GuidesExponential Backoff That Works on LLM APIs
The retry algorithm in detail: full versus decorrelated jitter, deadline propagation, idempotency, what to classify as retryable, and how to test it before production does.
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
ModelsFallback Model Selection: Choosing Your Second Model Well
A fallback that behaves nothing like your primary turns an outage into a quality incident. How to pick a second model and prove it works.
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GuidesFew-Shot Example Management: Curation Beats Quantity
Few-shot examples decay, contradict each other and leak into output. How to choose them, order them, keep them in sync with your schema and know when to drop them.
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Cost & PricingFinOps for AI Teams: What Transfers From Cloud and What Does Not
Cloud FinOps practice mostly transfers to LLM spend, but rightsizing and reserved capacity do not. What to keep, what to drop, and what to instrument first.
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FundamentalsFlash Attention Explained: Same Maths, Far Less Memory
Flash attention makes long context practical by never writing the score matrix to memory. What it changes, what it does not, and where you feel the difference.
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Cost & PricingForecasting Next Quarter's AI Spend as a Range
Why extrapolating token usage gives the wrong number, which drivers actually move an AI bill, and how to build a defensible range instead of a point estimate.
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Cost & PricingFree Tier Strategies: Getting Real Answers Without Paying
Free tiers are evaluation budgets, not production capacity. What they are for, where the limits bite, and how to fit a real model evaluation inside one.
ReadGuidesFunction Calling in Python: A Working Implementation
Build a tool-calling loop in Python that survives real inputs: schema generation, argument validation, parallel calls, error returns and the termination condition.
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GuidesFunction Calling in TypeScript Without Losing Type Safety
A typed tool-calling loop in TypeScript: Zod schemas, a discriminated tool registry, safe argument parsing, streaming assembly and AbortController cancellation.
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ModelsGDPval Explained: Benchmarking Real Professional Work
GDPval scores models on deliverables from real occupations, graded by experts. What that measures, why it is not a coding benchmark, and how to read it.
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GuidesGenerating API Clients With an LLM Without Silent Drift
Where a model beats openapi-generator, where it quietly loses, and how to build a generate-compile-test loop that catches the hallucinated field before you ship it.
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GuidesGenerating Regular Expressions With an LLM, Carefully
Models write regex fluently and confidently, which is the problem. How to specify the target, demand test cases, avoid catastrophic backtracking and spot dialect mismatches.
ReadShowing 445–456 of 731 articles