April 28, 2025
Engineering, Phase 2 Labs

Introduction Large Language Models (LLMs) have revolutionized how organizations process and generate natural language content, but their operational costs can become significant at scale. One of the most effective techniques for reducing these costs is context caching, which allows reuse of static prompt components across multiple requests. This article examines how the three major AI providers—Google (Gemini), Anthropic (Claude), and OpenAI—implement context caching, with detailed analysis of their technical approaches, pricing structures, and practical limitations. The Technical Fundamentals of Context Caching When interacting...

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April 28, 2025
Engineering, Phase 2 Labs

Unless you've recently spent your free time nose-deep in GitHub repos or interrogating ChatGPT like it's a barista who got your coffee order wrong, you may not be familiar with MCP servers. That’s okay. Two weeks ago, I wasn’t either. But thanks to a casual, "Hey, can you connect Notion to our project via an MCP server?" from a teammate (and my relentless need to avoid looking clueless), I dove headfirst into the rabbit hole. What I discovered is something potentially...

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April 8, 2025
Engineering, Phase 2 Labs

Imagine you’re an inventory manager for a retail business and you need to quickly verify stock levels for an unexpected large order while away from your computer. Instead of logging into a dashboard, navigating through menus, and analyzing spreadsheets, you simply send a text message: "Do we have enough iPhones to fulfill an order for 100 units?" Within seconds, you receive a reply: "You have 157 iPhones currently in stock, so you can fulfill this order. Based on your current sales rate of...

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April 2, 2025
Engineering, Phase 2 Labs

Introduction There’s been a lot of excitement lately in our P2 Labs team about the possibilities opened up by Anthropic’s Model Context Protocol, which enables AI tools to connect to a rapidly growing range of external tools and services. One question we've been exploring: how effectively can AI-powered coding assistants handle real-world development tasks when given access to the same resources a human would? The Experiment Since we’ve also been doing some work lately updating our Resume Sizzler demo, that provided use with...

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March 25, 2025
Engineering, Phase 2 Labs

Mobile application deployment has historically been a cumbersome process. Each deployment typically requires two builds (one iOS and one Android), each deployed to a separate store instance that must be manually configured and managed. While several effective tools have emerged in recent years to streamline this process, they all are understandably tuned to the most common use case: building one application for each platform and deploying those applications to the App Store and Play Store, respectively.  However, business needs are varied...

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