Agent-to-Agent (A2A) vs. Model Context Protocol (MCP): When to Use Which?
In the rapidly evolving landscape of AI, protocols like Google's Agent-to-Agent (A2A) and Anthropic's Model Context Protocol (MCP) are emerging as key enablers for building sophisticated AI systems. Understanding the differences between these protocols is crucial for making informed decisions about which one best suits your project's needs. This post will break down the core distinctions between A2A and MCP to help you choose the right tool for the job.
Claude Code vs GitHub Copilot: The Semantic Search Divide
When choosing between AI coding assistants, understanding their underlying search capabilities can significantly impact your development experience. While both Claude Code and GitHub Copilot excel at code generation and assistance, they differ fundamentally in how they find and understand relevant code context—and this difference can lead to dramatically different results.
How to Cut Your AI Token Bill Without Breaking What Works
Most AI spend isn't tied to a business outcome. Learn how to cut AI token costs 40 to 60% with model routing, evals, and cost-per-outcome visibility.
How We Built a Clinical AI Agent
Agent workflows have quickly emerged as one of the most compelling frontiers in AI application development—but building them for real-world production use cases is still a nuanced and evolving challenge. At Stride, we recently partnered with a healthcare client to redesign a complex patient-facing workflow using LangGraph, LangChain’s graph-based orchestration framework.
LLMs are the ultimate interns
LLM-powered bots are essentially gifted interns, with a wealth of capability and knowledge that they don’t fully understand how to use. It’s on us to figure out how to guide and leverage them to help us do our jobs better.
Press release: Stride Launches AI Token Cost Optimization as Worldwide AI Spending Climbs Toward $2.6 Trillion With Little Measurable Return
Stride announces AI Token Cost Optimization at Ai4 2026: cost-per-outcome visibility in two weeks and 40 to 60 percent AI cost reduction on routed surfaces.
Understanding Claude Code's Approach: Text-Based Tools vs. Editor Integration
Claude Code represents a fascinating approach to AI-assisted development, leveraging powerful language models through command-line tools and file manipulation. However, this architecture creates an interesting trade-off compared to editor-native AI assistants, particularly when it comes to tasks that modern IDEs handle through built-in tooling.
Why Isn't Our AI Coding Tool Making Us Faster? Start by Structuring Your Repos
Your AI coding tool isn't the variable, your repos are. Why structuring repositories for AI readiness is the first move that makes every gain measurable.
Why Shorter AI Coding Sessions Produce Better Code
Model output degrades as context grows. Why bounding delivery scope and coding sessions with a plan-first discipline improves quality and cuts token cost.