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New study reveals optimal windows for clarifying instructions in long-horizon agents, with goal info losing value after 10% of execution.

When Should AI Agents Ask for Clarification? Timing Matters

A forced-injection framework across 6,000+ runs shows that the value of clarification depends sharply on information type and timing. Goal clarification loses nearly all value after 10% of execution, while input clarification retains value through 50%. Current frontier models fail to ask within optimal windows.

Ensuring transparency and trust in autonomous AI agents through on-chain verification on Solana

Verifiable Proofs for Auditing AI Agents on Solana

Explore how verifiable proofs enable transparent auditing of AI agents on the Solana blockchain, combining cryptographic guarantees with decentralized trust to ensure accountability and reliability in autonomous systems.

Early beta for SuperGrok Heavy subscribers offers fast, flicker-free CLI with skills, plan viewer, and parallel subagents.

xAI Launches Grok Build Beta: CLI with Multi-Agent Coordination

xAI releases Grok Build Beta, a command-line interface for SuperGrok Heavy subscribers. Features include multi-agent coordination, skills adaptation, plan viewer, marketplaces, and design polish commands. Try now via curl install.

Leaked screenshots show Grok automatically assembling daily AI news briefings from saved Skills, part of a broader industry trend toward modular, shareable prompts.

Grok Skills: Reusable Instruction Sets for Task Automation

xAI's Grok chatbot is developing a Skills feature that stores reusable instruction sets for automation. Leaked screenshots and code references indicate modular templates for scheduled workflows, similar to Anthropic and OpenAI's recent moves.