DeepSeek-R1-0528 claims to rival GPT and Claude in reasoning — and it delivers, but with a catch. This hands-on review dives into eight hours of real-world testing, exposing the brilliance and the bottlenecks of this open-source AI model. From latency issues to architectural wins, get the no-BS verdict on when DeepSeek shines and when it stalls your workflow. If you're considering integrating it into your dev setup, read this first.
MCP servers are leaking conversations, injecting prompts, and hijacking your cloud bills—this isn’t theoretical. Backed by fresh Trail of Bits research and OWASP guidelines, this article outlines real-world MCP threats and five practical, code-level defenses you can ship today. If you're building with AI agents, you can’t afford to skip this.
A deep dive into the security blind spots of Anthropic's Model Context Protocol (MCP). This article uncovers how tool description injection, weak authentication, and supply chain risks are quietly undermining AI tool integrations. Tested against real implementations, these findings reveal critical vulnerabilities lurking behind the scenes—issues that won’t show up in logs but could be exploited at scale. If you're deploying or building MCP tools, read this before it’s too late.
After 180 days of pairing with AI coding agents in real-world development, this article shares 12 no-fluff lessons—what works, what breaks, and how actually to make AI helpful in your daily workflow. From tool fatigue to code trust issues, get the insights you won’t find in marketing decks.
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A head-to-head experiment comparing indexed vs no-index AI coding agents using Apollo 11's flight code. Discover which approach is faster, more reliable, and safer when coding at lunar scale.
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