Results for “retrieval”
8 matches across blog posts, projects, case studies and series.
Blog posts
Calling an LLM From Apex: Where Python Still Wins
Apex makes the HTTP call to an LLM in about twenty lines. Everything that decides whether the feature survives — validation, retrieval, evals, cost — is the pa…
Feb 21, 2026Building Your First RAG Pipeline: A Developer’s Guide to Context-Aware AI
LLMs hallucinate. RAG fixes that. This guide walks through building a retrieval pipeline from scratch, covering ingestion, chunking strategies, and how to eval…
Oct 4, 2026Why Use Gemini for AI Automation: A Builder's Comparison
When Gemini is the right model for automation workflows and agents: current models, verified pricing, native multimodal input, long context, tool calling, and …
Aug 25, 2026Graph Engineering For AI Agents: My Production Playbook
Stop wiring agents with brittle scripts. Learn how I structure knowledge graphs and state machines to build AI agents that actually scale in production.
Feb 22, 2026Building State: A Deep Dive into LangChain Memory for Conversational AI
LLMs are stateless by default. To build a conversational agent that actually remembers, you need to manage context effectively. This guide covers implementing …
Feb 22, 2026Building Robust RAG Pipelines: A Deep Dive into LangChain Document Loaders
RAG systems live or die by the quality of their data ingestion. This guide covers how to architect a robust document loading pipeline using LangChain to handle…
Feb 22, 2026Unmasking the Black Box: Mastering LangChain Callbacks for Debugging
Master LangChain callbacks to debug AI agents. Learn to build custom handlers, trace execution flows, and fix 'black box' LLM issues.
Feb 22, 2026Building Long-Term Memory: Setting Up Vector Databases for Semantic Search in LangChain
LLMs have a context limit; your data doesn't. Learn how to implement vector databases in LangChain to enable semantic search and build robust RAG pipelines.