Most of my work sits between two questions:

Creator reviews

Independent running-shoe reviews enter through submitted videos, channels, playlists and scheduled discovery. Each voice keeps its identity.

• The queue distinguishes video, channel, playlist and scheduled acquisition jobs.
• Source records connect videos to creator metadata.

Source identity

Video and channel metadata establish who spoke, what the review covers and where the original can be found.

• The metadata client uses the official YouTube Data API.
• Channel, video and playlist lookups preserve their source identifiers.

Timestamped words

Transcript segments preserve the reviewer's words and their position in the video, giving later claims a place to point back to.

• A configurable acquisition chain accepts supplied files and enabled providers.
• A fetched document must match the requested source ID.

Evidence store

Source records and timestamped transcripts are stored before interpretation. Later stages can reuse evidence without acquiring it again.

• Source artifacts preserve the original transcript payload and acquisition provenance.
• The ingestion handler reuses existing artifacts before calling a provider.

Corpus search

Operators can search the stored transcript corpus without repeatedly parsing every original artifact or making another model call.

• A rebuildable PostgreSQL full-text projection uses TSVECTOR and a GIN index.
• This admin-only projection is separate from the original timestamped evidence.

Mention extraction

Structured extraction identifies product mentions, resolves which shoe they concern and removes duplicates before they reach the grading engine.

• Time-marked windows pass through extraction and product resolution.
• Accepted records are deduplicated and persisted as mentions.

Stored mentions

Product-linked review evidence is stored with source identity. This is the input to the deterministic verdict engine.

• Mention records connect the product, source and extracted review evidence.
• Recomputation reads those records rather than generated editorial prose.

Deterministic verdict

A separate grading engine computes score, tier, verdict and confidence from stored review evidence. The editorial model does not choose the grade.

• The pure consensus engine applies shared, explicit grading rules.
• Its result is stored as a product verdict snapshot.

Attributed opinions

The editorial pipeline begins by extracting what each reviewer said. An unsupported claim can be removed while faithful claims from the same source survive.

Input

Timestamped transcripts

Output

Attributed claims

• Stage A produces source-specific distillates with claim-level admission.
• The cached output records transcript content, model, prompt and product scope.

Grounded themes

Opinions become useful themes: agreement, disagreement, minority views and individual observations. Each theme cites the particular claims that support it.

Input

Attributed claims

Output

Evidence-backed themes

• Stage B resolves exact Stage A claim IDs through the harness.
• A durable product theme set carries the evidence identities used in synthesis.

Buyer editorial

Grounded themes become clear writing about who a shoe suits and what tradeoffs reviewers describe. The writing can interpret buyer relevance without inventing product facts.

Input

Evidence-backed themes

Output

Product graph

• Stage C rewrites accepted themes and audits for invention or reversal.
• Its durable draft remains separate from the versioned publication.

Fidelity checks

Checks protect against fabrication, distortion and broken traceability. They act on individual claims, themes and paragraphs, while recording what was actually verified.

• Deterministic validation works alongside configured model verification.
• Verification coverage and exclusions remain recorded rather than implying universal review.

Pinned provenance

A published claim stays connected to the exact evidence used to write it, even if another ingestion run later changes the available corpus.

• Each selected distillate is pinned by ID with its full cache identity.
• Theme sets retain those pins for stable publication readback.

Durable queue

Work is recorded as database jobs, so acquisition and reasoning can continue independently of a page request or an operator's session.

• Active jobs are deduplicated by kind and entity.
• Workers claim queued rows with FOR UPDATE SKIP LOCKED.

Bounded workers

Workers claim a job, process its units and record progress. A maintenance pass recovers stale work and keeps operational state visible.

• The worker dispatches registered handlers outside the short claim transaction.
• Heartbeats and a stale-job sweep support recovery.

Progress checkpoints

Completed units are recorded as work proceeds. A recovered job can continue from its progress instead of repeating every finished unit.

• The worker commits per-unit progress and refreshes heartbeats.
• Budget pauses preserve the job's recorded progress.

Bounded recovery

Recovery handles infrastructure and unusable provider responses without repeatedly regenerating sound evidence because a checker disliked the content.

• The reasoning harness bounds producer retries and distinguishes infrastructure failures from low yield.
• Stages reuse durable upstream outputs rather than discarding valid prior work.

Spend controls

An estimate precedes execution. Per-call usage is recorded and reconciled, while a daily spend check can stop workers from claiming more billable work.

• The ledger stores estimated and actual cost, and jobs can pause for budget.
• In-flight work can still overshoot; this is not an exactly-once spending guarantee.

Models by role

Extraction, synthesis, writing and verification have distinct model roles. A run records its chosen configuration instead of leaving the model identity implicit.

• Explicit request choices override saved prompt choices and curated defaults.
• The runtime supports configured transports and records routing violations.

Durable stage outputs

Opinions, themes and draft editorial have their own stored outputs. One stage's failure does not require purchasing the work of every earlier stage again.

• Distillates, product theme sets and editorial drafts are persisted independently.
• Model, prompt and contract identity distinguish reusable outputs.

Publication preview

The operator can inspect the exact buyer-facing package before publishing a version. Its prose, citations and lineage are captured together.

• The publication bridge exposes a free preview and idempotent version creation.
• Its frozen public record excludes private runtime and transcript payloads.

Explicit activation

A published candidate becomes the current editorial only through an explicit activation choice. Producing a draft and making it public are distinct actions.

• The bridge appends a version linked to its source run.
• Only an explicit make_current choice changes the active editorial.

Version rollback

A previous editorial version can be restored without asking a model to recreate what the reader saw before.

• The publication bridge retains version and previous-version identity.
• Its rollback operation restores the previously current editorial.

Stored-result API

The product endpoint reads stored verdicts, editorial and evidence. Opening a product page does not launch the reasoning pipeline.

• The product response combines separately stored outputs.
• Import-boundary tests keep model runtime and pipeline modules out of the public read path.

A useful answer

The buyer sees a verdict, an explanation and the sources behind it. Separate systems come together in one understandable product page.

• The frontend displays the backend's verdict rather than recomputing a grade.
• Evidence links expose source identity and timestamp quality.

Discovery surfaces

Published product and source context also supports discovery through feeds, creator pages and rankings. Evidence becomes part of finding the product, not only explaining it.

• The feed reuses the shared publication predicate.
• Frontend clients expose creator and contribution leaderboard surfaces.

Typed contracts

Explicit data contracts connect Python services and the TypeScript interface. Optional additions preserve older responses while the system evolves.

• Strict Pydantic models define consensus inputs and outputs.
• The frontend's additive reasoning contract preserves the existing editorial surface.

Pinned dependencies

The backend CI installs a frozen dependency set so validation runs against the versions recorded in the repository.

• CI installs Python through uv and uses uv sync --frozen.
• The checked-in lockfile controls dependency resolution.

Hermetic validation

Backend CI tests behavior without provider calls or production data. Focused contracts protect the separation between reasoning, evidence and public reading.

• GitHub Actions runs pytest and a blocking lint check over the transcript surface.
• Publication tests check that evidence readback uses pinned source records.

Review artifacts

A branch and pull request carry each implementation slice into review. Recorded changes and check output give the next reviewer a durable starting point.

• The operating model names GitHub PRs as the shared review artifact.
• It requires command output rather than an unsupported claim that checks passed.