HTML Sitemap

Definition and scope

The HTML sitemap lists every public editorial page by cluster. It complements the XML sitemap for crawlers, JSON page index for machines, and RSS feeds for subscribers. All links are ordinary HTML and work without client-side JavaScript.

A complete route directory is a useful accessibility and discovery fallback for a large editorial architecture.

Why the distinction matters

The index organizes ordinary links so readers and crawlers can discover the full cluster without a scripted interface.

For list every route, the decisive question is what information the system can use, what role it performs, how long the context remains relevant, and what the player can inspect or control.

How to apply the idea

Browse by cluster or use the machine-readable resources in the footer for automated discovery.

Start with the smallest useful context. Name the relevant game, run, character, or interaction horizon; distinguish verified facts from player statements and model inference; then link the result to a visible source or restore point when it must remain durable.

Identify the primary player need.
Choose the companion type or comparison level.
Define inputs, authority, retention, and deletion.
Test the likely failure mode, not only the ideal response.

Boundaries and caveats

Generated service endpoints and the 404 page are intentionally excluded from the editorial list.

Product labels are not enough evidence. Current features, privacy behavior, platform access, and compatibility should be checked in official documentation. A fluent response can still contain an incorrect fact, stale state, or a plausible merge of two different runs.

A practical evaluation model

Evaluate a companion across five dimensions: context input, system role, action authority, time horizon, and player control. Add source quality and privacy when the system uses external knowledge or stores durable state.

This model keeps interface features in perspective. Voice, screen capture, an avatar, and a dedicated app can improve a particular implementation, but none of them defines the entire AI gaming companion category.

Browse the library

Definitions

What Is an AI Gaming Companion?An AI gaming companion is an AI system that supports a player through one or more forms of gaming context, including guidance, interaction, memory, continuity, collaboration, or restoration across play sessions. The category includes coaching, in-game, agentic, social, and continuity companions.
What Are the Five Types of AI Gaming Companion?The five primary types are coaching companions, in-game companions, agentic companions, social companions, and continuity companions. They differ in whether they advise, inhabit the game world, act, create social presence, or preserve context. A system may combine types, but one function is usually dominant.
How Did AI Gaming Companions Develop?AI gaming companions developed through several overlapping lineages: external game help, adaptive in-game characters, autonomous game-playing agents, conversational social systems, and general AI assistants. The label arrived after many of the component ideas. No single product architecture can therefore stand in for the whole category.
AI Gaming Companion GlossaryThis glossary defines the central terms used to describe AI gaming companions and continuity systems. Each entry is intentionally concise, connected to a canonical explainer, and written to separate category language from product claims. The definitions form a working editorial vocabulary rather than an external standard.
AI Gaming Companion Definitions and TerminologyThis terminology set defines the AI gaming companion category from the broadest technical terms to its five types and continuity concepts. Definitions are descriptive: they explain observable system roles and interfaces. They do not certify products or claim that every developer uses the same vocabulary.
AI Gaming Companion Frequently Asked QuestionsAn AI gaming companion can coach, interact, act, create social presence, or preserve gaming context. It does not always need screen access, voice, an avatar, or a place inside the game. The right architecture depends on the player’s goal and the data the system can access.

Continuity

What Is Gaming Continuity?Gaming continuity is the preservation of meaningful player context so the correct gaming thread can be resumed later. That context may include a game, run, character, location, decisions, objectives, relationships, questions, and narrative state. Continuity is about recovering relevance, not recording everything.
What Is a Gaming Restore Point?A gaming restore point is a named or otherwise addressable record of meaningful game-related state. It gives a later conversation enough context to recover the correct game, run, character, decisions, progress, and open questions without forcing the player to reconstruct the entire journey.
What Is a Conversational Save State?A conversational save state is a structured, intentional record of context created inside or for a conversation. In gaming, it can preserve the player’s current run, character, decisions, progress, goals, questions, and narrative situation so those details can be restored in a later chat.
How Does Cross-Chat Gaming Memory Work?Cross-chat gaming memory makes game-related context available outside the conversation in which it was first expressed. It may rely on general platform memory, an application record, or an explicit save state. Reliable gaming continuity needs identity, scope, provenance, and a way to correct stale information.
What Is Cross-Game Gaming Continuity?Cross-game gaming continuity is a model that preserves context for more than one game while keeping each game, run, character, and goal distinct. It supports gaming as a continuing part of life rather than treating every title as an isolated app session.
How Should AI Separate Multiple Games and Runs?An AI companion should separate multiple games and runs with explicit identifiers and scopes. A useful hierarchy is player, game, run or campaign, character or party, restore point, and timestamp. The system should ask before merging records that could refer to different playthroughs.
General AI Memory vs Game Save StateGeneral AI memory usually keeps useful context for personalization and future conversations. A game save state is intentionally captured, scoped, and addressable. Memory may recall that someone enjoys an RPG; save state should restore the correct character, run, decisions, progress, and unresolved goals.
What Is a Continuity Companion?A continuity companion is an AI system that preserves meaningful gaming context and restores the correct thread across sessions, chats, games, devices, characters, or separate runs. Its defining action is not watching the current moment; it is helping the player return to a meaningful journey later.
What Is Companion Play?Companion Play is a continuity-companion implementation created by Raynor Eissens. It treats saving meaningful gaming state as an action within an existing LLM conversation, creating an addressable restore point for a later conversation. It is one implementation of the wider continuity-companion concept.
Intentional Memory vs Associative MemoryIntentional memory is created or confirmed for a specific future purpose. Associative memory is recalled because a system judges it relevant to the current context. Gaming continuity benefits from both, but changing run-specific state needs explicit scope and addressability to avoid collisions.
Why Save Slots Still Matter in the LLM EraSave slots still matter because language models can hold or retrieve several plausible versions of a player’s gaming context. A visible slot distinguishes games, runs, characters, campaigns, and moments. It gives the player a stable handle for selecting the intended state instead of relying on similarity alone.

Comparisons

AI Game Companion vs AI Gaming CompanionAI game companion and AI gaming companion usually refer to the same broad category. “AI game companion” emphasizes a system related to a game, while “AI gaming companion” emphasizes the activity and wider practice of gaming. Neither phrase should be restricted to screen-reading coaches.
Coaching Companion vs Continuity CompanionA coaching companion observes or receives current-session context and offers advice, analysis, or commentary. A continuity companion preserves meaningful context and restores it later. One optimizes the present moment; the other protects the thread across time. A system can combine both functions.
AI Gaming Companion vs ChatGPTAn AI gaming companion is a functional category; ChatGPT is a general AI assistant and product. A player may use ChatGPT as a coaching, conversational, or continuity companion, depending on available features and context. The terms are not competitors at the same level of classification.
AI Gaming Companion vs Game WikiA game wiki is a reference collection organized around published knowledge. An AI gaming companion interprets context and responds, interacts, acts, or preserves continuity. A companion may use verified reference material, but conversational delivery does not make uncertain information authoritative.
AI Gaming Companion vs AI NPCAn AI NPC is a non-player character whose behavior or conversation uses AI inside a game. It can be an in-game or social companion, but the wider AI gaming companion category also includes external coaches, agents, and continuity systems. Location inside the game is the key distinction.
AI Gaming Companion vs AI CompanionAn AI companion can support many areas of life through assistance, interaction, or social presence. An AI gaming companion is specifically organized around gaming context. It may still participate in ordinary conversation, but its category identity comes from how it supports play, player state, or gaming continuity.
AI Gaming Companion vs Gaming AssistantA gaming assistant is primarily framed around utility: answering, configuring, finding, or optimizing. An AI gaming companion may perform those tasks but can also interact as a character, participate as an agent, create social presence, or preserve continuity. The terms overlap most in coaching systems.
Companion Play vs Screen CoachingScreen coaching uses live or recent gameplay context to provide immediate help, analysis, or commentary. Companion Play is a continuity implementation that saves meaningful gaming state for later restoration in an LLM conversation. The two patterns differ in data source, time horizon, and player action.
Companion Play vs General AI MemoryGeneral AI memory aims to retain useful context for future personalization. Companion Play is a gaming continuity pattern centered on an explicit save action and an addressable restore point. It complements general memory by giving changing game-specific state a visible scope and future purpose.
Real-Time Help vs Long-Term Game ContinuityReal-time help answers what the player needs now: a hint, warning, tactic, or explanation. Long-term continuity answers what the player needs after time has passed: the correct run, decisions, goals, relationships, and unfinished questions. A complete companion system may support both horizons.
Game-Specific Companion vs Cross-Game CompanionA game-specific companion is designed around one title’s mechanics, world, characters, or interfaces. A cross-game companion supports context across several games and may preserve the player’s wider backlog, preferences, runs, and comparisons. Depth and breadth create different design tradeoffs.

Research

Why Life Is the Session“Life is the session” describes an interaction model where gaming is one meaningful thread inside ordinary conversation and daily activity. The player does not need to open a dedicated companion destination for every interaction. A save action can mark important state, and a later conversation can restore it.
The Limits of App-First Game CompanionsAn app-first companion organizes interaction around the product’s session: open the app, select a function, formulate a prompt, receive help, and leave. That model works for discrete tasks, but it can fragment context when gaming is one thread among many conversations, devices, games, and periods of life.
Gaming as a Slice of LifeGaming is often a slice of life: a story remembered during a commute, a co-op plan discussed between sessions, a backlog decision, or a character revisited after months. Companion systems can support this wider context without turning every ordinary conversation into a game interface.
The Save Point as an AI InterfaceThe save point can function as an AI interface: the player deliberately marks context worth preserving, reviews a concise state record, names its scope, and restores it later. The metaphor turns invisible memory behavior into a legible action without requiring the AI conversation to imitate a game menu.
From Prompts to ContinuityPrompt-first interaction asks the player to reconstruct a need each time. Continuity-first interaction restores the relevant game, run, character, decisions, and goals before the next request is interpreted. Prompts still matter, but they no longer carry the full burden of rebuilding prior context.
The Future of LLM Gaming CompanionsLLM gaming companions are likely to develop along several paths rather than converge on one product shape. Multimodal coaches may improve immediate help; in-game characters and agents may participate more directly; continuity layers may preserve player context across increasingly ambient interfaces. Each path creates different safety and control requirements.
Why Gaming Does Not Require a Relationship BotGaming support does not require a simulated romantic or emotionally dependent relationship. A companion can be functional: it can coach, participate, preserve state, or restore continuity without asking the player to maintain a persona-centered bond. Social companions remain one type, not the definition of the category.
Why Companion Does Not Have to Mean RomanceA companion is something or someone that accompanies a person in a context. In gaming, that role can involve advice, in-world collaboration, direct action, social presence, or continuity. Romance is one possible social framing, not a technical requirement or default category meaning.
From Public Performance to Private ContinuityMany gaming technologies are easy to demonstrate through visible performance: a live voice, animated character, or dramatic intervention. Continuity is quieter. Its value often appears later, when a player privately restores the correct thread after an interruption and continues without reconstructing the past.
The Player Journey as StateThe player journey is a form of state. It includes objective facts such as progress and inventory, but also decisions, intentions, interpretations, relationships, play style, unresolved questions, and the meaning the player attaches to events. Continuity systems should preserve what will matter at return.
When Gaming Hardware Becomes AmbientAs conversational hardware becomes more available across rooms and devices, gaming support can become ambient: accessible when relevant without occupying the foreground. Continuity matters because the interface may change while the player’s game, run, decisions, and questions remain the same.
Why Specialized Save State Survives General AI MemorySpecialized save state remains useful even as general AI memory improves because gaming contains many changing, parallel, and versioned truths. A player can have several valid characters, runs, campaigns, and goals. Explicit state gives those truths stable boundaries and makes restoration a deliberate action.

Use cases

How Can an AI Companion Remember a Long RPG?For a long RPG, an AI companion can preserve a structured restore point containing the game and run, character build, current location, important decisions, active goals, relationships, unresolved questions, and the player’s intended next step. The player should review and update the record at meaningful milestones.
How Can AI Manage Multiple Game Characters?An AI companion can manage multiple characters by assigning each one a stable identity within a specific game and run. Each record should keep build choices, role-play intent, equipment priorities, relationships, open objectives, and the most recent restore point separate from every other character.
How Can an AI Companion Help You Return After Months Away?After months away, an AI companion can restore a concise snapshot of the correct run: where the player is, what happened, which decisions mattered, what remains unresolved, and what the player intended to do next. It can then separate confirmed state from details that need checking.
How Can an AI Companion Separate Multiple Runs?An AI companion can separate multiple runs with explicit run labels, creation dates, character or party identities, goals, decision histories, and independent restore points. It should show which run is active before using run-specific context and never merge states merely because they share the same game.
How Can You Continue a Game in a New AI Chat?To continue in a new chat, restore a named conversational save state containing the relevant game, run, player choices, progress, current goals, and unresolved questions. The new chat should show the restored summary and let the player correct it before the conversation relies on that context.
How Can an AI Companion Support Play Across Devices?An AI companion can support play across devices by storing a portable, account-scoped representation of the gaming thread rather than tying continuity to one screen or chat. The restored state should identify its source, last update, active run, and any device-specific limitations.
How Can AI Preserve Game Talk During Daily Life?A gaming thought can occur during ordinary life: a build idea, story interpretation, co-op plan, or remembered objective. A continuity companion can save that thought to the correct game and run without turning the rest of the conversation into a gaming session, then restore it when the player returns.
How Can AI Preserve Player Decisions?An AI companion can preserve player decisions by recording what was chosen, when, in which game and run, what the player knew, and why the choice mattered. Later restoration should distinguish the player’s stated rationale from inferred consequences and from outcomes that have been verified.
How Can AI Restore a Co-op Campaign?A co-op campaign restore point can preserve the game, group, player roles, shared decisions, current objective, schedule, unresolved questions, and the person authorized to update each part. The system should distinguish shared campaign state from private notes and individual character state.
How Can AI Keep a Useful Game Backlog Conversation?An AI companion can keep a backlog conversation by preserving why each game matters, current interest, platform, time constraints, co-op dependencies, and the next decision. The goal is to restore context for choosing or discussing games, not to maximize completion or create another obligation.

Types

What Is a Coaching companion?An AI system that observes or receives information about current play and provides hints, analysis, strategy, or commentary.
What Is a In-game companion?An AI character that exists within a game as an NPC, party member, teammate, or conversational presence.
What Is a Agentic companion?An AI system that can perform actions, follow commands, control a game entity, or participate directly in gameplay.
What Is a Social companion?An AI system designed to create personality, social presence, friendship, affection, or a relationship around play.
What Is a Continuity companion?An AI system that preserves meaningful gaming context and restores the correct thread across sessions, chats, games, devices, characters, or separate runs.

About and trust

About AI Gaming CompanionAI Gaming Companion is a category publication about the systems that guide, interact with, act for, socialize with, or preserve continuity for players. It is operated by Raynor Eissens, creator of Companion Play, and separates broader category analysis from discussion of that implementation.
Raynor Eissens — Author and Project ArchitectRaynor Eissens is the creator of Companion Play, author and project architect of AI Gaming Companion, and the publication operator. His work here focuses on gaming continuity, LLM-native interfaces, conversational save state, and a broader category model for AI gaming companions.
Editorial PolicyThe editorial policy requires clear definitions, observable distinctions, primary sources for current product claims, dated updates, visible disclosures, and corrections when material errors are found. It prohibits fabricated citations, fake reviews, unsupported leadership claims, copied competitor language, and paid conclusions presented as independent analysis.
Methodology for the AI Gaming Companion TaxonomyDefinitions are based on observable product architectures and conceptual distinctions: what context a system receives, what role it performs, whether it can act, where it exists, how long context remains useful, and what control the player retains. Screen coaching is treated as one subtype, not the category boundary.
Corrections PolicyReaders can report a factual, definitional, metadata, accessibility, or link error through the contact route. Confirmed material errors are corrected in the page, the updated date is changed, and a concise note is added when the correction alters the meaning of a claim or definition.
Disclosure and Product RelationshipAI Gaming Companion, AI Game Companion, and Companion Play share a creator, Raynor Eissens. Companion Play is a continuity-companion implementation and is used as a concrete example. The publication distinguishes the broader category from that product and does not present the relationship as full editorial independence.
Contact AI Gaming CompanionUse the published contact channel for corrections, source updates, accessibility problems, taxonomy feedback, and editorial enquiries. Include the affected URL and enough context to review the request. Do not send passwords, private game account data, unpublished personal information, or sensitive save-state content.
Privacy PolicyThe initial publication is a read-only website that does not require an account, accept public form submissions, or set application cookies. Optional analytics can be configured by the operator through an environment variable and must be documented here before activation. Hosting providers may process standard request logs.
Terms of UseThis site provides general informational and editorial material, not game support, legal advice, platform guarantees, or a promise of product compatibility. Readers should verify current product features and game facts with primary sources. Third-party names remain the property of their respective owners.

Indexes

AI Gaming Companion Article ArchiveThe article archive collects every public editorial route by topic. Use the cluster indexes for focused reading or the HTML sitemap for a complete route list. Machine-readable article metadata is available from the public data endpoint and RSS feeds.
Definitions and Category FoundationsThe definitions cluster establishes what an AI gaming companion is, the five primary types, how the category developed, and which terms should remain distinct. Start here when a product label or search query uses companion, assistant, coach, NPC, agent, or memory ambiguously.
The Five AI Gaming Companion TypesThe type library classifies AI gaming companions by primary role: coaching advises, in-game inhabits, agentic acts, social relates, and continuity preserves. Each type page explains defining traits, examples, exclusions, design questions, and links to relevant comparisons and use cases.
Gaming Continuity LibraryThe continuity library explains how meaningful gaming context can be captured, separated, corrected, and restored across time. It covers the emerging continuity-companion type, intentional save state, general memory, multiple games and runs, conversational restore points, and one disclosed implementation: Companion Play.
AI Gaming Companion Comparison LibraryThe comparison library distinguishes concepts that are often collapsed by product copy or search queries. Each page states the shared ground, the decisive difference, a compact evaluation model, and the limits of the comparison. The goal is architectural clarity rather than declaring a universal winner.
Research and Concept EssaysThe research and concept archive examines interface models that sit behind companion products: session boundaries, save points, public performance, private continuity, player journeys, ambient hardware, relationship framing, and specialized state. These are reasoned editorial essays, not claims of settled academic consensus.
AI Gaming Companion Use CasesThe use-case library translates the category into player situations. Each page identifies the state that matters, a practical continuity workflow, failure modes, privacy boundaries, and links to the relevant companion type and concept pages. The examples do not imply that every current product supports the described workflow.

Frequently asked questions

What is the shortest explanation of “HTML Sitemap”?

Does this require real-time screen access?

Not necessarily. Screen access is an input used by some coaching systems, not a requirement for the wider category.

What should a player or product team verify?

Verify the system’s actual inputs, action authority, source quality, privacy controls, retention, correction path, deletion behavior, and whether its visible product claims match its implementation.