{"id":999,"date":"2021-09-15T19:03:22","date_gmt":"2021-09-15T15:33:22","guid":{"rendered":"https:\/\/jetwp.ir\/demos\/woocemmerce-catalog-mode\/?p=999"},"modified":"2026-10-06T17:22:49","modified_gmt":"2026-10-06T13:52:49","slug":"how-agentic-ai-is-transforming-software","status":"publish","type":"post","link":"https:\/\/jetwp.ir\/demos\/woocemmerce-catalog-mode\/2021\/09\/15\/how-agentic-ai-is-transforming-software\/","title":{"rendered":"How agentic AI is transforming software development"},"content":{"rendered":"

\"agentic<\/p>\n

Deployment and operational tools extend this layer further by enabling safe, scalable adoption of agentic systems. Search capabilities from providers such as SerpApi give agents access to live web knowledge, ensuring responses are current and accurate. Agents can ground their outputs in context-rich knowledge from vector databases such as Pinecone and Weaviate, or from enterprise knowledge bases https:\/\/housebru.com\/modern-technologies-for-financial-success-application-development-services.html<\/a> like Confluence and Wikis. Without them, developers must manually format prompts, parse raw outputs, and handle API execution. The agent runtime & infrastructure layer provides the operational environment where agents are deployed, executed, and scaled.<\/p>\n<\/p>\n