Tag
#LLM
12 articles tagged with this topic.
AI/ML
Beyond the Linter: Engineering AI-First Review Pipelines in 2026
Manual code reviews are a bottleneck that costs your team millions in lost velocity. Here is how I built a multi-agent AI pipeline that catches race conditions, generates property-based tests, and reduced our MTTR by 42%.
June 1, 20266 min read
AI/ML
Beyond Vector Search: Building Production Knowledge Graphs with LLMs
Vector embeddings are hitting a wall. Learn how to build a robust, queryable knowledge graph from unstructured text using LLMs, Pydantic, and Graph databases for true multi-hop reasoning.
May 28, 20265 min read
AI/ML
Context is Everything: Engineering Persistent Memory for LLM Agents
Forget basic chat history. Scaling conversational AI in 2026 requires semantic retrieval, windowed summaries, and stateful graph management. Here is how I built a production-grade memory system using LangGraph and vector compaction.
May 12, 20266 min read
AI/ML
Scaling Engineering Velocity: Building Autonomous Code Review Pipelines in 2026
Stop wasting senior engineering hours on syntax and basic logic. I'll show you how we integrated GPT-5 and Llama 4 into our CI/CD to automate 80% of code reviews and unit test generation.
April 30, 20266 min read
AI/ML
Stop Shipping LLMs Blind: Building Production-Grade Evaluation Frameworks
Most LLM features die in production because teams treat testing like a vibe check. Here is how to build a rigorous, automated evaluation pipeline using G-Eval, DeepEval, and custom synthetic data generators.
April 14, 20265 min read
AI/ML
Stop Using Fixed-Size Chunking: Building Production RAG Pipelines That Actually Work
Fixed-size chunking is the quickest way to ruin a RAG pipeline. Learn how to implement semantic splitting and context-rich metadata injection to build production-grade retrieval systems.
April 2, 20266 min read
AI/ML
Engineering Reliable AI Agents: A Practical Guide to Tool Use and Function Calling
Stop treating AI agents like chat bots and start treating them like distributed systems. Here is how to implement tool-calling that actually works in production without the hallucinations.
March 29, 20266 min read
AI/ML
Beyond the Vibe Check: Engineering a Production-Grade LLM Evaluation Framework
Stop relying on manual 'vibe checks' for your LLM outputs. Here is how I built a robust, automated evaluation pipeline using G-Eval, RAGAS, and custom LLM-as-a-judge patterns for production-scale deployments.
March 25, 20266 min read
AI/ML
Building Production-Grade Knowledge Graphs: Beyond the LLM Extraction Hype
Stop building flat RAG systems. Learn how to extract high-fidelity entities and relationships from unstructured text using Pydantic, DSPy, and Neo4j to build a graph-augmented LLM stack that actually scales.
March 17, 20266 min read
AI/ML
Building Evaluation Frameworks for LLM Applications: Beyond the Vibe Check
Stop guessing if your prompt changes are working. Learn how to build a production-grade evaluation pipeline using LLM-as-a-judge, synthetic data, and automated regression testing.
March 9, 20265 min read
AI/ML
Beyond Fixed-Size Windows: Production Chunking Strategies for RAG in 2026
Fixed-size chunking is the reason your RAG pipeline fails on complex queries. Learn how to implement semantic, late-chunking, and recursive strategies that preserve context and boost retrieval precision.
March 1, 20265 min read
Deep Learning
Fine-Tuning Large Language Models: A Practical Guide
Learn to fine-tune LLMs for your specific use case. Covers LoRA, QLoRA, and best practices for efficient training.
November 18, 20242 min read