Google makes Gemini 4 Argon available for long-running agent tasks

What changed: Google released Gemini 4 Argon globally for developers and enterprises through the Gemini API, AI Studio, and the Gemini platform. The model is aimed at complex, long-horizon workflows such as code migration, enterprise research, and cybersecurity; Google is charging an introductory $2 per million input tokens and $10 per million output tokens.

Google also added a task mode to the Gemini app, allowing the assistant to continue working when the user is away from the computer, and connected it to more than 40 applications including Instacart, OpenTable, Adobe, and Shopify.

Why it matters: Builders can now test agent workflows against a model explicitly positioned for multi-step work rather than simple chat. The pricing makes small pilots relatively inexpensive, but teams should measure total task cost, tool calls, retries, and human review—not just model-token cost.

Try/watch: Run a bounded code-migration or research workflow with approval required before external actions; monitor whether longer autonomous runs actually reduce labor or merely increase review work.

Workday turns Sana into a governed front door for HR and finance agents

What changed: Workday made Sana its main agentic interface for HR, finance, and IT, allowing employees to ask for outcomes in natural language while Sana coordinates the appropriate agents, tools, and people. Workday also launched its Agent Harness generally, with memory, guardrails, regional data controls, model choice, evaluations, and step-by-step traces for auditing.

The company said Sana can operate across Workday and tools employees already use, including Claude, Microsoft 365 Copilot, Teams, Slack, and Google Gemini Enterprise, while preserving permissions and approvals.

Why it matters: Enterprise buyers can evaluate Workday less as a collection of assistant features and more as an operating layer for controlled business-process automation. The audit trail and permission model are particularly relevant for payroll, recruiting, employee data, and financial close workflows.

Try/watch: Start with one low-risk, high-volume process such as employee service requests, and define the approval checkpoints, data boundaries, and evidence required before allowing the agent to take action.

DXC and LangChain package agent development for mission-critical IT operations

What changed: DXC Technology and LangChain announced a partnership combining DXC’s OASIS IT-operations platform with LangGraph for agent orchestration and LangSmith for development, evaluation, and monitoring. OASIS is scaling toward 125 customer environments across regulated industries, with agents investigating operational events and bringing humans into decisions when judgment or approval is needed.

Why it matters: The partnership offers a practical pattern for deploying agents in environments where reliability and accountability matter more than an impressive demo. Teams get a framework for testing and observing agent behavior, rather than treating production monitoring as an afterthought.

Try/watch: Before expanding an IT agent, require replayable evaluations for common incidents, explicit authority limits, and a human escalation path for changes to production systems.

Rocket Software acquires Geniez AI to bring agents directly to mainframes

What changed: Rocket Software acquired Geniez AI, whose agents operate directly on mainframes to monitor live systems, diagnose incidents, and execute workflows through natural-language instructions. Rocket said the technology will strengthen its EVA agentic platform for core systems and help address the shortage of mainframe expertise.

Why it matters: This targets a high-value but difficult automation market: mission-critical legacy systems that cannot simply be replaced or disconnected. Direct access could shorten incident response and help experienced operators transfer knowledge into repeatable workflows, but mistakes could affect essential business processes.

Try/watch: Treat mainframe agents as supervised operators first: begin with monitoring and diagnosis, require approval for changes, and keep a complete record of every recommendation and action.