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Srijan Verma

Building production-grade AI systems, LLM orchestration layers, and low-latency backend pipelines that actually scale.

Joined on  srijanatwork1@gmail.com
Stop Using Regex: Building Zero-Crash LLM JSON Pipelines in Production

Stop Using Regex: Building Zero-Crash LLM JSON Pipelines in Production

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3 min read

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Surviving the 429 Storm: Building Resilient LLM Fallbacks in Production

Surviving the 429 Storm: Building Resilient LLM Fallbacks in Production

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Taming Context Bloat: How to Scale AI Agent Memory Without Breaking the Token Bank

Taming Context Bloat: How to Scale AI Agent Memory Without Breaking the Token Bank

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Stop Passing Full Chat Transcripts: Build a Two-Tier AI Memory System

Stop Passing Full Chat Transcripts: Build a Two-Tier AI Memory System

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Bulletproofing AI Agents: How to Prevent $2,000 Infinite API Loops

Bulletproofing AI Agents: How to Prevent $2,000 Infinite API Loops

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Stop Choosing Between RAG, Fine-Tuning, and Agents: Build the Hybrid Trio Instead

Stop Choosing Between RAG, Fine-Tuning, and Agents: Build the Hybrid Trio Instead

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Stop Leaking Data to Cloud APIs: Self-Hosting DeepSeek Locally with Ollama

Stop Leaking Data to Cloud APIs: Self-Hosting DeepSeek Locally with Ollama

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Deterministic Guardrails: Stop LLM Tool Calling Failures at Runtime

Deterministic Guardrails: Stop LLM Tool Calling Failures at Runtime

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Stop Using Naive Hugging Face Pipelines: Scale LLM Serving with vLLM

Stop Using Naive Hugging Face Pipelines: Scale LLM Serving with vLLM

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Stop Wasting Tokens: Building a Sub-50ms Semantic Cache with Redis

Stop Wasting Tokens: Building a Sub-50ms Semantic Cache with Redis

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Building Event-Driven AI Agents: Replacing Polling Loops with Redis Streams and Idempotent Workers

Building Event-Driven AI Agents: Replacing Polling Loops with Redis Streams and Idempotent Workers

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