Blog Archive
Database Agents: Natural Language to SQL in Production
Let users ask your database questions in plain English — safely. A production guide to text-to-SQL agents: schema grounding, query validation, and read-only guardrails.
Evals for Agents: Unit Testing Multi-Step Reasoning
Agents are too expensive to test by eye. Learn how to write evals for multi-step reasoning: checkpoints, tool-call assertions, rubric scoring, and regression gates in CI.
Fine-Tuning Small Models for Edge Deployment
Big models don\u2019t fit on edge hardware, but small ones can learn your domain. A practical guide to fine-tuning Gemma-class small models and deploying them on-device.
Local-First AI: Ollama, llama.cpp, and On-Prem Inference
Keep your data in-house and your bills predictable. A practical guide to running open models locally with Ollama and llama.cpp, plus when on-prem inference beats the cloud APIs.
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.