The rise of agentic AI is transforming software development — from ideation to deployment, infusing every stage with collaborative digital co-workers that enhance speed, quality and transparency. These AI agents don’t just generate code; they orchestrate complex workflows, model business outcomes and enforce compliance — all while enabling developers to focus on innovation and oversight.
In a recent discussion during the AI Agent Builder Summit between Scott Hebner, principal analyst at theCUBE Research and host of “The Next Frontiers of AI” podcast, and Arun Varadarajan, chief commercial officer of Ascendion, Inc., they explored how AI-native orchestration engines are redefining enterprise software delivery. The conversation covered key advances in multi-agent workflows, goal-driven development and the scaling of AI agents across entire software development lifecycle processes.
“Software [AI agents] will write software,” Varadarajan said. “And humans will orchestrate, calibrate and refine the process in real time.”
Agentic AI reshapes the software development lifecycle
Ascendion’s AAVA+ platform exemplifies how agentic AI is revolutionizing modern software engineering. Built from the ground up to operate via hundreds of specialized, autonomous agents embedded in every SDLC role — from product management to site reliability — AAVA+ enables lean, goal-based orchestration that aligns tightly with enterprise needs. These agents, numbering over 4,000 in production, connect seamlessly with more than 80 DevOps tools (including Jira, Jenkins, SonarQube, and AppDynamics), creating what Varadarajan calls an “open kitchen model” that grants clients end-to-end process visibility.
“We don’t just integrate AI,” he said. “We build from it. Every part of AAVA+ is agentic, from ideation to delivery.”
This approach enables organizations to define business outcomes upfront and let the agents generate user stories, code, tests and architecture — all while maintaining enterprise governance, compliance and quality standards.
“We are moving from task-based AI to goal-first systems,” Varadarajan said. “You tell AAVA+ the kind of portal you want, and the agents come back with a solution. You’re not writing specs, you’re defining outcomes.”
By transitioning from task-level automation to goal-oriented orchestration, AAVA+ reduces friction, shortens timelines and bridges the gap between business strategy and technical execution.
For a deeper dive into Hebner and Varadarajan’s discussion, part of the “Next Frontiers of AI” podcast series, check out their full discussion:
Image: News/Dall-E
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