venturebeat
85% of companies burned by an AI mistake are racing to cut the humans who might catch the next one

Enterprises that already got burned by an AI agent passing its evals and then failing in production are moving faster toward removing humans from deployment decisions, not slower — even as trust in automated evaluation is rising across the board, new VB Pulse research shows.In July, 13% of 108 enterprises surveyed said they trust automated evaluation, up from just 5% the month prior. Meanwhile, survey respondents citing poor alignment between tests and real-world results as their biggest concern fell 10 points, from 29% to 19%, month over month. Yet, 49% of survey respondents said that an AI agent or LLM-powered feature that had cleared company testing subsequently created a problem visible to customers, essentially unchanged from 50% in June. And nearly a quarter, 24%, said this troubli [...]

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venturebeat
Agentic reliability and evaluations : Enterprises that got burned by a bad eval are the most likely to remove humans from the loop, not the least

Across 108 enterprises, trust in automated agent evaluation rose sharply in July — and the failure rate it is supposed to predict did not move at all. The share of organizations that fully trust aut [...]

Match Score: 128.52

Destination
Kirby Air Riders is a cute, chaotic racing game

Kirby is a uniquely wholesome Nintendo character, yet his games often have a quirky mean streak to them. They're all about letting players absorb enemies and take on some wild powers to tear thro [...]

Match Score: 44.16

venturebeat
From human clicks to machine intent: Preparing the web for agentic AI

For three decades, the web has been designed with one audience in mind: People. Pages are optimized for human eyes, clicks and intuition. But as AI-driven agents begin to browse on our behalf, the hum [...]

Match Score: 40.63

venturebeat
57% of enterprises have watched AI agents be confidently wrong. The fix is an agentic context layer, but who has one?

An enterprise AI agent answers with total confidence, but the number is wrong. Nobody catches it until someone traces it back to a stale metric definition or a document the retrieval system never pull [...]

Match Score: 38.69

Destination
OpenAI's Sora burned a million dollars a day while losing half its users in record time

OpenAI is shutting down Sora after the video app burned through about a million dollars a day in compute, quickly lost half its users, and turned from a prestige project into a liability. The company [...]

Match Score: 33.72

Destination
OpenAI tripled revenue to $5.7 billion in Q1 but burned through $3.7 billion to get there

In the first quarter of 2026, OpenAI pulled in $5.7 billion in revenue and burned through about $3.7 billion, both figures tripled year over year. Stock-based compensation alone ate up over $2.3 billi [...]

Match Score: 33.72

venturebeat
Upwork study shows AI agents excel with human partners but fail independently

Artificial intelligence agents powered by the world's most advanced language models routinely fail to complete even straightforward professional tasks on their own, according to groundbreaking re [...]

Match Score: 33.30

venturebeat
Testing autonomous agents (Or: how I learned to stop worrying and embrace chaos)

Look, we've spent the last 18 months building production AI systems, and we'll tell you what keeps us up at night — and it's not whether the model can answer questions. That's ta [...]

Match Score: 30.87

venturebeat
You thought the generalist was dead — in the 'vibe work' era, they're more important than ever

Not long ago, the idea of being a “generalist” in the workplace had a mixed reputation. The stereotype was the “jack of all trades” who could dabble in many disciplines but was a “master of [...]

Match Score: 29.65