The industry is shifting from copilots that simply autocomplete code to agentic systems that autonomously plan and execute multi-step workflows in a recursive loop.
AI agents fail in production because they rely on prompts instead of systems. Without proper hosting, memory, tool access, and controls, they become unreliable.
Treating cost as a first-class signal lets teams spot financial regressions early and make informed infrastructure trade-offs before cloud spend becomes a surprise.
Model Context Protocol enables intent-driven GitHub workflows in the IDE, replacing command sequences with safe, structured natural language interactions.
Technical architecture, capabilities, and use cases of hurley, a project developed in Rust that functions as a general-purpose HTTP client and a performance testing tool.
End-to-end testing fails in microservices due to non-determinism, complex environments, slow feedback, and unclear ownership, making tests flaky and unreliable.
Attackers continue to exploit injection flaws — all ranked among the most dangerous weaknesses in MITRE’s 2025 CWE Top 25 list with 41 actively exploited vulnerabilities.
Learn how to size GPU capacity, batching, and concurrency for strict latency SLOs in production-ready LLM inference with this analysis of queuing theory applications.