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FeaturedengineeringApr 3, 202611 min read

How AI Agents Actually Work: Tool Use, Memory, and Orchestration Explained

'Agentic AI' is the buzzword of 2026 — but what's actually happening under the hood when an agent books your flight, refactors your code, or runs a 5-step research task? A plain-English breakdown with real examples.

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engineeringMar 27, 202611 min read

MCP (Model Context Protocol) Explained: The 'USB-C for AI Agents'

MCP is the plug standard that lets any AI model connect to any data source or tool — Gmail, GitHub, Notion, your filesystem — without bespoke integrations. Here's what it is, why it won, and how to actually use it in 2026.

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engineeringMar 20, 202610 min read

Multi-Model AI Workflows: Routing Prompts to the Right Model Automatically

Using one AI model for everything is like using one screwdriver for every job. Here's how to route each task to the best-fitting model — cheap for bulk, expensive for hard, fast for interactive — and cut your AI bill by 60% without losing quality.

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engineeringMar 3, 202611 min read

RAG vs Fine-Tuning vs Long Context: When to Use Each in 2026

Stop picking RAG by default. With 2M-token context windows, 90% prompt cache discounts, and cheap fine-tuning, the right choice for 'teach my AI about my data' has changed. Here's the real decision framework.

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