GuidesCursor Setup Guide: Pointing It at Your Own Endpoint
How to run Cursor against a custom OpenAI-compatible base URL, which features stop using your key, and how to tell whether the override took effect.
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.
Hands-on setup for the tools developers actually use.
GuidesGuidesEmacs LLM Setup: A Model Endpoint Without the Mouse
Wire an OpenAI-compatible endpoint into Emacs — package choices, auth-source instead of hardcoded keys, buffer versus region workflows, streaming and keybindings.
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GuidesEvaluating Prompt Changes Without Fooling Yourself
You edited a prompt and the output looks better. Here is how to find out whether it actually is, with paired runs, enough samples and judges you can trust.
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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.
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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.
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.
ReadGuidesGenerating 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.
ReadGuidesGitHub Actions LLM Setup: A Workflow That Reviews PRs
A working GitHub Actions job that calls an OpenAI-compatible model on pull requests — repository secrets, timeouts, rate limits, PR comments and cost control.
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GuidesGitLab CI LLM Setup: Masked Variables and MR-Only Jobs
A GitLab CI job that calls an OpenAI-compatible model on merge requests — masked variables, rules, artifacts versus MR notes, runner choice and cost control.
ReadGuidesGoose Setup Guide: Providers, Extensions and Safe Defaults
Configure Goose against a custom OpenAI-compatible endpoint, understand what its extensions cost you per request, and set approvals you can live with.
ReadShowing 13–24 of 77 articles