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Theory v1.0 · 2026-05-28

Fidelity is the correspondence between a claim and its referent. MFid is the instrument that measures it.

What fidelity is

Fidelity is the correspondence between a claim and its referent.

A claim is what something says it is — a spec, a contract, a datasheet, a marketing line, a certification, an architecture description.

A referent is what the thing actually is — measurable, observable, operating in the world.

Fidelity is high when the two are tightly coupled. Fidelity degrades as they diverge. Perfect fidelity is the exception, not the rule.

Why fidelity matters

In every domain, decisions are made against claims. A vendor selection is a decision against a claim about capability. A renewal is a decision against a claim about delivered value. A regulatory filing is a decision against a claim about compliance posture. Decisions are only as good as the fidelity of the claims they rely on.

The exposure of a buyer to a wrong decision can be written as:

exposure = consequence × (1 − fidelity)

Two ways to reduce exposure: reduce consequence (insurance, redundancy, diversification, second-sourcing), or increase fidelity of the claim (audit, instrumentation, verification). The market invests heavily in the first and under-invests in the second — not because fidelity doesn’t matter, but because there is no widely-adopted instrument for it. Buyers can’t measure what they have no tool for.

MFid is the instrument.

The four dimensions

A claim can fail to match its referent in four distinct ways. Each is the answer to a different empirical question the buyer can ask. Each requires a different verification method.

Determinism — does it behave consistently with the claim, across repeated observation?

A claim that “the API responds in under 200ms” is a Determinism claim. So is “the storage is durable for eleven nines” and “the policy is enforced for all requests.” These claims must hold every time, or they are not the same claim.

Determinism fidelity is verified by repeated measurement. A claim that holds once and fails twice scores 0.33 Determinism for the observed window.

Efficiency — does it perform at the quantitative level the claim specifies?

A claim that “the drive does 500K IOPS” is an Efficiency claim. So is “the model has 175 billion parameters” and “the network supports 100 Gbps line rate.”

Efficiency fidelity is verified by single measurement against the published number. If observed is 340K against claimed 500K, Efficiency for that claim scores 0.68.

Observability — can the gap, if any, be seen by the buyer?

A vendor that claims “audit logs for all administrative actions” but exposes log access only via a quarterly PDF report has low Observability fidelity for that claim. The buyer cannot independently verify what the vendor asserts.

Observability is the dimension that makes the other three measurable in practice. A vendor with high Determinism, high Efficiency, and high Intentionality but zero Observability is a black box — the buyer cannot trust any of the other dimensions because there is no way to check.

Observability is verified by attempting to instrument. What can be measured at the buyer’s edge counts; what is gated behind vendor cooperation does not.

Intentionality — does the design serve the purpose the claim states?

A claim like “Zero Trust architecture” or “GDPR by design” or “high availability” is an Intentionality claim. It is not a number — it is a stated intent. Intentionality fidelity asks whether the actual architecture, when read, matches the philosophy that was claimed.

A vendor that markets “Zero Trust” while operating a perimeter-based network with VPN tunnels has low Intentionality fidelity, regardless of how well that perimeter network performs.

Intentionality is verified by reading the design and comparing to the stated intent. This is the most novel of the four dimensions and the hardest to score consistently. It is also the dimension that distinguishes MFid from any pure-numerical framework like an SLO.

Why these four — non-overlapping, defensible as exhaustive

The four dimensions are not arbitrary. They answer four genuinely different questions, each with its own verification method:

Dimension Question Verification
Determinism Consistent? Repeated measurement
Efficiency Performant? Single measurement vs spec
Observability Visible? Attempted instrumentation
Intentionality Coherent? Design reading vs stated intent

Each dimension can fail independently. A vendor can be highly deterministic and highly efficient while still being opaque (low Observability) or marketing a design they don’t actually implement (low Intentionality).

Candidate failure modes that seem to be missing from the four collapse into one or two on examination:

  • Security-fidelity (“the system enforces what it claims to enforce”) = Determinism (consistent enforcement) + Intentionality (architecture matches stated security model).
  • Durability-fidelity (“the thing lasts as long as claimed”) = Determinism extended over time.
  • Cost-fidelity (“the bill matches the quote”) = Efficiency, where the resource being measured is dollars-per-output.
  • Compatibility-fidelity (“it interoperates as claimed”) = Determinism (interop holds across calls) + Intentionality (design choices match the interoperability claim).

If a fidelity failure mode genuinely fits none of the four, the decomposition needs revision. This is an invitation: stress-test it.

Scope of the theory

The theory of fidelity is domain-general. The four dimensions are abstract; they apply to any claim about any subject matter where a claim and a referent can be distinguished.

The current MFid practice is IT-focused. The examples, citations, and worked walkthrough on this site are drawn from software, hardware, infrastructure, and IT services.

Other domains — pharmaceutical efficacy claims, legal contract reliability, construction specification compliance — may admit MFid analysis under the same four dimensions, or may require domain-specific decompositions. SDCorp has not yet performed MFid analysis outside the IT domain. The theory permits it; the practice does not yet demonstrate it.

On the name: SDCorp stands for “Software-Defined Corporation,” which collides with the SDN/SDS/SDDC family of terms in IT. The phrase is used here in an older, narrower sense — see Why “Software Defined”? for the reclamation argument.

The math

MFid aggregates the four dimensions using the geometric mean:

MFid = (D × E × O × I)1/4

Each dimension is normalized to the interval [0, 1], where 1.0 means perfect correspondence between claim and referent on that dimension.

Why geometric and not arithmetic? Fidelity is multiplicative, not additive. A claim with three strong dimensions and one weak one is not mostly-honest at three-quarters strength. It is fragile: the weak dimension is a hole through which the buyer can be deceived, and the strong dimensions do not compensate.

Worked example. A vendor scores D=0.9, E=0.9, O=0.9, I=0.1.

  • Arithmetic mean: 0.70
  • Geometric mean: 0.516

The geometric score is more truthful. A vendor whose design does not match their stated intent (I=0.1) is misleading the buyer about the most consequential question — what kind of system this actually is — regardless of how well the secondary metrics perform. The geometric mean encodes this. The arithmetic mean obscures it.

The geometric mean of any dimension scoring zero is zero. This is the correct behavior: a claim with one dimension fundamentally broken is not a partially-honest claim, it is a broken claim.

The limits of MFid

Four things MFid does not measure. These are not modesty disclaimers — they are the boundary of what the definition (fidelity = correspondence to claim) can support.

Whether the claim is desirable

MFid measures match, not merit. A vendor claiming “we monitor every employee keystroke” can score 1.0 MFid if the system is in fact built to monitor every keystroke and operates as such. MFid says nothing about whether keystroke monitoring is desirable, legal, or ethical.

Behavior outside the claim

MFid scores against what was claimed. Undocumented behavior is not penalized, even if it is significant. A vendor that silently does things they never claimed — good or bad — scores 1.0 MFid as long as their documented claims hold. This is by design. MFid cannot audit the absence of a claim.

Future fidelity

MFid measures current correspondence. It does not predict whether the vendor will continue to deliver under load, time, or change of conditions. A trend-MFid (the same instrument applied across time windows) could address this; base MFid does not.

Strategic fit

MFid answers “is the claim true.” It does not answer “should I buy this.” A purchasing decision needs three inputs: fidelity of claim, utility of the thing being sold, and cost. MFid contributes the first. The other two require their own instruments.

Our own dates discipline

We publish no dates we cannot commit to. A roadmap is itself a fidelity claim — the gap between a promised ship date and an actual one is measurable, and we hold our own commitments to the same standard we hold a vendor’s. When we have nothing we can stand behind, we say so rather than publish a milestone.

MFid and SLO / error-budget practice

An SLO (Service Level Objective) and an error budget are well-formalized in the SRE community. They are not redundant with MFid; they are complementary.

SLO / Error Budget MFid
Measures Performance against a numerically agreed target Correspondence between published claim and reality
Target Agreed between buyer and seller Whatever the vendor publishes, including unilateral claims
Dimensions Single (the SLO itself) Four (D, E, O, I)
Output Error budget Dispersion-penalized aggregate score
Time scope Continuous, real-time Periodic, point-in-time

An SLO can serve as a single input to MFid’s Efficiency dimension when the vendor’s claim is the SLO. MFid extends to claims SLOs do not formalize: stated architectural intent, instrumentation completeness, qualitative consistency claims.

A mature buyer uses both: SLO for the contractual layer, MFid for the broader claim layer.

Where to next

  • Methodology — the operational spec: evidence tiers, scoring procedure, version history, how scores are produced.
  • Walkthrough — how MFid scores a real public SLA, demonstrated on Cloudflare.
  • Compare — MFid against SLOs, DORA, and ISO 25010: what each measures and what each leaves on the table.
  • Manifesto — the ethic that underlies the instrument.
  • Status — our own MFid, live, as the working proof point.

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