Presented by DigitalOcean From refactoring codebases to debugging production code, AI agents are already proving their value. But scaling them in production remains the exception, not the rule. In DigitalOcean’s 2026 Currents research report, based on a survey of more than 1,100 developers, CTOs, and founders, 67% of organizations using agents report productivity gains. Meanwhile, …
Traditional software governance often uses static compliance checklists, quarterly audits and after-the-fact reviews. But this method can’t keep up with AI systems that change in real time. A machine learning (ML) model might retrain or drift between quarterly operational syncs. This means that, by the time an issue is discovered, hundreds of bad decisions could …
Shadow mode, drift alerts and audit logs: Inside the modern audit loop Read More »
OpenClaw, the open source AI agent that excels at autonomous tasks on computers and which users can communicate with through popular messaging apps, has undoubtedly become a phenomena since its launch in November 2025, and especially in the last few months. Lured by the promise of greater business automation, solopreneurs and employees of large enterprises …
Runlayer is now offering secure OpenClaw agentic capabilities for large enterprises Read More »
For four weeks starting January 21, Microsoft’s Copilot read and summarized confidential emails despite every sensitivity label and DLP policy telling it not to. The enforcement points broke inside Microsoft’s own pipeline, and no security tool in the stack flagged it. Among the affected organizations was the U.K.’s National Health Service, which logged it as …
For the past three months, Google’s Gemini 3 Pro has held its ground as one of the most capable frontier models available. But in the fast-moving world of AI, three months is a lifetime — and competitors have not been standing still. Earlier today, Google released Gemini 3.1 Pro, an update that brings a key …
CX platforms process billions of unstructured interactions a year: Survey forms, review sites, social feeds, call center transcripts, all flowing into AI engines that trigger automated workflows touching payroll, CRM, and payment systems. No tool in a security operation center leader’s stack inspects what a CX platform’s AI engine is ingesting, and attackers figured this …
How attackers hit 700 organizations through CX platforms your SOC already approved Read More »
Late last year, Google briefly took the crown for most powerful AI model in the world with the launch of Gemini 3 Pro — only to be surpassed within weeks by OpenAI and Anthropic releasing new models, s is common in the fiercely competitive AI race. Now Google is back to retake the throne with …
Google launches Gemini 3.1 Pro, retaking AI crown with 2X+ reasoning performance boost Read More »
Despite growing chatter about a future when much human work is automated by AI, one of the ironies of this current tech boom is how stubbornly reliant on human beings it remains, specifically the process of training AI models using reinforcement learning from human feedback (RLHF). At its simplest, RLHF is a tutoring system: after …
Traditional ETL tools like dbt or Fivetran prepare data for reporting: structured analytics and dashboards with stable schemas. AI applications need something different: preparing messy, evolving operational data for model inference in real-time. Empromptu calls this distinction “inference integrity” versus “reporting integrity.” Instead of treating data preparation as a separate discipline, golden pipelines integrate normalization …
Agents built on top of today’s models often break with simple changes — a new library, a workflow modification — and require a human engineer to fix it. That’s one of the most persistent challenges in deploying AI for the enterprise: creating agents that can adapt to dynamic environments without constant hand-holding. While today’s models …