agentic ai

5 articles

Okta CEO Pushes Back on 'SaaSpocalypse' Narrative — Identity Infrastructure Is AI's Foundation, Not Its Casualty

Okta CEO Todd McKinnon publicly refutes the growing market thesis that AI agents will render traditional SaaS platforms obsolete, arguing instead that identity infrastructure becomes more critical — not less — as autonomous agents proliferate. His argument reframes the AI disruption debate from 'replacement' to 'dependency,' positioning identity and access management as the connective tissue of any agentic enterprise stack. For investors and enterprise buyers, this signals that the SaaS layer closest to security and governance may actually benefit from the AI wave.

Jun 4Read →

Artificial Intelligence

Endava's AI Agent-First Delivery Model: A Blueprint for Enterprise Software Transformation

Endava, a global technology services firm, is restructuring its software delivery methodology to place AI agents at the center of development workflows rather than treating them as peripheral tools. This shift signals a broader industry inflection point where traditional sprint-based, human-led delivery cycles are being replaced by agent-orchestrated pipelines capable of autonomous task execution. The move positions Endava as an early enterprise-scale validator of agentic AI applied to professional services.

Jun 4Read →

Developer Technology

Managed Agents in the Gemini API: Google's Bid to Own the Agentic Development Stack

Google has introduced Managed Agents within the Gemini API, providing developers with a structured, infrastructure-backed framework to build, deploy, and orchestrate autonomous AI agents at scale. This release signals Google's intent to move beyond raw model access and compete directly in the emerging agentic middleware market. For enterprises and independent developers alike, it lowers the operational barrier to multi-step AI workflows without requiring custom orchestration infrastructure.

Jun 4Read →

AI Research

AI Co-Scientists: How Autonomous Research Agents Are Redefining Scientific Discovery

A new class of AI systems — termed 'Co-Scientists' — is emerging to function not as mere search tools, but as active research collaborators capable of forming hypotheses, designing experiments, and synthesizing multi-domain literature. These systems, pioneered by labs including Google DeepMind, represent a structural shift in how foundational science gets done. Decision-makers in biotech, pharma, and deep-tech must now assess whether AI co-authorship is a competitive edge or an existential baseline.

Jun 4Read →

Developer Technology

Managed Agents: Google's Developer-First Framework for Orchestrating Autonomous AI Workflows

Managed Agents represent a structured paradigm shift in how developers deploy, coordinate, and govern multi-step AI systems at scale. Google's developer-focused guidance signals that orchestrated agentic architectures are moving from research prototypes to production-grade infrastructure. For engineering teams evaluating AI deployment strategies, understanding the managed agent model is now a foundational competency.

Jun 4Read →