Polymarket Faces Ban In Indonesia Amid Growing Global Crackdown

Hyperliquid's validator-driven model reduces reliance on external oracles, potentially enhancing market resilience and decentralization. The post Hyperliquid removes need for external oracles in prediction markets appeared first on Crypto Briefing.

Polymarket's whale-dominated voting highlights governance centralization risks, potentially undermining trust and fairness in prediction markets. The post Polymarket delays voting process revamp as nine whales dominate disputes appeared first on Crypto Briefing.

Hyperliquid launched canonical prediction markets for offchain events, expanding beyond perps as analysts frame it as an onchain superapp.

The definitive story of how Claude Code and OpenClaw kicked off computing’s biggest transformation possibly ever.

ClickUp CEO Zeb Evans announced last week that the collaboration software company, last valued at $4 billion in 2021, had laid off twenty-two percent of its workforce — framing the cuts not as cost reduction but as a structural shift toward AI-driven operations. The company has deployed roughly 3,000 internal AI agents to handle complex tasks, with […]

Hyperliquid, the decentralized perpetual futures platform with over $5.5 billion in total value locked, has launched canonical prediction markets for real-world offchain events, powered by automated software run by its validator network. Validator-Based Markets Enter the Fray Hyperliquid, the L1 best known for its perpetual futures exchange, announced on May 26 that it now supports […]

The gap between what agentic AI promises and what it actually delivers in live environments is now one of the most consequential engineering problems in the industry. It is also, frustratingly, one that the field has been slow to name precisely, let alone fix...

AI agents look brilliant in a demo because demos are friendly worlds. The data is curated, the tools behave, and nothing important changes while the agent is in mid-thought. Production is the opposite: data arrives late, facts conflict, permissions bite, APIs time out, and the underlying state changes constantly. That gap is why early “agents in production” often get scoped down to something safer: read-only assistants, human-in-the-loop workflows, or narrow domains with heavily curated data. Several high-profile deployments have also been scaled back after meeting messy real-world constraints. Rather than being a verdict on autonomy, these stumbles are a reminder that autonomy is unforgiving. Small cracks in your data stack become large cracks in agent behavior. The same pattern shows up whenever agents move from toy workflows to systems with real state. As scope increases, weak guarantees create predictable symptoms: overconfident actions on stale data, brittle reasoning when meaning