Every AI headline in 2026, from frontier model launches to boardroom debates about agentic workflows, gets filed under the same catch-all word: AI. That flattening obscures a distinction that matters enormously for anyone trying to separate real capability from hype. Artificial intelligence is not one thing. It is a three-tier hierarchy, and almost everything currently […]
OpenAI's Fidji Simo is departing her full-time role as the company's AGI chief and is transitioning to being a "part-time advisor," she said on X.
The news follows Simo's original announcement in April that she would take a few weeks of medical leave due to a neuroimmune condition, shortly after she had taken on the AGI chief title. (She had formerly been the company's CEO of applications). Around the same time, COO Brad Lightcap also stepped down from his role to focus on "special projects," and OpenAI CMO Kate Rouch also stepped down in order to focus on her health. Rouch planned to return to a "more narrowly scoped role" when her health …
Read the full story at The Verge.
The shift towards video games for AGI training could redefine AI development, influencing market dynamics and competitive AI model rankings.
The post Video games seen as superior AGI training data over internet: CEO appeared first on Crypto Briefing.
When it comes to achieving artificial general intelligence (AGI), large language models just don’t have what it takes. Models like ChatGPT and Claude are great at text, but they’re less skilled at understanding how things actually move through space and time — an essential skill for producing intelligence that generalizes. That gap, it turns out, might be filled by gaming data. That’s the bet behind General Intuition, a […]
When it comes to achieving artificial general intelligence (AGI), large language models just don’t have what it takes. Models like ChatGPT and Claude are great at text, but they’re less skilled at understanding how things actually move through space and time — an essential skill for producing intelligence that generalizes. That gap, it turns out, might be filled by gaming data. That’s the bet behind General Intuition, a […]
A prompt injection attack can trick GitHub’s preview Agentic Workflows into retrieving content from private repositories and publishing it publicly, exposing a broader risk as enterprises deploy AI agents with privileged access to software development environments, according to new research from Noma Security.
The AI security company detailed the attack, dubbed GitLost, in a blog post, saying an unauthenticated attacker could exploit GitHub’s preview Agentic Workflows by submitting a crafted GitHub issue to a public repository. If the AI agent has read access to private repositories within the same organization, it can retrieve sensitive information and publish it in a public comment, the company said.
GitHub Agentic Workflows combine GitHub Actions with AI models such as Claude or GitHub Copilot, allowing developers to define workflows in Markdown. At the same time, AI agents read issues, invoke tools, and perform tasks on their behalf.
“What will happen when the GitHub agent reads so
JetBrains has announced JetBrains AI for Teams and Organizations, an initiative that promises to deliver a broad set of AI capabilities that connects AI tools developers already use with shared context, reusable agentic workflows, and organization-wide governance and cost control for software production. The intent is to move users from fragmented AI usage to coordinated software development, the company said.
Unveiled July 7, JetBrains AI for Teams and Organizations will provide a unified system for agentic software development, according to the company. Vendor-agnostic by design, JetBrains AI for Teams and Organizations will connect external tools via Model Context Protocol (MCP) and external agents via Agent Client Protocol (ACP). Organizations will be able to evolve their AI stack without sacrificing governance or developer choice, the company said.
Alongside new capabilities, JetBrains plans to evolve its commercial model to better support AI-powered software development. For bus
Behind a customer's API, a high-quality answer isn't enough. It has to be usable, which means on time. Delivering that consistently is a problem about variance, not speed, and the fixes are counterintuitive.
The post Tail Control: The Counterintuitive Engineering of Reliable Agentic Workflows appeared first on Towards Data Science.
