Large language model (LLM)-based software engineering (SWE-) agents have recently demonstrated remarkable progress on realistic software engineering tasks such as code review, bug fixing, and repository-level reasoning. Most SWE-agents start from a fresh…
For years, organizations relied on static dashboards, reports, and human interpretation to make decisions. AI agents are collapsing the gap between insight and action.
Peek into the world of vibe coding and its potential to transform your business, from simple websites to complex data analysis tools.
Salesforce AI Research announces framework to optimize agent capability and consistency through synthetic data, realistic testing, and reinforcement learning. Even as AI models grow more sophisticated, a curious challenge persists: systems that solve…
Explore new Agentblazer Status content, a fun Halloween badge, strategic AI agent planning, and a comprehensive Data Cloud learning journey.
In this seamless ecosystem, conversations become actions, AI agents sit right in workflows, and workforces scale up or down to meet customer demand.
New capabilities help you reach customers faster across channels, decrease third-party integrations and improve personalization
AI can feel magical—or mildly terrifying. Here’s how thoughtful UX turns fear into confidence and delight.
Agentic personalization only works when your customer profiles are unified and accurate
