GuidesGenerating Commit Messages That Are Actually Useful
A diff shows what changed, never why. Where generation genuinely helps, a working prepare-commit-msg hook, and the Conventional Commits rules a model gets wrong.
ReadNotes on models, agents, and what inference costs
Practical writing for developers building with large language models — how they work, how to pick one, and how to keep the bill predictable.
Guides
GuidesGenerating Documentation With LLMs That Is Worth Reading
Most generated docs restate the function signature in English. What to generate instead, which formats tools can actually consume, and how to stop docs drifting from code.
Read
GuidesGenerating SQL Safely: Least Privilege Beats Better Prompts
Text-to-SQL fails two ways: destructive queries and quietly wrong answers. Read-only roles and timeouts handle the first. The second needs a different kind of guardrail.
ReadGuidesGenerating Tests With LLMs: Coverage Is Not the Goal
Models are very good at writing tests that pass and prove nothing. How to get suites that actually catch regressions, and how mutation testing tells you which ones do.
Read
ModelsGLM-5.1 vs GLM-5.2: Same Size, Same Price, Different Job
Z.ai kept the architecture and the price list identical and changed what the model is for. The context jump, the long-horizon gains, and the token cost nobody mentions.
Read
ModelsGLM-5.2 vs DeepSeek V4 Pro: Endurance or Raw Problem Solving
Both are MIT-licensed open models, so the licence is a wash. The split is agentic endurance against algorithmic power, at a three-to-five times price gap.
Read
ModelsGLM-5.2: The Open Model Built for Long-Horizon Coding
Z.ai shipped a 744B MoE with 40B active, MIT-licensed weights and the first open-weight Terminal-Bench 2.1 score above 80. A technical read on what that means.
Read
FundamentalsHow LLMs Actually Work: Next-Token Prediction, End to End
A large language model does one thing repeatedly. Here is what happens between your prompt and the first token out, and what that mechanism explains about behaviour.
ReadModelsHow to Choose a Coding Model Without Trusting Anyone’s Chart
Six properties decide whether a model is good at your codebase — and only one of them shows up on a leaderboard. A practical framework for picking.
Read
AI AgentsHuman in the Loop: Designing Approval That Actually Works
Most approval gates fail not from too little oversight but from too much. Here is how to design agent checkpoints people actually read before clicking yes.
ReadCost & PricingInput vs Output Token Pricing: Which One Actually Bills You
Output tokens cost several times more per token, yet input usually dominates the bill. Here is how to compute your own blended rate and act on it.
Read
Cost & PricingIs Unlimited AI Actually Unlimited?
No inference provider can sell genuinely uncapped compute. Here is what the word hides, why the limits exist, and exactly what to demand in writing before you buy.
ReadShowing 661–672 of 731 articles