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cs.SE2026

Beyond Code Generation: Reliability, Verification, and Cost Economics in the Agentic Software Development Lifecycle

Happy Bhati

AI coding systems are moving from autocomplete and chat toward agents that can inspect repositories, edit multiple files, run tools, write tests, open pull requests, and work for l…

cs.SE2026

Agentic AI in the Software Development Lifecycle: Architecture, Empirical Evidence, and the Reshaping of Software Engineering

Happy Bhati

The arrival of large language models (LLMs) capable of multi-step reasoning, tool use, and long-horizon planning has produced a qualitative shift in software engineering. Where ear…

cs.SE2026

AI Observability for Developer Productivity Tools: Bridging Cost Awareness and Code Quality

Happy Bhati, Twinkll Sisodia

As AI-assisted development tools proliferate, developers face a growing challenge: understanding the cost, quality, and behavioral patterns of AI interactions across their workflow…

cs.SE2026

Workstream: A Local-First Developer Command Center for the AI-Augmented Engineering Workflow

Happy Bhati

Modern software engineers operate across 5-10 disconnected tools daily: GitHub, GitLab, Jira, Slack, calendar applications, CI dashboards, AI coding assistants, and container platf…

cs.SE2026

LLM-Augmented Release Intelligence: Automated Change Summarization and Impact Analysis in Cloud-Native CI/CD Pipelines

Happy Bhati

Cloud-native software delivery platforms orchestrate releases through complex, multi-stage pipelines composed of dozens of independently versioned tasks. When code is promoted betw…