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A Python REPL loads ish-codes-magic/ishita-pal with transformers (checkpoint shards: DESY, CERN, IISER Pune, Coriolis, Hashkraft) and asks it what it does. It answers: Founding Engineer & AI Lead @ Storefox.ai. I build LLM pipelines that turn noisy real-world audio into insight, obsess over evals, and care a lot about making AI safe and reliable.

Hey, I'm Ishita! 👋

Building AI systems. Studying how they fail.

I'm a Founding Engineer & AI Lead at Storefox.ai, building production multimodal LLM systems for retail intelligence.

Alongside engineering, I work on technical AI safety research — particularly AI control, agent security, model evaluations, chain-of-thought faithfulness, and model misalignment.

🔬 Some things I've worked on

  • 🛡️ Janus — Open-source security framework for LLM agents, enforcing least-privilege policies at the tool-call boundary. Presented at Black Hat Arsenal, SecTor 2026.

  • 🧠 Multimodal CoT Faithfulness — Whitebox Research study investigating how faithfully models explain their reasoning across text and image inputs.

  • 🔍 LLM Self-Recognition — Replication experiments exploring whether language models recognize and prefer their own generations.

  • ⚙️ Transformer from Scratch — A modular PyTorch implementation of the original Transformer architecture.

🌱 Currently exploring

  • AI control and monitoring autonomous agents
  • Reasoning vs. agent-trace monitorability
  • Shutdown resistance and emergent misalignment

Tools I reach for: Python · PyTorch · LLMs · AWS · Docker · Git

🌐 Elsewhere on the internet

Portfolio · LinkedIn · Technical Writing · Substack

📈 GitHub stats

GitHub stats for ish-codes-magic Most used languages, excluding Jupyter Notebook and HTML

>>> ishita.generate("Can we work together?")
'Yes! LinkedIn or email are the fastest ways to reach me.'

Usually reading, listening to music, or wondering whether an LLM's explanation explains anything at all.

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