A comprehensive review of DeepSeek-R1-0528's AI coding capabilities, architectural innovations, and significant latency challenges via OpenRouter API. Is this open-source LLM ready for your real-time development workflow?
How our explosive early access growth shaped our pricing strategy and what's now available for developers at every scale.
A deep dive into Grok 4's benchmarks, architecture, and community impressions. Is xAI's latest LLM a breakthrough towards AGI, and is it worth integrating into your AI development workflow?
Discover how applying Rich Hickey's 'Simple Made Easy' principles can solve the 'AI 90/10 problem', leading to more maintainable and reviewable AI-generated code by constraining architectural choices.
A deep dive into Kimi K2 and Grok 4 for real-world coding, comparing their performance across bug fixing, feature implementation, tool use, and cost efficiency. See which model stands out and when to choose each for your dev workflow.
I tested Kimi K2 and Qwen-3 Coder on 13 Rust development tasks across a 38k-line codebase and 2 Frontend refactor tasks. The results reveal differences in code quality, instruction following, and development capabilities.
A detailed root cause analysis of the Forge AI coding assistant's quality degradation incident on July 12, 2025, including the impact of aggressive conversation compaction and steps taken for future prevention and stability improvements.
I pitted Claude 4 Opus against Grok 4 in a series of challenging coding tasks. The results highlight trade-offs in speed, cost, accuracy, and frustration factors that every dev should know.
Forge v0.98.0 release brings browser-based authentication, AI safety limits, and enhanced file operations for AI coding assistants. Streamline your terminal development workflow with improved reliability and developer experience.
Real talk about MCP Spec update (v2025-06-18), including important changes, security implications and what developers should actually care about.
A deep dive into critical security vulnerabilities found in Model Context Protocol (MCP) implementations, including tool description injection, authentication weaknesses, and supply chain risks, highlighting why these issues demand immediate attention in AI development.
Dive into real-world MCP security vulnerabilities and discover actionable prevention strategies for AI development, focusing on prompt injection, cost-based attacks, and secure credential handling.