7 papers
MAPLE: A Sub-Agent Architecture for Memory, Learning, and Personalization in Agentic AI Systems
Deepak Babu Piskala
Large language model (LLM) agents have emerged as powerful tools for complex tasks, yet their ability to adapt to individual users remains fundamentally limited. We argue this limi…
Spec-Driven Development:From Code to Contract in the Age of AI Coding Assistants
Deepak Babu Piskala
The rise of AI coding assistants has reignited interest in an old idea: what if specifications-not code-were the primary artifact of software development? Spec-driven development (…
From Everything-is-a-File to Files-Are-All-You-Need: How Unix Philosophy Informs the Design of Agentic AI Systems
Deepak Babu Piskala
A core abstraction in early Unix systems was the principle that 'everything is a file', enabling heterogeneous devices and kernel resources to be manipulated via uniform read/write…
The AI Roles Continuum: Blurring the Boundary Between Research and Engineering
Deepak Babu Piskala
The rapid scaling of deep neural networks and large language models has collapsed the once-clear divide between "research" and "engineering" in AI organizations. Drawing on a quali…
PROFASR-BENCH: A Benchmark for Context-Conditioned ASR in High-Stakes Professional Speech
Deepak Babu Piskala
Automatic Speech Recognition (ASR) in professional settings faces challenges that existing benchmarks underplay: dense domain terminology, formal register variation, and near-zero…
Mind the Goal: Data-Efficient Goal-Oriented Evaluation of Conversational Agents and Chatbots using Teacher Models
Deepak Babu Piskala, Sharlene Chen, Udita Patel +2
Evaluating the quality of multi-turn chatbot interactions remains challenging, as most existing methods assess interactions at the turn level without addressing whether a user's ov…