Blog Archive
Optimizing Context Windows: Token Budgeting Best Practices
A 10M-token window is a trap, not a license. Learn to budget tokens like memory: account for every section, prioritize by recency and relevance, and cut cost and latency.
Synthetic Data Generation for Testing and Fine-Tuning
Real data is scarce, private, and expensive to label. Learn how to generate high-quality synthetic data with LLMs — for unit tests, evals, and fine-tuning datasets.
Automating Documentation with AI: Codebase to Docs
Stale docs die by neglect; AI keeps them close to the code. Build a scan → plan → generate → verify pipeline that turns any repo into current, useful documentation.
The State of Open-Source LLMs in 2026
Open weights route most production tokens now, Qwen leads the Hub, and China out-downloads the West. Here is the data-driven 2026 map for choosing an open model.
AI-Native Databases: Auto-Embeddings and Data APIs
The AI-native database keeps embeddings and your data in sync without a separate pipeline. Learn the trigger + queue + edge-function pattern on Supabase pgvector, and when auto-embeddings beats a standalone vector store.
Image Generation APIs and Structured Prompts
Turn image generation from a coin flip into a repeatable pipeline. Structure your prompt, set aspect ratio and size, ground with search, and wire it into code with Gemini image models.
Voice Interfaces: Speech-to-Text to LLM to TTS Pipelines
Under 1 second of perceived latency for a voice agent. Break down the STT -> LLM -> TTS pipeline, learn when streaming beats speech-to-speech, and engineer the latency budget line by line.
GenAI Security: The OWASP Top 10 for LLM Applications
The 2026 OWASP GenAI LLM Top 10 is grounded in ~10,000 real incidents. Learn the actual risks — prompt injection, excessive agency, misinformation — and the concrete mitigations for devs.
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.