker reported another quarter of record results, Huang reacted sharply to reports that some managers inside the company were urging teams to dial back their AI use. Business Insider listened to the meeting. "My understanding is Nvidia has some managers who are telling their people to use less AI," Huang said. "Are you insane?"

Family and friends often ask why I work so hard. Moments like this are why,

At the core of the new release is Builder agent, a generative AI system that converts plain text prompts into functional, customized map prototypes within minutes. Developers can type natural instructions like "create a Street View tour of a city" or "build a map that visualizes real-time weather in my region," and Builder agent automatically produces an interactive layout using Gemini's reasoning and visualization capabilities.

The company said the launch of Red Hat Developer Lightspeed, a portfolio of AI solutions, will equip developer teams with "intelligent, context-aware assistance" through virtual assistants. Available on the Red Hat Developer Hub, the first of these AI tools is accessible through the hub's chat interface. The company said this will help speed up non-coding-related tasks, including development of test plans, troubleshooting applications, and creating documentation. This AI assistant can be used via both publicly available and self-hosted large language models (LLMs).

The event marked a turning point for one of Microsoft's most important but often under-analyzed assets. GitHub, which is used by more than 180 million developers, wants to be the central platform for AI coding agents. Its new Agent HQ interface lets outside coding assistants, including OpenAI's Codex and Anthropic's Claude Code, plug into the GitHub ecosystem. The timing is apt.

Google has released the Genkit Extension for Gemini CLI, a specialized plugin that brings deep, framework-aware AI assistance directly to the terminal, aiming to streamline the development and debugging of Genkit-based applications.The extension's primary function is to streamline Genkit-based application development by surfacing essential information like flows, traces, and documentation without requiring the developer to leave the command line. Genkit is Google's open-source framework for building and orchestrating generative AI applications.

I trained a Google Gemini model on my most effective emails, giving it a large sample of my writing and Devpost context. When drafting important messages, I collaborate with the model to ensure I'm expressing myself as I intend. It's still my tone and ideas, but the model helps me deliver consistently strong communication. I also built a Google Gemini CLI "Executive Assistant" to replace my visual Kanban board with a markdown-based, conversational task manager.

APIs, or application programming interfaces, started out as a mechanism to let computers talk to other computers, but somewhere along the way, they've evolved into an ecosystem all their own. For virtually any development need, there is likely an API ready and waiting to deliver. Like the Lincoln Logs or Lego bricks of old, APIs are building blocks for creating applications.

In addition to being generally available, Gemini 2.5 Flash Image now comes with 10 aspect ratios across four styles (landscape, square, portrait, and "flexible"), enabling "effortless content creation across various formats, from cinematic landscapes to vertical social media posts," Google wrote in its announcement. The company also published developer docs and a " cookbook" to help users get started with Gemini 2.5 Flash Image, which costs $0.039 per image.

Tim Chen, solo VC at his firm Essence VC, just closed his fourth fund, a fresh $41 million, without even trying. Limited partner investors (LPs) were so eager to invest, they pre-empted it, he told TechCrunch. He hadn't even time to generate a pitch deck. True, $41 million might not sound like much in this age of multi-billion venture firms and solo VCs like Jack Altman (who just raised his second giant fund, at $275 million).

Baseten just pulled in a massive $150 million Series D, vaulting the AI infrastructure startup to a $2.15 billion valuation and cementing its place as one of the most important players in the race to scale inference - the behind-the-scenes compute that makes AI apps actually run. If the last generation of great tech companies was built on the cloud, the next wave is being built on inference. Every time you ask a chatbot a question, generate an image, or tap into an AI-powered workflow, inference is happening under the hood.