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About Logeshwaran
I am an experienced AWS Full Stack Developer with expertise in building scalable, cloud-native applications using a wide range of technologies, including AWS, Angular, Java, Node.js, Python, Terraform, Docker, and TypeScript. With a strong focus on delivering high-performance solutions, I specialize in leveraging AWS services for cloud architecture, creating dynamic front-end interfaces, and building efficient back-end systems. I have hands-on experience in automating infrastructure with Terraform, containerizing applications using Docker, and implementing DevOps best practices.
Day 46: Synthetic Data That Doesn't Clone GitHub Noise
Posted inAI Machine Learning

synthetic code data: Synthetic Data That Doesn’t Clone GitHub Noise

This senior-level guide covers synthetic code data with production trade-offs for reliability, security, and cost.
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Day 47: Serving Custom Models Behind the Same API
Posted inAI AWS System Design

custom model serving: Serving Custom Models Behind the Same API

This senior-level guide covers custom model serving with production trade-offs for reliability, security, and cost.
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Day 48: License and Training-Data Risk
Posted inAI Machine Learning

AI training data compliance: License and Training-Data Risk

This senior-level guide covers AI training data compliance with production trade-offs for reliability, security, and cost.
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Day 49: Eval for Fine-Tunes: Blind A/B on Real Tickets
Posted inAI Machine Learning

Day 49: Eval for Fine-Tunes: Blind A/B on Real Tickets

This senior-level guide covers Eval for Fine-Tunes with production trade-offs for reliability, security, and cost.
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Day 50: Project: Internal SDK Autocomplete Model
Posted inAI AWS Machine Learning

Day 50: Project: Internal SDK Autocomplete Model

This senior-level guide covers Internal SDK Autocomplete Model with production trade-offs for reliability, security, and cost.
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Posted inAI AWS Debugging

CloudWatch EMF for LLM Cost: Per-Tenant Token Metrics That Survive Sampling

This senior-level guide covers CloudWatch EMF for LLM Cost with production trade-offs for reliability, security, and cost.
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Posted inAI AWS System Design

SQS FIFO Lambda: SQS FIFO + Lambda: Ordered Agent Job Queues Without Double-Applies

This senior-level guide covers SQS FIFO Lambda with production trade-offs for reliability, security, and cost.
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Posted inAI AWS Machine Learning

Bedrock Converse toolConfig: Idempotent Tool Results Under Retries

This senior-level guide covers Bedrock Converse toolConfig with production trade-offs for reliability, security, and cost.
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Posted inAI AWS System Design

IAM for AI Agents: Condition Keys That Limit Blast Radius by Tag

IAM for AI agents means tag-based condition keys — not app-only path checks — so Bedrock/S3/Dynamo access fails closed outside the tenant cell even when the model hallucinates.
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Day 51: Multi-Agent Roles: Planner, Implementer, Critic
Posted inAI System Design

multi-agent orchestration: Multi-Agent Roles: Planner, Implementer, Critic

This senior-level guide covers multi-agent orchestration with production trade-offs for reliability, security, and cost.
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