Companies are still struggling to figure out if they are getting a return on their AI investments. These metrics can help.

Speculative decoding can help AI chatbots improve throughput and reduce hardware demand by using a smaller model to draft tokens that a larger model validates.

MotherDuck is launching Flights, an agent-native data pipeline that enables users to choose the MCP server and AI agent of their choice to build and deploy data pipelines in minutes using a flexible, ...

OpenAI API costs can spiral when agents run wild. Here's how to set spend limits, enable hard caps, and avoid surprise AI ...

Modern business intelligence demands speed, and utilizing AI tools for Excel is the ultimate way to hyper-charge your data workflows this year.

The offices of Google are pictured in London on February 28, 2026. JUSTIN TALLIS/AFP via Getty Images Google released agents-cli on April 21, 2026, and it has shipped 13 updates in the 71 days since — ...

OpenAI paper shows nearly all employees shifted from chatbots to agents, with non-dev usage growing 137x. But every metric comes from OpenAI itself.

Jeremy Freeman, Co-Founder and CTO of Allstacks, is a software engineer, technology architect, and entrepreneur with a career ...

Look to these key metrics and benchmarks to evaluate the performance, capability, reliability, and safety of your AI models and agents. We’ve all heard the mantra from the quants in the business ...

VentureBeat surveyed 132 enterprise AI leaders: the production failure point isn't the model — it's the runtime layer most teams are patching with retries instead of fixing.

Abstract: AI coding agents have shown great progress on Python software engineering benchmarks like SWE-Bench, and for other languages like Java and C in benchmarks like Multi-SWE-Bench. However, C# – ...

DeepSWE, created by DataCurve offers a benchmark for assessing AI coding models by focusing on real-world programming challenges rather than synthetic test cases. According to Matthew Berman, one of ...