Blog
Latest articles
Running LLMs Locally for Privacy-Sensitive Work: A Practical Setup Guide
When local LLMs make sense for privacy, how to set up Ollama with IDE integration, performance benchmarks on real hardware, and the honest quality trade-off.
Vercel AI SDK Guide for Next.js Streaming and Multi-Step Agents
Master the Vercel AI SDK in Next.js App Router. Learn streamText, useChat, generateObject with Zod, multi-step tool agents, and multi-provider integration.
Anthropic Claude API and Message Batches Guide for Developers
Complete guide to the Anthropic API - authentication, message format, streaming, tool use, prompt caching for 90% cost reduction, batch processing, and production error handling.
Prompting for Classification: Getting Consistent Labels Every Time
How to write prompts that produce reliable, consistent classification labels - covering category definitions, JSON output, multi-label vs single-label, confidence scores, and when to use zero-shot vs few-shot vs fine-tuning.
OpenAI o1 and o3 Reasoning Models: Architecture, Test-Time Compute, and Production Routing
What makes o1 and o3 different from GPT-4o, where they dramatically outperform standard models, where they are overkill, and how to decide which model to use.
LLM Privacy for Enterprise: What Actually Happens to Your Data
Whether providers train on your API calls, what zero data retention means, on-premise alternatives, and how to build a practical LLM data policy for your team.
Prompting for Summarization: Techniques That Actually Work
Learn how to write prompts that produce accurate, concise summaries - covering length control, chain-of-density compression, source citation, and prompt differences across email, meeting, and document contexts.
LLM Knowledge Cutoffs: What They Mean and How to Work Around Them
What a knowledge cutoff is, current cutoff dates for GPT-4o, Claude, Gemini, and Llama, what models cannot know, and 4 practical workarounds for real-time information needs.
LLM Context Window Sizes Compared in 2026: What Fits, What Doesn't, and the Lost-in-the-Middle Problem
Context windows from 128k to 1M tokens compared - what fits in each size, the lost-in-the-middle accuracy problem, and practical guidance for choosing the right model for your context needs.
Prompting for Creative Writing: Getting Less Generic Output
How to escape generic AI writing - using specific stylistic constraints, exclusion lists, tone references, temperature settings, and iterative generate-critique-revise loops to get genuinely distinctive creative output.
Claude 3.5 Sonnet Review: What It Does Better Than GPT-4o (and Where It Falls Short)
An honest, benchmark-driven comparison of Claude 3.5 Sonnet vs GPT-4o covering coding, document analysis, multimodal tasks, pricing, and real-world verdict.
LLM Safety and Alignment Explained for Developers
What alignment means, how RLHF and Constitutional AI shape model behavior, why models still fail, and what application-level guardrails you actually need to build.
