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Poolside, the San Francisco AI lab that has spent most of its three-year existence quietly selling coding models to governments and defense agencies, released its most capable model to date on Tuesday — and made an unusually aggressive bet that radical transparency, not raw scale, is how a smaller lab competes at the frontier. The …

Poolside drops Laguna S 2.1, an open-weight coding model that beats rivals 10x its size Read More »

GPU memory is the most expensive resource in production AI, and it’s also the one running out fastest. Long context windows and multi-turn conversations force AI models to repeatedly recompute information they’ve already processed, consuming GPU memory and compute that could otherwise serve additional users or generate new responses. Instead of treating GPU memory as …

Stop adding more GPUs: Weka’s new storage platform reduces load by caching 100% of AI model’s pre-calculated tokens Read More »

Google DeepMind today released three new proprietary AI models it says are among its most token-efficient yet: Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber. The models aim to make AI agents faster, smarter, and cheaper at scale. Google is pricing Gemini 3.6 Flash at $1.50 per one million input tokens and …

Google’s Gemini 3.6 Flash model cuts AI agent token costs by up to 65% on long horizon engineering tasks —and 3.5 Pro is on the way Read More »

“The new PRD are the evals,” Xavi Amatriain, Expedia Group’s first chief AI and data officer, told the VB Transform 2026 audience last week in Menlo Park. “So basically, you encode what you want the product to do through your evals, which might include red teaming evals and all kinds of other things, which already …

Evals are the new PRD, Expedia’s AI chief tells VB Transform 2026 Read More »

Presented by Atlassian Most companies are approaching AI adoption backwards by optimizing how individuals use AI instead of how teams work together, said Dr. Molly Sands, head of the Teamwork Lab at Atlassian, during a fireside chat with VentureBeat senior technology contributor Sam Witteveen at VB Transform 2026. Sands leads a team of behavioral scientists …

Atlassian: Why AI speeds up employees but not organizations Read More »

Enterprise AI is facing an ROI paradox. While throwing more compute at the strongest foundation model works well in product experiments, the costs become unbearable when the product is deployed in production. A new paper from researchers at Writer provides a solution that is accessible to engineering teams. The study takes a systematic look at …

Writer’s AI harness cuts token spend nearly 40% — without sacrificing accuracy Read More »

A single AI agent conversation can look flawless scored on its own and still point to a broken product. That gap is driving a shift in how enterprises evaluate agents, away from scoring individual traces and toward comparing cohorts of users against a baseline. At VB Transform 2026, Harrison Chase, CEO of LangChain; Hui Zhang, …

A single AI agent conversation can look perfect and still be broken, leaders from LangChain, Conviva and CoreWeave said at VB Transform 2026 Read More »

Zillow, the real estate technology company, doesn’t get one conversation with its customers. They move from a phone screen to a loan officer to a real estate agent, sometimes over months or years, and expect the context to follow them. A single chatbot could never carry that thread. At VB Transform 2026, Zillow SVP of …

At VB Transform 2026, Zillow’s engineering chief said AI ROI numbers only hold up if you measure before you build Read More »

Hugging Face’s incident response team first turned to frontier AI models to analyze a breach of the company’s production infrastructure, and the models refused to help. Commercial safety guardrails built to stop attackers blocked every forensic query because they treated the IR team’s real exploit data the same way they would treat a live attack. …

Safety guardrails blocked Hugging Face’s defenders, not the attacker, when an AI agent breached its systems Read More »

Presented by JumpCloud The organizations losing confidence in AI are the ones most likely to get it right. Six months ago, 40% of IT leaders described their organizations as mature in AI deployment. Today that number is 23%. Before you read that as a setback, consider what it actually reflects. We recently surveyed 800 IT …

AI confidence just dropped 17 points in six months. That’s actually great news. Read More »