Publication
Engineering notes
Systems engineering, AI, cloud, DevOps. Writing about production infrastructure, LLMs, and observability.
Top posts
View all →- Production-grade
Data Pipelines for LLM Training and Fine-Tuning
Cleaning, deduplication, instruction formatting, tokenization choices, and dataset hygiene for supervised fine-tuning and preference tuning—emphasizing data quality as the dominant lever.
- Advanced
Streaming LLM Systems and Token-Level Response Design
How partial decoding and streaming protocols shape UX, back-end buffering, and client rendering—without coupling to any single provider’s wire format.
- Production-grade
Building Real-Time Conversational AI Systems
WebSocket and HTTP streaming architectures, session memory, cancellation, and interruption handling for low-latency chat—where network, orchestration, and model tiers all shape the experience.
- Production-grade
API Safety Design for AI Agents
Rate limits, permissioning, tool sandboxing, and execution boundaries for agent-facing APIs—where the agent runtime is a new class of client that amplifies abuse patterns.
- Production-grade
Secure RAG Systems and Prompt Injection Prevention
How untrusted documents and web pages become indirect injection channels into retrieval pipelines—and how engineers harden ingest, retrieval, and tool boundaries without pretending RAG eliminates adversarial text.
- Production-grade
Safety Layers in Production LLM Systems
Prompt injection defenses, output filters, policy enforcement, and sandboxing patterns that stack like defense in depth—because no single layer catches every abuse case.
- Production-grade
Evaluation Frameworks for LLM Applications at Scale
Golden datasets, regression suites, LLM-as-judge patterns, and offline versus online evaluation loops—emphasizing measurement discipline over benchmark theater.
- Production-grade
LLM Observability in Production Systems
Prompt and completion logging, distributed tracing, token accounting, feedback capture, and debugging pipelines for LLMOps—balanced with privacy, retention, and cost.
- Production-grade
Memory Systems for LLM Agents — Short-Term vs Long-Term Memory
Episodic buffers, summarization, retrieval-augmented memory, and persistence patterns for agents—separating conversation state from durable knowledge stores.