Cost & PricingContext Window Cost Tradeoffs: Bigger Is Not Free
A million-token window changes what you can do and what you will pay. Here is the arithmetic for filling one, and when retrieval beats stuffing on cost.
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.
Cost & Pricing
FundamentalsContext Windows: Why More Is Not Always Better
A million-token context window sounds like the end of chunking. In practice models get slower, pricier and less accurate long before you fill it. Here is why.
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GuidesContinue.dev Setup: config.yaml for a Custom Endpoint
Point Continue at any OpenAI-compatible base URL using config.yaml — model roles, apiBase, request options, and why the autocomplete slot needs its own model.
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Cost & PricingCost Per Pull Request: A Unit Metric Worth Tracking
Total AI spend tells you nothing actionable. Cost per merged pull request ties inference to delivered work and exposes exactly where the money goes.
ReadCost & PricingCutting Token Usage Without Making Answers Worse
Most prompts carry substantial waste. Nine techniques that reduce spend while usually improving output quality, ordered by how much they actually save.
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GuidesDebugging LLM API Errors, Status Code by Status Code
A field guide to the errors an LLM API actually returns: what each status means, which ones are worth retrying, and how to reproduce the failure in one curl command.
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ModelsDeepSeek V4 Pro: Frontier Reasoning at Commodity Prices
A 1.6T MoE that activates 49B per token, ships under MIT, and costs $0.435 per million input tokens. Where V4 Pro is strong, where it is not, and Pro versus Flash.
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FundamentalsEmbeddings Explained: Vectors, Similarity and Where It Breaks
Embeddings turn text into vectors so you can search by meaning instead of keywords. Here is how they work, what similarity really measures, and the failure modes to expect.
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AI AgentsEvaluating Agent Reliability: Past the Single Pass Rate
An agent that works four times in five is not 80 percent useful. Here is how to measure agent reliability in a way that predicts production behaviour.
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FundamentalsFine-Tuning vs Prompting vs RAG: How to Adapt a Model
Three ways to make a general model do your specific job, with very different costs. Here is a decision rule based on what each one can and cannot actually change.
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Cost & PricingForecasting AI Spend Without Guessing
Most AI budget forecasts are a headcount multiplied by a hopeful number. Here is a model that decomposes spend into drivers you can actually measure and control.
ReadCost & PricingFree AI API Tiers: How to Compare Limits That Keep Moving
Free tier numbers rot within weeks, and several vendors have stopped publishing them entirely. Here is a method for comparing them that survives the churn.
ReadShowing 649–660 of 731 articles