Blog Archive
Self-Hosting an LLM Gateway with LiteLLM
One OpenAI-compatible endpoint in front of every model your team uses, with routing, rate limits, spend caps, and auth. Deploy LiteLLM and stop hard-coding provider keys in your services.
The Agent SDK Landscape: PydanticAI vs. LangGraph vs. CrewAI
Stop choosing an agent framework at random. Compare PydanticAI, LangGraph, and CrewAI on statefulness, multi-agent design, type safety, and operational control — then pick the right tool per job.
Multimodal Pipelines: Images, Audio, and Video in LLMs
Stop reducing your data to text before the model sees it. Send images, audio, and video natively to Gemini and build one pipeline that understands them together.
Building a Multi-Agent System with Google ADK
Move from single-prompt chatbots to a team of collaborating agents. Use Google ADK hierarchy, workflow agents, and session state to orchestrate a research-and-write pipeline.
Linux Foundation Launches the Tokenomics Foundation to Define the Economics and ROI of AI Value
The Linux Foundation launches the Tokenomics Foundation with 30 founding members to establish open, vendor-neutral standards, benchmarks and best practices for measuring the true cost, value and ROI of AI spend.
Web Scraping for RAG: Clean Data Extraction at Scale
Junk in, junk out. Learn to extract LLM-ready Markdown from JS-heavy sites with Playwright, strip boilerplate, and chunk the results for a RAG pipeline.
Building an AI Pair Programmer: From IDE Plugin to CLI
An AI pair programmer is an agent with file tools and a loop. Learn the architecture, then build a minimal CLI pair programmer in Python with Gemini function calling.
Time-Series Forecasting with Foundation Models
Chronos, TimesFM, and Lag-Llama forecast series they have never seen. Learn how time series became token sequences, and when to use a foundation model over ARIMA.
Knowledge Graphs for AI: GraphRAG Explained
Naive RAG misses the answer that connects many documents. GraphRAG builds a knowledge graph from text and queries it. Learn the indexing pipeline, community detection, and query modes.
Semantic Caching to Reduce Latency and Spend
Users ask the same question a hundred different ways. Semantic caching serves cached answers for similar queries — cutting LLM spend by up to 86% and latency from seconds to milliseconds.
LangGraph: Stateful, Graph-Based Agent Orchestration
LangGraph turns an agent into an explicit graph of nodes with durable state. Learn StateGraph, checkpointers, thread_id, and crash-resilient execution.
Tools, Function Calling, and the Agent Execution Loop
The agent loop is a model deciding which tools to call, observing results, and iterating. Learn function declarations, tool_choice modes, and parallel calling.