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.
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?"
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.
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.
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.
