Claim-Verification on AIBussin — AI applications, systems and books

Verification, Repair, and Rejection

Sun, 30 Aug 2026 18:38:00 +0100

Chapter 12 gave the system a control plane.

It can now say:

commitment = HOLD
next_action = VERIFY

or:

commitment = HOLD
next_action = RETRIEVE

or:

commitment = HOLD
next_action = REFINE

or:

commitment = DENY
response_mode = REJECTION

Those are policy decisions.

They are not yet recovery implementations.

The obvious implementation is dangerously tempting:

The answer failed a check.
Ask the model to fix it.

But the model that produced the first unsupported statement can produce a second unsupported statement while “correcting” it.

Semantic Pipelines

Thu, 08 Oct 2026 09:00:00 +0100

Semantic Pipelines

This chapter reports a CPU run of the pipeline’s retrieval and relevance stages over SciFact, and the full pipeline with a declared weak relation provider. The relation (entailment) and generation providers need a language model and are deferred. The author’s private Writer evidence is off limits; the public claims are SciFact’s.

The problem

Chapters 21-24 built the pieces: candidate generation, filtering, relation, composition. This chapter asks whether they fit together into a real task. The task is claim research: given a claim, retrieve evidence, decide whether the evidence supports or contradicts the claim, produce an answer, and decide whether that answer is supported.

Warranted Search: When AI Must Prove Before It Looks

Tue, 02 Jun 2026 18:54:26 +0100

TL;DR

Modern AI systems often retrieve nearby text and generate confident answers, but that is not the same as proof. A citation can be real, the answer can be correct, and the evidence can still fail to support the claim.

This post argues for warranted search: a scoped, claim-driven form of intelligent grep. Instead of asking an AI to rummage through a corpus, we give it a specific claim, a bounded search warrant, and a limited set of safe operations.