hiro.solutions

A practical RAG tutorial covering ingestion, chunking, retrieval, citations, evaluation, failure handling, and ongoing maintenance.

A practical RAG tutorial covering ingestion, chunking, retrieval, prompts, citations, evaluation, monitoring, and recurring reliability reviews.

A reusable guide to benchmark LLM latency across chat, extraction, and tool-calling workflows with metrics, templates, and update triggers.

A reusable pre-launch checklist for reviewing prompts, safety, evaluation, fallbacks, and observability before shipping an AI feature.

A reusable guide to track AI cost per prompt, user, and workflow so teams can monitor token spend and optimize with confidence.

A practical guide to adding LLM guardrails that reduce risk without blocking legitimate, useful output.

A practical comparison of RAG chunking strategies, including size, overlap, and structure trade-offs for more reliable retrieval.

A practical framework for comparing prompt management tools by versioning, collaboration, evaluation, and production fit.

A reusable guide to writing portable prompts that behave more consistently across OpenAI, Anthropic, and Gemini-style models.

A practical framework for reducing LLM hallucinations with stronger prompts, retrieval, validation, and safe fallback behavior.

A practical guide to budgeting tokens, trimming noise, and structuring prompts so LLM context stays useful as models and limits change.

A workflow-focused guide to SQL formatting conventions, tools, and review habits that make debugging and code review easier.

A practical workflow for previewing and checking Markdown in README files, docs, and AI-generated drafts before publishing.

A practical Base64 encoder decoder guide for API payloads, files, and debugging, with common pitfalls and repeatable quality checks.

A practical JWT decoder guide for safely inspecting tokens, explaining payload claims, and debugging common authentication failures.

A practical regex tester guide with reusable patterns, testing advice, and a maintenance checklist developers can revisit regularly.

A practical guide to when to use a JSON formatter, validator, or linter in real development workflows.

A reusable checklist for diagnosing inconsistent LLM output across prompts, models, settings, context, and app logic.

A reusable classification prompt guide for sentiment, intent, and support triage with templates, examples, and update advice.

A practical guide to selecting AI evaluation metrics for quality, safety, reliability, latency, and cost in production LLM systems.