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1 point 0 comments on Hacker News · aichatspot.online
Australia return to full strength for two-Test series against Bangladesh, as injured trio return to strengthen squad.
A newly discovered turning point in the Sun’s 11-year cycle could allow scientists to predict future solar activity years earlier than before. At this “switch-off” point, the most violent space weather abruptly ends, and the remaining number of sunspots offers clues about the next cycle’s strength. Early projections suggest Solar Cycle 26 may be moderate, but a clearer forecast is expected in about two years.
Moment terrifying floodwaters sweep through Afghan village
An Israeli air attack on an apartment in Gaza City set the building on fire, killing five people.
Live from Snowflake Summit, Ryan talks with Snowflake’s Head of Developer Experience Umesh Unnikrishnan about the industry-wide shift from “vibe coding” for quick prototypes to agentic engineering for enterprise-ready software, how enterprises can scale governance with guardrails like human-in-the-loop approval and control layers that go beyond the underlying LLM, and why Umesh predicts all developers will become someday become full-stack builders.
Researchers at Sysdig have linked a second attack on the same Langflow server to JADEPUFFER, the AI-agent-driven operator it first documented earlier this month. The same operator has now been spotted deploying ENCFORGE, a new compiled Go ransomware designed to encrypt model weights, vector indexes, training datasets, and other AI infrastructure files across the host filesystem. The entry
Vermont passed a new law on AI and mental health. One aspect to note is whether therapists will rubber-stamp AI. An AI Insider analysis and scoop.
21 points 4 comments on Hacker News · blog.jetbrains.com
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 and psychologists who study how AI is reshaping the way people work together, using those findings to help organizations redesign how work gets done. "We don't just study it, we also actively go in and change it," she explained. Her teams teach new ways of working and remap how work flows across companies, a challenge that many organizations are still struggling with, she said. Why AI speed isn’t translating into ROI Atlassian's annual State of Teams Report, which this year surveyed 12,000 global knowledge workers and interviewed roughly 200 Fortune 1000 executives, found a significant disconnect between activity and value, showing that everyone is using AI, while very few can yet locate where it pays off. "89% of those executives told us that individuals are speeding up in their companies, and only 6% of them said they could point to specific examples of clear ROI," Sands said. But roughly 14% of teams had translated AI usage into real value — meaning a single organization could contain a handful of high-performing teams surrounded by others seeing no return at all. Those leading teams shared three characteristics: context, workflows and culture. The teams pulling ahead were building what Atlassian calls a context graph by capturing goals, decisions, and organizational knowledge in shared digital records rather than leaving them in individual memory. Across products such as Jira and Confluence, the graph connects work items, goals and the people doing them, giving AI access to the organizational context it needs. On workflows, the winning teams redesigned entire end-to-end processes rather than simply accelerating isolated tasks. Otherwise, speeding up individuals who are pointed in slightly different directions only causes them to “very quickly start to crash into each other,” as Sands puts it. On culture, the fastest-moving teams worked under leaders who explicitly encouraged learning and experimentation, while making it clear that some experiments would fail. How leaders can move AI from individual hack to team advantage Experimentation and constraints are the fastest route to learning, Sands said. The teams seeing the biggest gains were deliberately imposing constraints on how they worked, from breaking every task into the smallest practical unit of work (a single story point) to committing to write no code by hand for a week. "Most of it is not sustainable to do forever, but it is a really, really fast way to learn," she said. Sands argued that another obstacle isn’t the technology itself but the fact that employees are figuring out AI on their own. Every worker develops different prompts, agents and assumptions, creating another layer of unspoken knowledge inside teams that rarely translates into organizational performance. To counter that, Atlassian experimented with AI working agreements at the start of projects, asking teams to decide not only what they would use AI for, but what they would deliberately avoid using it for, which agents they would share and what common skills would keep everyone working from the same context. Teams that adopted the practice used AI more, moved faster, made better decisions and ultimately produced higher-quality work. The broader lesson, Sands said, is that AI isn’t creating entirely new management problems so much as exposing old ones. Teams have always struggled with hidden assumptions and different mental models of their work. AI simply makes those gaps more consequential, increasing the importance of shared context and explicit ways of working. Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com .
How about AI telling you how to get a better photo of your subject?
Don't expect great gaming performance, but it seems like we could get a significant AI boost.
Hacker News
“GPT-5.5's API pricing is reshaping how startups build AI products”
