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Nvidia Forecasts 70% Revenue Growth as AI Spending Heads Toward $1.3 Trillion

Nvidia has decided to break with its usual practice of providing guidance only for the upcoming quarter and, for the first time, has given investors an outlook for the next fiscal year. The company expects to increase revenue by approximately 70% to $673 billion, which would further cement its position in the Dow Jones index and make it the secondlargest U.S. technology company by revenue, after Amazon. This projection substantially surpasses market expectations based on growth of about 44% and is effectively an attempt to convince the market that the AI boom is far from over. Against this backdrop, Nvidia stock moved higher.

Monitor smarter with Applications Manager's GenAI capabilities

GenAI has moved well past the pilot stage. According to a Gartner finding, by 2026, more than 80% of enterprises will have used GenAI APIs or deployed GenAI-enabled applications in production. Today, GenAI is becoming an integral part of how infrastructure and application teams work every day. Organizations are depending on LLMs from a diverse range of vendors—OpenAI, Anthropic, Google AI, and DeepSeek—based on the strengths each offer for different use cases.

Questions to Ask About AI Agent Orchestration

Running AI coding agents in parallel across repositories is no longer experimental. It’s how high-performing engineering teams ship faster. But the tools you pick to orchestrate those agents can either multiply your output or introduce new bottlenecks. GitKraken gives your team a purpose-built surface for AI coding agent orchestration through Kepler, its agent-agnostic development environment. Before you commit to any orchestration tool, though, you need to ask the right questions.

McKinsey Says Agentic Enterprises Need "Automated Guardrails." Here's What That Means

TLDR/: McKinsey’s new research on AI transformation, published August 28, 2026, studied 20 companies that have created real economic value from AI and found that only a small number have reached “Stage 3: Agentic AI enterprise.” The capability that separates Stage 3 from Stage 2, per McKinsey’s own maturity framework, is orchestration layers and automated guardrails: the ability to govern agent actions automatically, in real time, rather than reviewing them after the fact.

n8n pricing in 2026: every plan, the execution math, and what AI agents change

n8n pricing runs €24 per month for 2,500 workflow executions (Starter), €60 for 10,000 (Pro), and €800 for 40,000 (Business), with 17 percent off on annual billing and custom Enterprise pricing above that. Every plan includes unlimited users and unlimited workflows. The self-hosted Community Edition is free with unlimited executions; you pay only for your server.

CoreWeave pricing in 2026: every GPU rate and what a node really costs

CoreWeave, a GPU cloud provider, prices start at $6.16 per GPU hour for an Nvidia H100 and reaches $8.60 for a B200, sold as fixed multi-GPU nodes: an 8x H100 node lists at $49.24 per hour on demand. Spot rates run up to 60 percent below on demand, reserved contracts discount up to 60 percent, and egress is free.

How we built data-driven AI Golden Paths at Datadog

As teams rush to adopt AI, they often find themselves with conflicting workflows unique to each individual developer. To manage costs and promote good development practices, organizations need to establish Golden Paths around AI usage. AI Golden Paths are standardized flows that help developers work with agents more reliably and effectively. But how do you sift through all the possible workflows to decide what these Golden Paths should be?