AWS Turns AI Agents Into a Workhorse as Nvidia Sees a Threat

It’s hard to get in and out of a conversation with a friend or even take a cursory look at a mainstream news source these days without a reference to some version of AI. Agentic AI has yet to crack the consumer attention case so far, but last week may have changed that.

The Prompt Economy had a big week for consumer exposure, new applications at work and use cases. The consumer exposure came courtesy of Time Magazine. It listed vibe coding, which is one of the foundations of the Prompt Economy, as one of its top 125 inventions of 2025. As is the case with most coverage of agentic AI, it came with equal parts excitement, intrigue and caution.

“The trend of vibe coding— tech novices using AI to write and refine code—hasn’t come without catches,” Time wrote. “For example: companies are now hiring engineers to fix errors in vibe-coded software. Warp (agentic infrastructure company) has taken a different approach with an agent-based alternative to traditional coding interfaces. Launched in June, Warp’s agentic development environment (ADE) allows software engineers to task AI agents with developing their code, then intervene when they notice errors.”

Autonomy Also May Create Vulnerabilities

Coding innovations were also the subject of news from Nvidia. Nvidia’s latest technical blog takes a stark look at the security risks embedded in agentic AI development tools, warning that the same autonomy that makes these agents powerful can also make them vulnerable. The post titled “From Assistant to Adversary: Exploiting Agentic AI Developer Tools” details how attackers can manipulate large language model (LLM)-driven coding assistants like Cursor, Claude Code, and GitHub Copilot through indirect prompt injection.

By embedding malicious instructions in open-source repositories, threat actors can exploit computer-use agents that autonomously read and execute commands. The blog situates this threat within a growing challenge for the Prompt Economy, where agentic systems blur the line between assistance and execution, often without adequate oversight or containment. Nvidia recommends developers adopt an “assume prompt injection” mindset, limiting agent autonomy, enforcing human review of sensitive commands, and running autonomous agents only within isolated environments.

“An overly privileged agent treating untrusted data as trusted can be turned into a tool working on behalf of the attacker,” the post reads. It adds that while agentic coding workflows have “unlocked rapid development capabilities across the industry,” their power must be matched by “mitigating policies” to prevent misuse. Nvidia urges developers to test systems with its garak vulnerability scanner, use NeMo Guardrails to contain model behavior, and above all, recognize that as AI gains autonomy, the developer’s own tools may become an adversary.

Other news of the week came from more predictable and innovative sources. Perhaps the biggest provider announcement came from Amazon Web Services. AWS introduced Amazon Quick Suite, a new agentic AI platform designed to automate complex workplace tasks and bridge the gap between consumer AI convenience and enterprise-grade functionality. The suite allows employees to query data, generate insights, automate workflows and build specialized agents that operate securely across internal systems like S3, Redshift and SharePoint, as well as more than 1,000 external applications through its Model Context Protocol.

AWS said the platform, which is already in use by Amazon employees and clients such as DXC Technology, Vertiv and Jabil, can cut multiday processes down to minutes, combining data analysis, automation and research capabilities into one workspace. Quick Suite marks Amazon’s bid to anchor itself at the center of the Prompt Economy, where generative agents move from consumer novelty to business necessity by directly executing work across enterprise systems.

As Swami Sivasubramanian, AWS’s Vice President of Agentic AI, explained in the company’s announcement: “What strikes me about these examples isn’t just the time saved — it’s how Quick is fundamentally changing our relationship with work. It’s removing the busy work that used to consume valuable time and energy and gives us the time back to focus on what matters. It brings together all the data, metrics, and institutional knowledge you need to make decisions, and helps you act on these decisions to drive outcomes.”

New Use Cases

New use cases also surfaced last week, notably IBM and S&P Global have announced a strategic alliance to deploy agentic AI across enterprise operations, beginning with supply chain management. The partnership embeds IBM’s watsonx Orchestrate framework into S&P Global’s Market Intelligence suite, combining S&P’s proprietary data with IBM’s AI orchestration capabilities. The goal: to help businesses automate procurement, assess supplier and country risk, and make faster, better-informed decisions in increasingly complex global supply chains.

Over time, the companies plan to expand the integration into finance, procurement, and insurance, using AI agents to convert data into actions that streamline operations. The collaboration positions both firms at the center of the Prompt Economy’s applied use cases, where agentic systems are moving from concept to enterprise infrastructure.

As S&P Global Market Intelligence President Saugata Saha explained, “By integrating IBM’s innovative AI capabilities with S&P Global’s distinctive data and analytics offerings, we are creating an exciting combination that is set to advance actionable insights and streamline workflows.” IBM’s Chief Commercial Officer Rob Thomas added that agentic AI can “connect data to action,” helping companies “restore control” in the face of global supply chain complexity.