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Max Dev

Enterprise AI agent evaluation gap leaves half of passed agents failing

A VentureBeat Pulse survey of 157 enterprises found that half have shipped an AI agent or LLM feature that cleared their internal evaluations and then failed a customer in production. Only 5% say they fully trust automated evaluation. Yet two-thirds already allow, or are actively engineering toward, allowing agents

Amazon AI agents: 85% pilot, 5% production gap is a measurement problem

Amazon's AGI autonomy lead Bryan Silverthorn argued at VB Transform 2026 on Tuesday that the 85% pilot-to-5% production gap in enterprise AI agent deployment reflects a measurement problem, not a capability shortfall. The argument is correct in direction but lighter on mechanism than it appears, and

Claude leads enterprise orchestration while multi‑step agent use stays low

Anthropic's Claude leads enterprise agent orchestration by a wide margin, but the more revealing number in a VentureBeat Pulse survey of 101 enterprises is the gap between orchestration ambition and what those deployments actually do. Seventy-one percent of respondents say a quarter or fewer of their deployed

Amazon AGI lab says AI agent pilot to production gap is measurement failure

Amazon's AGI autonomy lead used a VB Transform 2026 stage to argue that the enterprise agent deployment gap is a measurement failure, not a capability one. Bryan Silverthorn, who joined Amazon through the Adept AI acquisition, said teams are still scoring agents on benchmarks that mask the dimensions

MIT Media Lab interpretability preview raises chatbot trust but not design

The MIT Media Lab team behind "neural transparency" reports a finding that complicates the standard transparency narrative: showing users an interpretability-style preview of their personalized chatbot raised trust but did not change how they actually designed the AI. The result, from a study presented at the ACM

Celonis buys Ikigai Labs to embed structured data AI in its automation suite

Ikigai Labs, a spinoff from MIT researcher Devavrat Shah focused on AI for tabular data, has been acquired by Celonis, signaling a push to integrate specialized structured data models into enterprise process automation. The acquisition highlights a contrast with mainstream AI trends that prioritize unstructured data, positioning this technology as

1Password launches AI spend and consumption dashboard for token tracking

1Password launched AI Spend and Consumption Management on Tuesday, an extension of its SaaS Manager platform that pulls token-level consumption data from Anthropic, Cursor, and OpenAI into a single dashboard. The product sits inside an identity management company, not a procurement or FinOps vendor, and the move is a

Slopsquatting uses AI‑hallucinated names to threaten open‑source projects

Slopsquatting is the name for a new software supply chain attack built directly on LLM package hallucinations. The source frames it as a category shift from typosquatting: instead of betting on developer typos, attackers register the non-existent package names that AI coding assistants confidently invent, then upload malware under

AI agents’ token usage surge makes seat‑based SaaS pricing untenable

DeepSeek's 75% price cut on its V4-Pro model makes inference cheaper at the per-token level, but the source frames this as insufficient against a structural problem: agent workflows amplify token usage from roughly 1:5 in a single-turn chatbot to 1:700 or higher in

Slopsquatting frames LLM hallucinated packages a supply‑chain attack vector

Slopsquatting reframes LLM hallucinations as a supply chain attack surface rather than a quality problem, according to a recent ReHack analysis. The technique works because hallucinated package names are statistically predictable outputs, not random errors. That predictability is the property attackers exploit, because any name a model generates at scale