CueCrux Whitepaper -The Cost of Proof (and Why It’s Worth Paying)

Version: 1.0
Date: 10 January 2026
Contact: contact@cuecrux.com

Executive summary

Proof is expensive because it is work you can check.

Most AI systems optimise for producing answers quickly. The moment you ask for verification, you are asking for additional behaviours:

retrieve and preserve admissible evidence,
select non-redundant support (not just lots of links),
expose contradictions and missing context,
mint receipts that can be verified later,
enable replay so drift can be detected,
and keep the whole thing secure under adversarial pressure.

Those behaviours cost compute, storage, operational complexity, and time.

The mistake is assuming the alternative is free.

When organisations ship unproven answers into workflows, they still pay. They pay later, in a different currency:

incident time,
legal and compliance friction,
reputational damage,
rework,
and the slow decay of organisational confidence.

CueCrux takes a practical position:

Proof should be selective, budgeted, and reusable.

CueCrux does not ask you to audit everything. It gives you mechanisms to:

pay for proof when it matters,
reuse verified artefacts across teams,
route uncertain answers for extra checks,
and keep costs bounded through explicit modes and policies.

This whitepaper explains:

why proof costs what it costs,
how to make proof cheaper than the alternative,
and how partners and AI companies can integrate verification without turning every query into a forensic investigation.

1. Proof is expensive because it refuses to be vague

A confident paragraph is cheap.

A proof-carrying answer is not.

1.1 What “proof” means in an AI context

CueCrux uses “proof” in the operational sense:

Evidence lineage: what sources were used, under what policies.
Minimal support: the smallest non-redundant evidence set (MiSES) that supports the atomic claims.
Receipts: signed snapshots (CROWN receipts) that bind the answer to its inputs and settings.
Replay: the ability to re-run a query under the same snapshot (especially in audit mode) and detect drift.
Visible uncertainty: coverage, fragility, contradiction signals.

This is not philosophical certainty. It is “can we defend this in a room where someone is paid to be sceptical”.

1.2 Why that costs more than generation

Proof requires additional work that plain generation skips:

more retrieval and filtering
more ranking and validation
more storage for traceability
more observability and logging
more security controls (keys, signing, separation of powers)
more product surface (trust panels, receipts, dispute handling)

If you have ever tried to make “it seemed reasonable at the time” acceptable evidence, you already know how this ends.

2. The hidden cost of unproven answers

The cheapest answer is often the most expensive decision.

2.1 Narrative debt

Unproven answers create narrative debt: the obligation to explain later why something was believed and acted on.

You can push that debt forward by shipping quickly, but it still accrues interest:

the answer gets copied and reused
context gets shaved off
assumptions become implicit
automation applies it consistently
accountability gets messy

Eventually the organisation pays, usually during an incident, and usually with everyone watching.

2.2 Rework is a proof bill you pay twice

When an answer is wrong or fragile, teams commonly do:

a re-check,
a manual audit,
a patch,
and a governance scramble.

That is “proof”, but late, stressful, and duplicated.

Paying for proof earlier is often cheaper because:

it is done once,
it is structured,
it is reusable,
and it creates receipts that reduce future audit costs.

2.3 Compliance friction

In regulated or high-stakes domains, “show your working” is not a preference.

It is the difference between:

a controllable process, and
a scenario where the only defensible position is “we shouldn’t have used it”.

CueCrux is designed so receipts and evidence lineage exist by default in verified and audit paths, not as an afterthought.

3. Where the cost comes from

The cost of proof is not one cost. It is a stack.

3.1 The cost drivers

Below is a simplified cost map. Numbers are not included because your costs depend on corpora, policies, and risk levels. The structure is what matters.

Cost driver	What it buys	Why it matters
Retrieval depth	broader context, counterevidence chances	shallow retrieval makes fragile answers look confident
Evidence filtering	admissibility, licence, policy compliance	proof that violates policy is just expensive wrongdoing
MiSES selection	minimal support, reduced redundancy	makes dependency structure visible and reusable
Receipt minting	signed snapshots, integrity metadata	enables verification and later defence
Replay capability	drift detection, reproducibility	turns “it changed” into “here’s what changed”
Coverage + fragility	operational uncertainty signals	makes routing possible and prevents false decisiveness
Observability	detection of drift, manipulation, failure modes	prevents silent degradation
Security	key management, signing, separation	stops receipts becoming decorative

3.2 Proof has storage cost, but also storage value

Storing:

evidence references,
receipts,
and governance state

has a cost.

It also creates a new asset: verified knowledge you can reuse.

Most organisations already store answers, just in a worse format:

screenshots
copied paragraphs
email threads
“final” decks

CueCrux makes that storage structured and verifiable.

4. The economic mistake: treating all questions as equal

The single biggest cost error is applying one verification approach to all queries.

Not every question deserves audit mode. Not every answer deserves to be preserved. Not every workflow deserves automatic action.

CueCrux treats proof as selective, not universal.

4.1 Risk tiers, not vibes

A simple risk tiering makes proof practical:

Tier 0: exploratory
Curiosity, ideation, drafts. Light mode is fine.
Tier 1: operational
Support, product decisions, internal comms. Verified mode should be the default.
Tier 2: policy-critical
Compliance, finance, safety, HR, legal. Audit mode or verified plus additional checks.

The point: proof should follow risk.

4.2 The cost of being wrong is asymmetric

The cost of being wrong in a brainstorming session is usually small.

The cost of being wrong in a policy decision is often:

irreversible
public
and career-shaped

Selective proof is simply acknowledging reality.

5. How CueCrux makes proof affordable

CueCrux reduces the cost of proof in four ways.

5.1 Evidence discipline: MiSES prevents citation inflation

“Plenty of sources” can be the least informative thing you can say.

MiSES focuses on minimal sufficient support:

reduces redundancy
exposes dependencies
improves maintainability
and lowers long-term review cost

This turns “review 40 links” into “review the 3 that matter”.

5.2 Modes: buying the right depth

CueCrux modes exist so you can buy the right behaviours per use case:

light: fast, low overhead
verified: receipts and minimal sufficient evidence sets
audit: replay, counterfactuals, and stronger verification expectations

Modes prevent “proof for everything” and also prevent “proof for nothing”.

5.3 Routing: pay for proof only when signals demand it

CueCrux signals (coverage, fragility, contradiction, staleness) exist to support routing:

If coverage is low, broaden retrieval or request better query constraints.
If fragility is high, run counterfactual replay.
If contradiction rises, mark disputed and escalate.
If staleness flags are hit, revalidate or constrain time windows.

This is how proof becomes operational, not decorative.

5.4 Reuse: pay once, benefit many times

The strongest economics of proof is reuse.

If receipts and evidence sets are stored and addressable, you can:

reuse verified answers across teams,
compare snapshots across time,
and avoid re-auditing the same claim repeatedly.

Proof becomes an asset, not just a cost.

6. A practical budgeting model

Proof needs a budget, otherwise it becomes an unbounded hobby.

CueCrux supports budgeting through explicit policies and guardrails.

6.1 Budget what you can control

A practical proof budget can constrain:

maximum retrieval depth (k, candidate sets)
maximum evidence set size per claim
maximum model calls per answer
maximum counterfactual runs
sampling rates for audit replay
freshness constraints (time windows)
maximum spend per workflow or per user

Budgets should be explicit and visible. Hidden budgets become mysterious failures.

6.2 Spend where it reduces future spend

A useful heuristic:

Spend more on proofs you will reuse.
Spend more on workflows with irreversible outcomes.
Spend more when downstream automation will act without hesitation.
Spend less when the answer is disposable.

This is not being cheap. It is being sane.

7. A TypeScript example: routing and budgeting proof

Below is a policy pattern that keeps costs bounded while still paying for proof when the system signals risk.

import { Answers, Receipts } from '@cuecrux/sdk';

type Policy = {
  maxMedianAgeDays: number;
  maxContradictionRate: number;
  maxFragility: number;
};

const policy: Policy = {
  maxMedianAgeDays: 90,
  maxContradictionRate: 0.05,
  maxFragility: 0.7
};

const verified = await Answers.ask({
  q: "Summarise the regulation and the implications for our product",
  mode: "verified",
  // Budget controls (illustrative)
  k: 20,
  timeWindow: { from: "2025-01-10", to: "2026-01-10" }
});

if (!(await Receipts.verify(verified.crown.receiptId))) {
  throw new Error("Receipt verification failed");
}

const medianAgeDays = verified.trust?.recency?.medianAgeDays ?? 9999;
const contradiction = verified.trust?.contradictionRate ?? 0;
const fragility = verified.contextCoverage?.fragility?.score ?? 1;
const coverageLabel = verified.contextCoverage?.label ?? "low";

const risky =
  coverageLabel === "low" ||
  medianAgeDays > policy.maxMedianAgeDays ||
  contradiction > policy.maxContradictionRate ||
  fragility > policy.maxFragility;

if (risky) {
  // Escalate selectively, not by default
  const audited = await Answers.ask({
    q: "Re-check with counterevidence and produce a disputed label if warranted",
    mode: "audit",
    // Tighter budget for audit, but deeper guarantees
    k: 30,
    timeWindow: { from: "2025-07-10", to: "2026-01-10" }
  });

  if (!(await Receipts.verify(audited.crown.receiptId))) {
    throw new Error("Audit receipt failed verification");
  }

  return audited;
}

return verified;

The point is not the exact thresholds. The point is that proof becomes a policy-driven behaviour, not a marketing promise.

8. Proof incentives: pay for evidence, not persuasion

If the system rewards:

fluency,
speed,
and volume,

it will produce confident nonsense more efficiently.

CueCrux incentives are designed to reward:

evidence diversity and independence,
minimal sufficient support,
replayability,
and stable governance.

This matters for partners, too.

If an AI company integrates CueCrux but strips receipts and uncertainty signals, it will get short-term UX smoothness and long-term incident theatre.

Smooth is not strong.

9. Common anti-patterns (and how CueCrux avoids them)

9.1 “Audit everything”

Auditing everything is like logging every thought you have: expensive, noisy, and only useful for a therapist or a post-mortem.

CueCrux solves this with:

modes,
routing,
and sampling.

9.2 “Trust score theatre”

A single score invites gaming and hides structure. CueCrux prefers structured signals and receipts that can be checked.

9.3 “Proof laundering”

This happens when:

a system uses CueCrux once,
then copies the answer elsewhere,
then claims the copied answer is “verified”.

CueCrux integration guidance is strict:

store receipt IDs with any relied-on answer
verify server-side
carry uncertainty through pipelines

that proof is free,
that receipts guarantee correctness,
that every question should be audited,
that one policy fits every domain,
that governance removes disagreement.

CueCrux claims something narrower and more practical:

proof can be structured,
proof can be budgeted,
proof can be reused,
and proof can be cheaper than the alternative.

Call to action

If you are integrating AI into workflows, you will pay for proof either:

upfront as a designed capability, or
later as a chaotic incident response.

CueCrux exists to make the upfront version possible:

proof-carrying answers,
minimal sufficient evidence,
receipts and replay,
and uncertainty signals that drive policy and routing.

Pay for proof when it matters. Reuse it when you can. And stop buying confidence at retail prices.