EDITORIAL WORKFLOW · BUILT WITH OVERLIFT

Article Studio

Take a brief through draft, review, and publication.

Article Studio is an administration workspace for preparing articles and their media. Follow the stages from a structured brief to a reviewed page, with model choices, estimated costs, and publication controls visible.

See the editorial workflow See project screenshots
Article Studio creator wizard showing the eight-stage guided content workflow
Creator wizard The guided run moves from one idea through brief, draft, audit, images, preview, cost review, and a deliberate manual publish decision.

Recorded project scope

Implemented

Eight-stage Article Studio creator workflow

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  • Structured-output model routing, fallback recovery, duplicate-action guards, and readiness checks
  • Azure Blob media integration, preview, cost review, and manual publish control

Demonstrated

Guided idea-to-brief-to-draft workflow in the live administration interface

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  • Detailed model, prompt, style, approval, and structured JSON controls
  • Multi-site configuration and safe local fallback behavior

Planned

Additional production publishing connectors across owned web properties

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  • Broader campaign queues, editorial analytics, and reusable content programs
  • MiniLM semantic checks for consistency, duplication, and source alignment

Research

Measured agent evaluation for brief fidelity and supported claims

More in this category (2)
  • Local semantic routing before expensive provider calls
  • Higher-autonomy content operations that preserve explicit human authority
PROJECT SCREENSHOTS

Explore the interface, workflow, and results shown in the project screenshots.

Article Studio brief builder with AI approval, angles, readiness, model, style, and prompt controls
Brief builder Focused step options keep the simple path clear while exposing approval, angle, readiness, model, style, and prompt evidence when the operator needs it. View full-size image
MARKETING

Who it helps and why.

Content work becomes unreliable when research, instructions, drafts, review, images, cost, and publishing are scattered across prompts and browser tabs. A model can return attractive prose while missing the brief, breaking the required structure, or publishing before a person has approved the result.

What makes it useful: One-shot writing tools optimize for a quick draft. Article Studio makes the entire editorial pipeline visible: sources, stage transitions, approvals, costs, media, metadata, and final publish authority remain inspectable, so creative assistance does not erase editorial accountability.

BUSINESS / EXECUTIVE

Business value.

The workflow brings the brief, draft, media, and publication review into one administration experience. Its value depends on useful supported content and editorial judgment; generating a draft does not make it ready to publish.

Explore the business outcomes
  • Higher content throughput
  • More consistent editorial process
  • Clear proof of applied agentic AI
ARCHITECTURE

How the system fits together.

The agentic layer is structured around staged work: gather context, shape an outline, draft, review, enrich metadata, select media, and prepare publication. The goal is controlled autonomy: useful AI throughput with reusable instructions, quality checks, and human judgment still in the loop.

A representative workflow

  1. 01

    Prepare a brief with the audience, purpose, required sources, structure, and style.

  2. 02

    Generate and review the draft and media, inspecting supported claims, changes, and estimated cost.

  3. 03

    Preview the assembled page and approve the exact version through the publication controls.

Explore the architecture details

I built Article Studio as an eight-stage content operations system: Idea, Brief, Draft, Audit, Images, Preview, Cost Review, and Publish. It uses structured model requests, task-specific routing, reusable site rules, recovery paths, media management, cost visibility, and an explicit human decision before publication.

ENGINEERING

Engineering choices.

I divided content production into explicit stages with structured outputs and readiness checks. Model routing, cost estimates, media review, and retry controls support the workflow, while a person retains the decision to publish.

Explore the technology and engineering details
Technology stackAzure, ASP.NET Core, agentic workflows, content services, PostgreSQL, telemetry
  • Research, outline, draft, review, metadata, media, and routing stages
  • Reusable instructions and quality controls
  • Publishing support across multiple connected web properties
OVERLIFT METHOD

How this product applies the OverLift method.

The OverLift method turns a vague idea into typed stages, keeps sources and editorial rules visible, compares content paths before generation, requires human approval, and preserves the reasoning behind the final publication. Creativity stays flexible while the workflow remains accountable.

Explore the shared OverLift architecture

The method is reusable. Each product supplies its own facts, rules, execution, and validation. These tiers describe the shared architecture; the project scope above records which capabilities are implemented here.

Why determinism matters here: Publishing changes public truth. Determinism keeps source identity, approved wording, version state, and release authority reproducible even when models help research or draft.

  1. T0
    Exact baseline

    Define the authoritative result before adding acceleration, semantics, or agents.

  2. T1
    Measured evidence

    Instrument state, latency, quality, and failure so improvement is observable.

  3. T2
    Bounded ownership

    Move expensive or high-frequency work behind clear worker and memory boundaries.

  4. T3
    Deterministic transport

    Version messages, snapshots, identities, deadlines, and replay inputs.

  5. T4
    Semantic assistance

    Let local retrieval and models propose meaning only inside admitted evidence.

  6. T5
    Candidate paths

    Compare several allowed next actions with explicit risk, cost, fit, and uncertainty.

  7. T6
    Shadow verification

    Challenge the production route without giving the challenger authority.

  8. T7
    Governed production

    Promote only measured, replayable paths with fallback and operational receipts.

  9. Tier-S
    Experimental challenger

    Run advanced evaluators in shadow, compare them with the control, and graduate only repeatable gains.

CATS

Context-Aware Tier Selection

CATS chooses a qualified execution tier for the evidence, device, latency, permissions, and failure conditions of the task.

SEMANTIC BRIDGE

Meaning becomes typed product state

The Semantic Bridge maps a goal to explicit entities, evidence, uncertainty, tools, and permissions. Missing or contradictory information remains visible.

DETERMINISM

Validate the action and retain the result

Models may retrieve, compare, or propose. Exact software checks facts, permissions, state changes, and execution, then records what happened.

OverLift securityAgentic AI Glossary

Read the OverLift MethodOverLift.ai See other products
PROOF

Evidence and limits.

The supplied screenshots show the administration workflow, brief builder, model controls, and publication review. The portfolio describes these private tools without giving visitors access to generate content, incur provider charges, or publish. Output quality still requires editorial review.

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