> ## Documentation Index
> Fetch the complete documentation index at: https://invoca-5bd45748-mintlify-6c3474a6.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# AI Experience overview
> Wayfinders, inputs, tuners, governors, trust builders, identifiers, and actions for Invoca's agentic AI surfaces — where every page states its agency tier and how a user catches a wrong answer.
**Exemplar section — first pass, entirely proposal, with one narrow exception.** No pattern
in this section is built as an experience, which means none of them carry code fact or
evaluation data — every statement here is design intent, offered for review, not established
policy. The one exception is [Signal AI](/invoca-design-system/ai-experience/actions/summarize)'s
transcript-summary capability, which is shipped and named — but even there, only its external
API contract is verified; the experience around it (disclosure, outcome states, correction)
is proposal like everything else. See [Coverage, stated honestly](#coverage-stated-honestly).
## What this section governs
Anything in Invoca's product where the output is generated by a model rather than rendered
from state, or where a feature acts on the user's behalf rather than only responding to input.
A [Signal AI](/invoca-design-system/ai-experience/actions/summarize) call summary, a natural-language search over call data, an assistant that
drafts a follow-up or updates a record, a panel that recommends a routing or budget change —
all of it lives here, not in Patterns.
It does not govern the visual materials an AI surface is built from. A summary still renders
in a [Card](/invoca-design-system/components/data-display/card); a streaming answer still
uses [Foundations](/invoca-design-system/foundations/overview) motion and color tokens. This
section governs what is different about the experience once the thing filling those
components is not deterministic.
## Why this isn't a Pattern
The rest of this design language resolves top-down through four tiers — Foundations,
Components, Patterns, Views — and each tier is defined by a test: is it a token, a package
export, a composition with no export, or a page archetype. An AI experience fails all four
tests the way a Pattern would pass them, because four assumptions those tiers depend on do
not hold here:
| A Pattern can assume | An AI experience cannot |
| ------------------------------------------- | ---------------------------------------------------------- |
| The same input produces the same output | Output varies, and sometimes it is wrong |
| Every value is derivable from source | A behavior like "cites its sources" has no emittable value |
| The failure case is one state among several | The failure case **is** the design surface |
| Documented behavior stays true | Model capability moves underneath the page |
So an AI experience page carries every section a Pattern page carries — constraints, content
rules, accessibility, gaps — plus four sections nothing else in this design language has:
**agency tier**, **outcome states**, **disclosure & recourse**, and **evaluation**. Skipping
straight to Components or Patterns for an AI feature means improvising exactly those four.
## Vocabulary
Seven categories, adopted from the public pattern catalogue
[Shape of AI](https://www.shapeof.ai/). The names are taken deliberately: two of the seven —
Governors and Trust builders — exist purely for oversight and correction, which is the right
weighting for a house system and worth keeping as emphasis rather than reinventing.
| Category | Answers | First page |
| ------------------ | --------------------------------------------------------------------- | ------------------------------------------------------------------------------------ |
| **Wayfinders** | How does the user find or start using the AI feature at all? | [Initial CTA](/invoca-design-system/ai-experience/wayfinders/initial-cta) |
| **Inputs** | How does the user tell the AI what they want? | [Open input](/invoca-design-system/ai-experience/inputs/open-input) |
| **Tuners** | How does the user adjust what the AI is doing before or during a run? | [Controls](/invoca-design-system/ai-experience/tuners/controls) |
| **Governors** | How does the user see and check what the AI is doing? | [Stream of thought](/invoca-design-system/ai-experience/governors/stream-of-thought) |
| **Trust builders** | How does the interface admit what it doesn't know? | [Caveat](/invoca-design-system/ai-experience/trust-builders/caveat) |
| **Identifiers** | How does the AI present itself — visually and verbally? | [Avatar](/invoca-design-system/ai-experience/identifiers/avatar) |
| **Actions** | What is the AI actually being asked to do? | [Search](/invoca-design-system/ai-experience/actions/search) |
**Actions is Invoca's own category, not Shape of AI's.** Shape of AI catalogues the
surrounding chrome — how you prompt, watch, and correct a model — and deliberately stops short
of naming the jobs themselves. Invoca's agentic surfaces already do specific jobs today —
[Signal AI](/invoca-design-system/ai-experience/actions/summarize) summarizing a call transcript is shipped, named, and real — so this section
names the seven jobs its agentic features are known or expected to do: search, summarize,
draft, update, disambiguate, recommend, and the welcome/empty state every one of them needs on
day one.
**Identifiers reads differently from the rest of this section.** Avatar, Color,
Iconography, Name, and Personality describe how the AI presents itself, not an interaction —
there is no run to interrupt and no output to be confidently wrong about. Those five pages
use the lighter foundation shape (what it governs, choosing a value, constraints) instead of
the full pattern shape below. Everything else in this section — Wayfinders, Inputs, Tuners,
Governors, Trust builders, Actions — uses the full shape.
## The four sections nothing else in this design language has
### Agency tier
Every interactive page in this section (everything except Identifiers) states, plainly, how
much authority the feature has. Naming the tier is what makes the confirmation-versus-undo
question askable at all.
| Tier | Authority | Requirement |
| ---------------------- | -------------------------- | ----------------------------------------------------- |
| **Suggests** | Proposes; the user acts | Refusable without friction |
| **Drafts** | Produces reviewable output | Obviously a draft; never auto-submits |
| **Acts, reversible** | Does it; the user can undo | Undo is real, discoverable, bounded in time |
| **Acts, irreversible** | Cannot be undone | Explicit confirmation naming the specific consequence |
| **Acts unsupervised** | No per-action review | An audit trail, a kill switch, a stated blast radius |
**Escalating a feature's tier is a decision, never a default.** A feature that starts
suggesting and ends up acting unsupervised has crossed a line that needs recording, the same
way a token change does — see [Constraints](#constraints).
### Outcome states
A component has interaction states — hover, pressed, disabled. An AI experience has outcome
states, and every pattern page in this section carries a treatment for each one that applies:
**working, streaming/partial, confident and right, confident and wrong, uncertain, refused,
empty, interrupted, degraded, rate-limited, stale.**
**Confident and wrong is the primary case to design for**, not the edge case. A wrong answer
delivered with no visible seam is the characteristic failure of this whole section, and every
pattern page states how a user notices and corrects one. "The model is usually right" does not
count as an answer.
Disclosure & recourse
Six questions, on every interactive page, answered or explicitly marked not applicable:
1. Does the user know this is AI, at the moment it matters?
2. What did it use — call data, prior conversation, other records?
3. How sure is it, and does that change what the user should do?
4. How does the user check it?
5. How does the user correct it, and does the correction persist?
6. How does the user get out — reach a person, do it manually, turn it off?
Question 6 is the one most often missing and the one a user wants most when the feature has
already failed them once.
### Evaluation
Nothing in this section is built, so nothing in this section has been evaluated. Every page
says exactly that rather than implying otherwise. Once a pattern ships, its page states the
eval set, the metric and threshold, named failure classes from real output, and the date of
the last run — a capability claim with no evidence behind it is the failure this section
exists to prevent.
## Coverage, stated honestly
| Category | Decided for Invoca? |
| -------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Wayfinders | **No** — proposal only, no shipped surface |
| Inputs | **No** — proposal only, no shipped surface |
| Tuners | **No** — proposal only, no shipped surface |
| Governors | **No** — proposal only, no shipped surface |
| Trust builders | **No** — proposal only, no shipped surface |
| Identifiers | **No** — proposal only; Invoca's agentic features have no stated visual or verbal identity yet |
| Actions | **Partly** — Signal AI's transcript summary is shipped and named; search, draft, update, disambiguate, recommend, and the welcome/empty state are proposals with no shipped surface |
Unlike every other tier in this design language, there is no generated reference layer here
and there will not be one until something ships. A page in this section that looks thinner
than a Pattern page is not missing content — it is missing a product to observe.
## Choosing where to look
Getting a user to try the feature, and to keep going once they're in it.
Letting the user say what they want in their own words.
Adjusting scope, tone, or depth before or during a run.
Showing and checking what the AI is doing.
Admitting what the system doesn't know.
How the AI looks, sounds, and refers to itself.
The seven jobs Invoca's agentic features are known or expected to do.
## Constraints
| ID | Constraint | Rationale |
| --------------- | ------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------- |
| **TITAN-AI-01** | Every interactive page in this section states its agency tier. | Confirmation, undo, and audit requirements all follow from the tier. Without it, each feature improvises its own answer. |
| **TITAN-AI-02** | Every interactive page names how a user notices a confident-but-wrong output. | The failure with no visible seam is the one that costs the most, and it is the one silence hides best. |
| **TITAN-AI-03** | A confidence signal ships only if it changes what the user should do. | A number that reads the same at 82% and 94% is decoration wearing the shape of information. |
| **TITAN-AI-04** | The user learns this is AI at the point of the output, not only in settings or a footer. | Disclosure that requires the user to already suspect something is not disclosure. |
| **TITAN-AI-05** | A capability claim on any page in this section names how it was established, or states plainly that it hasn't been. | "It works well" with no eval set behind it is a hope, not documentation, and it is indistinguishable from a claim that was checked. |
## Gaps
* **No model, prompt, or vendor has been named for any pattern in this section except Signal
AI's existing transcript summary.** Every Reference section below is a placeholder for
content that does not exist yet.
* **No evaluation framework exists.** There is no eval set, no scoring rubric, and no named
owner for deciding when an AI feature is good enough to ship.
* **The escalation path from Suggests to Acts is undecided.** Nothing says who approves a
feature moving up a tier, or what evidence that decision requires.
* **Whether Identifiers apply per-feature or once for all of Invoca's agentic surfaces is
undecided.** Signal AI, a future assistant, and a future copilot panel could each need their
own name and avatar, or could share one identity. See
[Identifiers: Name](/invoca-design-system/ai-experience/identifiers/name).
## Related
[Patterns overview](/invoca-design-system/patterns/overview), for the compositions this
section's outputs still render inside of. [Foundations: Accessibility](/invoca-design-system/foundations/accessibility),
for the criteria every page here inherits before adding its own. [Foundations: Motion](/invoca-design-system/foundations/motion),
for streaming and loading treatments.
## Why it works this way
**Borrowing the vocabulary and rejecting the shape.** Shape of AI's own page format is
description, design considerations, related patterns, examples — no constraints, no "choose
something else when," no stated risk, no gap. That is the right shape for a public survey of
what the industry does, and the wrong one for a house system, where the reader needs to know
what *Invoca* requires and what it must not do. This section keeps the names and adds the
parts a public catalogue has no reason to carry.
**Oversight is not a chapter here — it is two of seven categories.** Governors and Trust
builders exist to let a user check and correct the system, and giving them equal billing with
Wayfinders and Inputs is a stated priority, not an accident of alphabetizing a list.