Shashi Jagtap

Shashi Jagtap

Agentic AI and Quantum AI Researcher.
#8497222119 followers1 following
7 points
☀️ 2 day streak

About

Agentic AI and Quantum AI Researcher. Focused on building tools for AI Agents for better experience. Compound AI Research using DSPy. Multi-Agent system and Agent Frameworks

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Maker History

  • SpecMem
    SpecMemUnified Agent Experience & Pragmatic Memory for Coding Agent
    Dec 2025
  • DSPy Code
    DSPy CodeComprehensive CLI to Build and Optimize Your DSPy Code
    Nov 2025
  • SuperRadar
    SuperRadarGlobal Intelligence Radar for Agentic AI
    Oct 2025
  • SuperQuantX
    SuperQuantXThe foundation for the future of Agentic and Quantum AI
    Sep 2025
  • SuperOptiX AI
    SuperOptiX AIFull Stack Agentic AI Framework
    Jul 2025

Forums

Shashi Jagtap•

4d ago

SuperQode - Agent-Native Coding harness for agentic quality engineering

SuperQode is a terminal UI for interactive, agent‑driven QA. SuperQE is the automation CLI for CI and deep evaluation runs. Let agents test agents, capture evidence, and ship with confidence.
Shashi Jagtap•

2mo ago

SpecMem - Unified Agent Experience & Pragmatic Memory for Coding Agent

SpecMem is the first Unified Agent Experience and Pragmatic Memory platform for AI coding agents. It turns specifications into a shared, agent-agnostic memory layer that works across Kiro, GitHub SpecKit, Tessl, Cursor, Claude Code, Codex, Factory, Warp and more. SpecMem gives coding agents real context, detects drift, maps specs to code and tests, enables selective testing and delivers portable, unified memory for every agent.
Shashi Jagtap•

2mo ago

DSPy Code - Comprehensive CLI to Build and Optimize Your DSPy Code

Comprehensive CLI to Build and Optimize Your DSPy Code. Develop DSPy AI Agents and Optimize with GEPA. Think of it as Claude Code for AI Agents built with DSPy. In-built MCP client and local model suppor, Version-aware intelligence, Validate, Evaluate and Optimize Your Code as you Go, You manage your context not let others. The CLI that does not degrade your work with outdated library assumptions or pre-training artifacts. Perfect for everyone, DSPy beginners, experts and pros.
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