Operations | Monitoring | ITSM | DevOps | Cloud

Cost Optimization for AI Workloads: From Visibility to Control

ITOps teams can achieve cost management of AI workloads with an observability platform that connects AI usage and performance with cloud spend for clear visibility and predictability. Behind the buzz around artificial intelligence, or AI, many companies are discovering the hidden and compounding costs of AI adoption.

How LogicMonitor Delivers AI Cost Optimization

LogicMonitor delivers AI cost optimization by unifying infrastructure telemetry, AI-specific signals, and cloud financial data into a single workflow, so teams can move from visibility to continuous, operationalized cost control. In Cost Optimization for AI Workloads: From Visibility to Control, we explored why AI workloads introduce new layers of cost complexity—from GPU-heavy compute and token-based pricing to distributed infrastructure that obscures true spend.

Should You Use AI for Business Contracts?

AI is creeping into almost every corner of business life. It drafts emails, builds presentations, analyses data, and even creates marketing campaigns, So, it is hardly surprising that some companies have started using it to draft business contracts too. At first glance, this might sound like an efficient and sensible use of resources. Faster turnaround. Lower cost. Instant templates. But when it comes to legal agreements, speed and convenience are not always the priority.

AI-Driven Automated Testing for Oracle Applications

As enterprises continue to change rapidly, businesses depend on Oracle-based ecosystems to track their finances, supply chains, HR, and customer operations. With the increase of digital transformation in companies, these environments continue to become more complex. As a result, manual testing is no longer enough for maintaining pace with ongoing updates, integrations and customizations that occur within an organization's systems. This is where AI-powered automated testing for Oracle applications revolutionizes how quality assurance is approached.

Is Generative AI Eroding Our Ability to Think?

In aviation, there's a well-documented issue known as "automation addiction." As cockpit systems became more advanced, pilots gradually shifted from actively flying aircraft to supervising automated controls. Everything worked smoothly-until a system malfunctioned. Investigations revealed a troubling pattern: even experienced pilots sometimes struggled with basic manual maneuvers. Their hands remembered less because their brains had practiced less.

The Current State of Content Negotiation for AI Agents (Feb 2026)

The web was built for humans, but now the agents are taking over. Humans look at a web page and see content rendered by their browser. AI agents see 180,000 tokens of nav bars, footers, and div soup — burning through their context window on junk that makes them slower and stupider. The web needs to evolve, and we as developers are driving the shift. AI agents like Claude Code, Cursor, Codex, and Gemini are how we interact with documentation, CLIs, and products today.

The 2025 Wake-Up Call for Engineering Teams

For years, organizations tried to solve operational pain by collecting more data, adding more dashboards, and consolidating more tools. But 2025 exposed a deeper mismatch. Systems had become more distributed, AI-assisted, and interdependent than ever before, while teams had shrunk and on-call pressure had intensified. This wasn’t a tooling failure. It was an architectural and cognitive one.