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Pedram Rezaei, a 20-year Microsoft veteran, will work on the Kiro coding tool and the Quick workplace assistant at AWS. He's the latest Microsoft executive to make the move this year. Read More
Voice AI that integrates with existing VOIP phone systems without exposing IT leaders to hidden compliance risk from unvetted third-party infrastructure.
Support leaders, find the easiest voice AI to set up for customer support teams in 2026 and avoid costly deployment failures before they start.
Seven OpenClaw alternatives sorted by job: Hermes Agent, Munder Difflin, NanoClaw, ZeroClaw, nanobot, Goose and Claude. Licences and prices checked 5 Oct 2026.
Ask your AI to answer in ASD-STE100, the aerospace manual standard, about 80% of the way. Plus Karpathy's three other tricks: diagrams, HTML and video.
Static evaluations credit a language model for naming the right move, but an agent must carry a plan through to a verified outcome while an opponent responds.
Agent harnesses make many small, typed decisions per task: which model to call, which tool to use, whether retrieved text is relevant, whether an input carries an injection.
Multi-agent debate is increasingly used to reach consensus among LLM agents, yet agents often yield to a unanimous majority. When an agent changes its answer, has it changed its mind or only its statement? We study this with two-hop factual questions whose intermediate entity (the bridge, e.g.
Recent benchmarks rely on user simulators to evaluate AI agents in multi-turn interaction. While existing simulation techniques demonstrate surface fidelity to human style and behavior, ecologically valid interactive benchmarking also requires alignment in when and how agents fail across simulated…
ReAct-based agents typically rely on a single LLM policy to propose actions, interact with the environment, and decide when a task is complete. This coupling makes action authorization and completion control difficult to enforce independently, allowing errors to propagate and unsupported completion…
You've likely seen this movie before: something breaks in an app you built with an AI coding agent. You ask the agent to fix it. It "fixes" it. But the bug is still there, or a second bug appears. So
Chatbot metrics explained: 15 KPIs with formulas, the unit each one is counted in, what skews containment, resolution and CSAT, and what to test before release.
Onwuemene Joshua is a Documentation Writer and Community Contributor at TestMu AI, with expertise in API and product documentation. He holds a Bachelor of Engineering from the University of Benin and has 3+ years of hands-on experience with Docusaurus, Markdown, Swagger, and Git, authoring…
AI agent tracing explained: what an agent trace is made of, how OpenTelemetry names its spans, how context crosses MCP, and where a trace stops being evidence.
Red teaming LLMs step by step: scope and rules of engagement, a threat model, manual and automated attacks, attack success rate scoring, reporting and retests.
Instrument Pydantic AI with Agnost and distinguish schema-valid output from correct results. Diagnose validation retries, tool failures, and missing conversation context.
Export Mastra traces to Agnost, preserve user and conversation identity, and diagnose tool failures, workflow bottlenecks, and duplicated request counts.
Instrument CrewAI with Agnost, separate crew completion from task success, and diagnose delegation loops, slow tools, missing traces, and repeated work.
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