Insights - Amplifi Labs

Windsurf for Data Engineers: Pipelines, ETL, Notebooks and Automation Scripts

Data engineering is one of the technical areas that benefits the most from agentic AI. Traditional code assistants can speed up small tasks, but they usually fall short when the workflow spans full pipelines, multi step transformations, schema evolution, infrastructure interactions, and operational debugging. Windsurf takes a different approach by understanding repositories end to end and executing complex tasks in the same way a real engineer would. This article explores how data engineers can use Windsurf to build and maintain pipelines, ETL processes, notebooks, and automation scripts with more speed, consistency, and reliability.

Tabnine Guide: Everything You Need To Know About the Privacy First AI Code Assistant

AI coding assistants have become a core part of modern software development, and Tabnine has emerged as one of the most reliable tools for teams that want speed, consistency, and strong data protection. As the demand for secure AI development workflows increases, many companies look for an assistant that improves productivity without sending private code to external servers. This is the area where Tabnine stands out.

Self-Verifying AI, Accessible Auth, and Platform Shifts

Beyond the Build • December 01, 2025

Google Antigravity Review: Everything You Need to Know About Google’s AI First IDE

Google Antigravity is an AI assisted integrated development environment designed around autonomous agents instead of simple autocomplete suggestions. Announced together with the Gemini 3 model family, it introduces a development workflow where agents can plan, execute, and evaluate tasks across the editor, terminal, and an integrated browser. This positions Antigravity as one of the first truly agent first IDEs built to support end to end coding missions.

Nano Banana Pro: What Google’s New Image Generation Model Means for the Future of Visual Creation

Nano Banana Pro is Google’s latest high performance model for image generation and visual editing. It offers high resolution output, detailed creative controls, accurate text rendering inside images, and strong reasoning capabilities for diagrams, layouts, and structured visuals. The model is designed for creators, technical teams, designers, educators, and anyone who needs consistent and high quality graphics at scale.

Claude Opus 4.5: Technical Overview of Anthropic’s Most Advanced Model

Claude Opus 4.5 is Anthropic’s newest flagship model and represents a major step forward in coding performance, reasoning depth, computer use, and multi step automation. Designed for high complexity tasks, the model introduces improvements in accuracy, efficiency, and tool interaction that make it suitable for advanced engineering and enterprise workflows.

Microsoft Fara-7B: The Lightweight Computer Use Agent Transforming AI Automation

The AI landscape has been dominated by massive language models, but a new frontier is emerging. Compact, efficient, on device agents are becoming central to automation, and Fara-7B is one of the most compelling examples. Developed by Microsoft Research, Fara-7B is an open weight computer use agent model with only 7 billion parameters, yet capable of automating real web based tasks, interacting with UI like a human using mouse and keyboard, and delivering performance that rivals much larger systems. Below we explain what Fara-7B is, how it works, its main strengths and limitations, and why it is relevant for companies, developers, and teams exploring efficient AI automation.

ChatGPT 5.1 vs Gemini 3: Which AI Model Is Better for Developers and Engineering Teams?

Choosing the right large language model is one of the most important decisions for teams building AI powered applications. ChatGPT 5.1 and Gemini 3 represent the newest generation of reasoning focused, multimodal, and code capable models. Even though both models target similar use cases, their design priorities, performance profiles, and integration paths are very different. This comparison explains how each model works, what developers should expect in production, and which longtail use cases each model supports best.

Gemini 3: What Developers Need To Know About Google’s Next Generation Multimodal AI

Google’s Gemini 3 family represents the newest step in large scale multimodal AI. It brings stronger reasoning, more efficient context handling, and deeper integration across code, text, images, audio, and structured data. For developers and technical teams, Gemini 3 is positioned as a versatile model family for building intelligent applications that require fast inference, long context windows, and advanced multimodal understanding. Below is a complete overview of what Gemini 3 is, how it works, and why it matters for engineering teams building modern AI driven products.

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