Systems | Development | Analytics | API | Testing

How to Prevent AI Hallucinations: 3 Hidden Threats When AI Analyzes Your Data

A VP of Marketing presents an AI-generated performance review on a Monday morning. The CAC numbers are clean. The trend lines are directional. The exec summary recommends a $200K budget reallocation from paid search to organic content. The CFO nods. The budget shift is approved before lunch. Two weeks later, an analyst spot-checks one figure against the source system. The number doesn’t exist anywhere in the connected data.

What is an MCP Registry? The Centralized Directory for AI Agents

A guide to learning how MCP registries help govern AI agent-to-tool connectivity AI agents are only as capable as the tools they can reach. When an agent needs to query a database, file a support ticket, or pull data from a CRM, it has to find the right tool, authenticate, and invoke it — all at runtime. The Model Context Protocol (MCP) standardizes how agents communicate with these tools. But MCP alone does not answer a fundamental question: how does the agent know which tools exist?

How to Optimize iOS Push Notifications in Production

Push notifications are one of the most powerful retention tools in mobile. iOS opt-in rates average 40–45%, and apps that use push effectively can triple their long-term retention. However poorly timed, poorly crafted alerts can drain our open rates, leading to opt-outs and disengagement. When designing iOS push notifications, we need to think about engagement and retention, not just impressions.

How to Fix a React Native Production Bug Without Waiting for App Store Review

There is a specific kind of dread that comes with finding a critical bug in a production React Native app. The fix is usually straightforward: a broken API call, a logic error, a UI state that did not account for an edge case. You can see exactly what went wrong and exactly how to correct it. The code change might take an hour. What takes days is everything that comes after. App Store review. Google Play review. Waiting. Watching your crash reports climb.
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Run Local LLMs on Mac to Cut Claude Costs

Part of the motivation for this post is how cloud API economics are shifting: Anthropic is moving large enterprise customers toward per-token, usage-based billing (unbundled from flat seat fees), which makes "always call the API" a moving cost line for teams at scale. A hybrid or local layer is one way to keep spend bounded while you still use premium models where they matter.