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).
MCP provides a structured interface for tools and AI agents to query observability data, enabling developers to surface traces, metrics, and logs in their IDE without switching context. This high-level capability is designed to streamline debugging and reduce time spent navigating between systems, while also laying the groundwork for consistent access across AI assistants and integrations. Originally launched as an open source project, MCP is now offered by Honeycomb as a managed service.
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.
Cursor impressed me with its real-time visualization and intelligent code suggestions. Recent comparisons show that Cursor is adopted by 7 million developers and Fortune 1000 companies, and I could see why: when it worked. The problem? Debugging in Xcode felt like trying to perform surgery with oven mitts. For someone lacking coding fundamentals, Cursor's power becomes a liability because I'm unsure which part it's executing correctly and how to maintain that code.
Its technical performance is particularly notable for its speed. Thanks to prompt caching, grok-code-fast-1 achieves cache hit rates above 90 percent and can handle multiple tool calls before the first output lines are visible. The model supports a wide range of programming languages, including TypeScript, Python, Java, Rust, C++, and Go. It can perform a variety of tasks, from setting up new projects to answering programming questions and targeted bug fixing.
Vibe coding is everywhere, and it's already drastically changing the tech industry, shaping everything from how software gets made to who gets hired. Back in July, WIRED's very own Lauren Goode went on a journey to become a vibe coder at one of San Francisco's top startups. In this episode, she sits down with our director of consumer tech and culture, Mike Calore, to share her experience and break down whether vibe coding really spells the end of coding as we know it.
95% of developers now rely on AI‑assisted tooling to accelerate their workflows and catch critical bugs before they ship, indicating a significant shift towards AI solutions in software development.
Gemini CLI is an open-source AI assistant from Google, designed for terminal use, enabling developers to interact with the Gemini 2.5 Pro language model seamlessly in their command line workflows.
GitGuardian's Model Context Protocol (MCP) Server enables AI-assisted secrets security directly in developer environments, compressing security feedback loops into minutes.
I remember needing an organization feature. It's a very common use case for most SaaS applications, but it wasn't available from these providers. So I had to build it from scratch.
Google's Gemini AI model family has expanded with the general availability of the 2.5 Pro model and the introduction of the Flash-Lite version, enabling more cost-effective AI solutions.
MCP support in Amazon Q Developer IDE plugins enables integration of external tools, enhancing code accuracy and streamlining complex workflows for developers.