Aditya Mishra

engineering, applied AI, and systems

I’m a software engineer and engineering leader focused on building production AI systems and the infrastructure that makes them scale. Currently, I’m a Principal Engineer at Sharpsell.ai, working at the intersection of AI and systems engineering.

My experience spans both the backend and platform foundations that systems are built on, and the production AI applications that run on top of them. My current work includes AI applications, voice agents, multi-agent systems, and core platform infrastructure.

I write about the engineering behind these systems: how they work, the decisions and trade-offs involved in building them, and what it takes to make them scalable and reliable in production. I also write about technical ideas I want to understand more deeply, often by implementing and testing them myself.

Recent Projects

Indic Smart Turn

End-of-turn detection for voice agents in English and 11 Indian languages, built on Pipecat's Smart Turn. It runs on one CPU core and beats Smart Turn v3.2 by 12 to 22 points on the eight Indian languages that v3.2 has no training data for.

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Retold

A local, provider-neutral memory layer for AI agents, with evidenced records, hybrid retrieval, and a usefulness judge that admits a record only if it would change the answer.

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LLM Inference Experiments

Six quantization methods on Llama 3.1 8B, scored against the same fp16 baseline. Speculative decoding that matches greedy output and arrives 1.8x sooner, plus KV cache size, wall time, and hosted prompt-cache cost.

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Real-Time Streaming Systems

Kafka ingest into Flink jobs that window product conversion and raise stateful fraud alerts as the events arrive.

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Self-hosted Video Recorder

A headless bot joins a Daily room, encodes each participant in real time, and composes an MP4 that switches layout as people join and leave.

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Async Job Processing

Priority queues, retries with backoff, and a Postgres record for every job. If Redis dies, queued and started work is requeued on boot.

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