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Deep Agents can plan, use tools, manage state, and handle long multi-step tasks. But their real performance depends on context engineering. Poor instructions, messy memory, or too much raw input quickly degrade results, while clean, structured context makes agents more reliable, cheaper, and easier to scale. This is why the system is organized into five […]
Mastering Deep Agents: Context Engineering that Actually Works Read More »
Snap is cutting 16% of its workforce and crediting AI for making it possible. Here’s what the numbers say and what it means for the industry. The post Snap Layoffs: 1,000 Jobs Cut as AI Takes Over appeared first on 1redDrop.
Google just announced the release of Skills in Chrome, a new feature built into Gemini in Chrome that lets users save frequently used AI prompts as reusable, one-click workflows called Skills. The rollout begins April 14, 2026, targeting Mac, Windows, and ChromeOS users who have their Chrome language set to English-US. If you’ve been paying
AI agents struggle with tasks that require interacting with the live web — fetching a competitor’s pricing page, extracting structured data from a JavaScript-heavy dashboard, or automating a multi-step workflow on a real site. The tooling has been fragmented, requiring teams to stitch together separate providers for search, browser automation, and content retrieval. TinyFish, a
AI agents struggle with tasks that require interacting with the live web — fetching a competitor’s pricing page, extracting structured data from a JavaScript-heavy dashboard, or automating a multi-step workflow on a real site. The tooling has been fragmented, requiring teams to stitch together separate providers for search, browser automation, and content retrieval. TinyFish, a
In this tutorial, we build an advanced data analysis pipeline using Google ADK and organize it as a practical multi-agent system for real analytical work. We set up the environment, configure secure API access, create a centralized data store, and define specialized tools for loading data, exploring datasets, running statistical tests, transforming tables, generating visualizations,
Standardized tests can tell you whether a student knows calculus or can parse a passage of text. What they cannot reliably tell you is whether that student can resolve a disagreement with a teammate, generate genuinely original ideas under pressure, or critically dismantle a flawed argument. These are the so-called durable skills — collaboration, creativity,
MiniMax, the AI research company behind the MiniMax omni-modal model stack, has released MMX-CLI — Node.js-based command-line interface that exposes the MiniMax AI platform’s full suite of generative capabilities, both to human developers working in a terminal and to AI agents running in tools like Cursor, Claude Code, and OpenCode. What Problem Is MMX-CLI Solving?
MiniMax has officially open-sourced MiniMax M2.7, making the model weights publicly available on Hugging Face. Originally announced on March 18, 2026, MiniMax M2.7 is the MiniMax’s most capable open-source model to date — and its first model to actively participate in its own development cycle, a meaningful shift in how large language models are built
In this tutorial, we build and operate a fully local, schema-valid OpenClaw runtime. We configure the OpenClaw gateway with strict loopback binding, set up authenticated model access through environment variables, and define a secure execution environment using the built-in exec tool. We then create a structured custom skill that the OpenClaw agent can discover and
