-- W e present a n approach to software testing automation using Agentic Retrieval - Augmented Generation (RAG) systems for Quality Engineering (QE) artifact creation. We combine autonomous AI agents with hybrid vector - graph knowledge systems to automate test plan, case, and Q E metric generation. The system achieves remarkable accuracy improvements from 65% to 94.8% while ensuring comprehensive document traceability throughout the quality engineering lifecycle. Experimental validat ion of enterprise Corporate Systems Engineering and SAP migration projects demonstrates an 85% reduction in testing timeline, a n 85% improvement in test suite efficiency, and projected 35% cost savings, resulting in a 2 - month acceleration of go - live . Index Terms -- agentic systems, retrieval - augmented generation, software testing, quality engineering, multi - agent orchestration, hybrid vector - graph, test automation, SAP testing, en terprise systems These limitations become particularly pronounced in enterprise software testing, where maintaining traceability between requirements, test cases, and business logic is paramount for regulatory compliance and quality assurance.

In this work, we aim to develop LLM agents to mitigate social norm violations in negotiations in a multi-agent setting. We simulate real-world negotiations by letting two large Language Models (LLMs) play the roles of two negotiators in each conversation. A third LLM acts as a remediation agent to rewrite utterances violating norms for improving negotiation outcomes. As it is a novel task, no manually constructed data is available. To address this limitation, we introduce a value impact based In-Context Learning (ICL) method to identify high-quality ICL examples for the LLM-based remediation agents, where the value impact function measures the quality of negotiation outcomes. We show the connection of this method to policy learning and provide rich empirical evidence to demonstrate its effectiveness in negotiations across three different topics: product sale, housing price, and salary negotiation. The source code and the generated dataset will be publicly available upon acceptance.

OctoML says it has ended its business relationship with Civitai days after an investigation by 404 Media revealed the text-to-image platform was being used to generate images that "could be categorized as child pornography." While OctoML initially indicated it would continue working with Civitai and introduced new measures to curb the creation of harmful images, 404 Media reported on Saturday that it has now decided to cut ties with the platform altogether. According to 404 Media's December 5 report, internal communications showed that OctoML was aware some Civitai users were creating sexually explicit material that included nonconsensual images of real people and pornographic depictions of children. In a followup report this weekend, the publication noted that OctoML rolled out a filter to block the generation of all NSFW content on Civitai before announcing its decision to pull out. Civitai also added new moderation methods in response to the investigation earlier this week, including a mandatory embedding called Civitai Safe Helper (Minor) that bars the model from generating images of children if "a mature theme or keyword is detected," according to 404.

Generative AI will change the nature of how we interact with all software, and given how many brands have significant software components in how they interact with customers, generative AI will drive and distinguish how more brands compete. In our last HBR piece, "Customer Experience in the Age of AI," we discussed how the use of one's customer information is already differentiating branded experiences. Now with generative AI, personalization will go even further, tailoring all aspects of digital interaction to how the customer wants it to flow, not how product designers envision cramming in more menus and features. And then as the software follows the customer, it will go to places that range beyond the tight boundaries of a brand's product. It will need to offer solutions to things the customer wants to do.

"Contracts are the foundation of commerce." Does this sound like an overstatement? When you think about almost any ongoing business transaction (be it with a supplier, a customer, a partner or an employee), there is most likely a contract that defines the terms of the relationship--the obligations, the entitlements, the dollars in and dollars out. Amazingly, the written word itself seems to have been invented to record contracts. According to a recent exhibit at the British Library, cuneiform script has been traced back to traders in Mesopotamia whose commercial agreements became too complex to commit to memory. However, in today's fast, digital-first business environment, the critical data found in contracts is left out of the operational systems of record that companies run on.

In 2018, Streamr announced a partnership with Daisy AI, Japan, an AI platform using blockchain for deep learning, based in Japan. Streamr intended to become Daisy AI's official data provider to exclusively sell data from Streamr's decentralized data Marketplace. Daisy AI planned to purchase data for a wide range of purposes, including forecasting stock and cryptocurrency prices, economy insights, footfall and traffic. Shohei Ohsawa, representative director of Daisy AI and associate professor at the University of Tokyo, recently made a series of racist and offensive statements on Twitter. He wrote that "Daisy does not hire Chinese people."

Employees at Microsoft on Friday demanded the company cancel a contract to supply its augmented-reality headsets to the U.S. Army, warning in a letter that putting HoloLens in the military's hands could "help people kill." Writing to chief executive Satya Nadella, more than 50 workers said the devices would be "turning warfare into a simulated'video game.'" They also urged Microsoft, which won the $480 million contract in November, to "cease developing any and all weapons technologies" for the government. "As employees and shareholders we do not want to become war profiteers," the letter concluded. "To that end, we believe that Microsoft must stop in its activities to empower the U.S. Army's ability to cause harm and violence."

AI (artificial intelligence) technology is advancing at an exponential rate, and some workers are feeling nervous about what it might mean for their job security. But while AI offers many advantages, there is one factor hampering its full-blown adoption – a lack of emotional intelligence. Robots won't take over from humans until they become advanced in reacting to emotional cues – an inherent aspect of a human workforce which remains very much needed. AI can bring manifold advantages to a business and many are already heralding its transformative properties. No industry has been untouched by the AI revolution.

Building and managing business network in the digital economy is a challenging task. With multiple communication channels, both conventional (e.g., phones) and new (e.g., social media), your contacts can become a real mess. As a result, both your productivity and your ability to build strong business relationships and leverage your network's value suffer. Fortunately, new AI-powered tools for social media, contact management and networking solve most of these problems. One option to help you stay on top of your business relationships in the digital age is to use AI-enabled contact managers like Etch.

Thirty-three percent of consumers who abandoned a business relationship did so because personalization was lacking. Hyper-Relevance is the new baseline for success for addressing banking customer demands for tailored experiences. Consumers want to be treated'special' in every business relationship. No longer is it acceptable to place customers or members in segments that are defined only by age or income, or lack differentiation based only on the length, depth, value or lifestage of the relationship. Consumers know organizations have enough insight to know them, look out for them and reward them.