Build & ship software
Plan, implement, test and prepare websites, applications and software changes using AI Prompts and Workflows.
Explore Build & ShipPractical AI resources and tools
Find structured Prompts for individual tasks, follow Workflows for larger jobs, and reuse Skills for repeatable capabilities. Copy them into your preferred AI tool, run supported Prompts and Workflows privately in Workplace, or use Amo.ng Build to create websites and browser tools.
What Amo.ng is
Browse Prompts, Workflows and Skills by the job you need to complete. Each resource explains how to use it, including Workplace where supported. Copying instructions does not execute them.
Amo.ng is free to use, with no subscription or paywall. No Amo.ng account is required for the public library or Workplace. Your AI provider may charge for its own API usage.
Explore Amo.ng Build. Your selected AI provider’s usage charges may apply.
Who it is for
The library provides instructions with practical inputs, constraints, output formats, review points and next actions. Use them for coding, business, research, education and everyday work, and review AI-generated results before relying on them.
Start with one task, a larger job or a method you want to use again.
A structured set of instructions for completing one task with an AI tool.
A step-by-step sequence for completing a larger job, with inputs, review points and handoffs between steps.
Reusable instructions for applying a focused capability repeatedly. A Skill is based on an Amo.ng Prompt or Workflow and does not run automatically.
From idea to outcome
Choose the stage that matches what you need.
Find structured Prompts, guided Workflows and reusable Skills for practical work.
Browse Amo.ngWorkplace is a private workspace for running supported Prompts and Workflows with your own AI provider.
Open WorkplaceAmo.ng Build is an AI-assisted builder for creating supported websites and browser tools from an idea or compatible Amo.ng Prompt, using your own AI provider.
Explore Amo.ng BuildStart with an outcome
Choose the result you need, then explore Prompts and Workflows that guide you from inputs to a practical outcome.
Plan, implement, test and prepare websites, applications and software changes using AI Prompts and Workflows.
Explore Build & ShipTurn repetitive work into a reliable process with controls and recovery steps.
Explore AutomationTurn datasets, spreadsheets and metrics into trustworthy findings and decisions.
Explore Data AnalysisCreate clearer priorities, handoffs, documentation and follow-through.
Explore Productivity & WorkflowsDevelop evidence-based marketing, content and growth execution.
Explore Marketing & GrowthDiagnose, correct, test and safely release changes to an existing codebase.
Explore Laravel & Software EngineeringFeatured resource pack
Prompts, Workflows, Skills, templates and synthetic cases for using AI in internal audit and reviewing AI-enabled systems.
Supporting free access to Amo.ng
Explore practical AI tools.
Get started with ChatGPT.
Follow step-by-step guides with review points for larger AI-assisted tasks.
Use this for coordinating a source-backed close review across data, reconciliations, entries, reporting ties and unresolved matters before a controller decides.
Use this for building a reviewed planning package from authorised actuals and operational drivers, with manual model construction, assumption challenge, cash review and human approval.
Develop a research question and interview protocol, pause for authorised fieldwork and human analysis, then challenge interpretations and compare evidence-bounded positioning options.
Reuse focused methods based on Amo.ng Prompts and Workflows.
Create a defensible evidence-screening and extraction protocol for systematic, scoping, or living reviews, including eligibility rules, deduplication, reviewer decisions, appraisal, and flow reporting.
Assess evidence for paid-media creative fatigue against audience saturation, delivery changes and other confounders, then propose controlled refresh tests without treating descriptive patterns as causal proof.
Diagnose intermittent CI or local test failures, identify the supported nondeterministic cause, and define a cause-specific stabilization plan with reliability evidence instead of hiding product defects.
Prompts for debugging, refactoring, building features, reviewing security, improving performance, and guiding Codex through safe code changes.
View categoryPrompts for strategy, pricing, operations, decision-making, planning, and business execution.
View categoryPrompts for content strategy, topical authority, SEO briefs, internal linking, content refreshes, and search intent analysis.
View categoryPrompts for positioning offers, planning campaigns, refining landing pages, understanding objections, and improving conversion paths.
View categoryPrompts for building content calendars, repurposing long-form ideas, writing hooks, managing community replies, and publishing authority content.
View categoryPrompts for mapping workflows, designing no-code automations, debugging webhooks, and building AI-powered operations systems.
View categoryPrompts for lesson planning, tutoring, curriculum design, rubric creation, assessment, and diagnosing student misconceptions.
View categoryPrompts for literature reviews, source checks, interview planning, research questions, evidence tables, and synthesis workflows.
View categoryPrompts for weekly planning, deep work, decision triage, meeting follow-through, and personal knowledge systems.
View categoryPrompts for resumes, interviews, negotiation, career transitions, portfolios, and professional storytelling.
View categoryPrompts for auditing datasets, planning SQL analysis, defining dashboards, reviewing experiments, and checking causal assumptions.
View categoryPrompts for designing, testing, improving, and hardening reusable prompt systems.
View categoryPrompts people are viewing and copying most across Amo.ng.
Use Codex to reproduce a frontend state defect, trace its causal state transition, implement an authorized minimal patch, and produce evidence-backed regression verification.
A Codex coding prompt for proposing and, when authorized, implementing one metadata-driven static site system that serves distinct sale, ecosystem, active-destination, and fallback pages by hostname. It includes Cloudflare Workers controls, domain-inventory reconciliation, SEO checks, active-domain safeguards, and evidence-based reporting without assuming deployment or provider access.
Reconcile actuals, budget, and forecast; explain operating and accounting drivers; test cash runway scenarios; and produce evidence-linked actions, review gates, and executive decisions.
Turn customer feedback, product behavior, commercial signals, and delivery constraints into a traceable roadmap recommendation with explicit decision gates and verification evidence.
Map a manual business process, evaluate AI and deterministic automation opportunities, define human controls, and produce an evidence-linked implementation and validation plan.
Design an implementation-ready RAG architecture with governed retrieval, citations, tool boundaries, safety controls, evaluation tests, rollout gates, and evidence-based acceptance criteria.
Codebase-ready prompts for debugging, refactoring, deployment safety, testing, and production workflows.
Reproduce Next.js hydration failures, isolate server-client divergence, repair the smallest responsible boundary, and verify rendering across affected routes and environments.
Assess a FastAPI service for secure deployment, validated API boundaries, resilient workers, dependency safety, observability, operational ownership, rollback readiness, and evidence-based release approval.
Investigate a PostgreSQL query using plans, runtime statistics, locks, indexes, data shape, cache conditions, and controlled experiments before recommending a safe optimization.
Assess a Terraform plan’s real blast radius across resources, state, dependencies, services, and data before an authorized apply decision.
Diagnose failed Kubernetes rollouts, isolate the failing layer, choose a controlled recovery path, and verify service restoration using supplied evidence.
Reproduce intermittent test failures, isolate nondeterministic causes, implement a cause-specific fix, and measure reliability without hiding product defects.
Deep prompts for advanced AI users, builders, and teams working on serious workflows.
Design a governed prompt library for a department, including use-case mapping, prompt templates, naming rules, ownership, testing, version control, training, rollout, and maintenance practices.
Create a practical SOP for responsible team AI use, covering allowed use cases, restricted data, review rules, approval roles, escalation paths, and update cadence.
Design human review gates for AI-assisted workflows with quality criteria, escalation rules, reviewer rubrics, audit evidence, and risk-based approval paths.
Build an auditable AI workflow ROI measurement plan that reconciles baseline and pilot evidence, calculates net value, tests quality and risk guardrails, and supports a keep, improve, scale, pause, stop, or retest decision.
Create an evidence-traceable sensitive data handling checklist for an AI workflow, including data classification, minimization, tool and storage verification, approval gates, escalation paths, incident readiness, and acceptance criteria.
Convert pilot and operating evidence into a defensible decision on whether one AI initiative should scale, hold, redesign, or stop.
Practical prompts for planning, research, education, marketing, productivity, and business execution.
Use this for reviewing a prepared account reconciliation, supporting evidence and unresolved differences before an authorised accountant decides what can be cleared or requires further action.
Review an audit finding, management response or closure claim for evidence linkage, response coherence, unresolved matters and support for any proposed reporting or closure decision.
Challenge a proposed audit sampling and control-test design for population coverage, selection logic, evidence requirements, exception handling and defensible inference before testing begins.
Review a supplied internal audit engagement plan for evidence coverage, scope gaps, assumptions, access constraints and feasibility before the approach is accepted.
Validate international URL targeting, reciprocal hreflang clusters, locale codes, canonicals, redirects, indexability, sitemaps, templates, and rendered output using crawl evidence and post-release acceptance tests.
Diagnose paid-media creative fatigue by combining visual and video evidence, concept similarity, audience exposure, delivery patterns, outcome trends, confounders, and controlled refresh experiments.
Recently published prompts from across the Amo.ng library.
Use this for challenging an organisational capital-expenditure business case, its incremental cash flows, assumptions and financial appraisal before an authorised decision-maker approves funding.
Use this for reviewing whether product, service or customer margin movements reflect underlying economics, cost-allocation choices, classification changes or data defects.
Use this for reviewing a prepared financial-statement package against approved balances, supporting schedules and supplied policy or disclosure requirements before authorised professional review.
Use this for challenging the support, calculation and uncertainty behind a proposed journal, accrual or estimate before human accounting approval.
Use this for reviewing a prepared account reconciliation, supporting evidence and unresolved differences before an authorised accountant decides what can be cleared or requires further action.
Challenge a paid-media plan or proposed budget change using comparable performance, measurement and commercial evidence while keeping attribution, causality and spending decisions properly bounded.
Review the evidence supporting a proposed marketing audience use, including its source, purpose, destination, permissions, restrictions and suppression status, before a human activation decision is made.
Review an audit finding, management response or closure claim for evidence linkage, response coherence, unresolved matters and support for any proposed reporting or closure decision.
Challenge a proposed audit sampling and control-test design for population coverage, selection logic, evidence requirements, exception handling and defensible inference before testing begins.
Powered by RichlyAI
Learn how to apply AI prompts, automation, and AI workflows through RichlyAI Learn, or use AI tools directly on RichlyAI Hub.
RichlyAI ecosystem
Discover AI tools, practical AI learning, expert articles, and the RichlyAI Hub experience.
RichlyAI Hub
Use RichlyAI's AI tools and productivity features for everyday work, writing, research, and business tasks.
Visit hub
RichlyAI Blog
Read practical AI guides, tool reviews, prompt ideas, business insights, and productivity articles.
Read articles
AI Tools Directory
Explore a growing directory of AI tools for writing, design, coding, marketing, research, automation, and business.
Explore tools
RichlyAI Learn
Learn practical AI skills through self-paced courses, AI Tutor support, hands-on tasks, assessments, and certificates.
Start learning