SamurAI Studios: Contribution Record

This is the evidence-backed reference for my work at SamurAI Studios. It is deliberately more detailed than the public portfolio or resume so I can prepare accurate interview stories without turning every application into a wall of text.

The underlying repositories are private. This document describes the systems and outcomes without publishing private links, source code, credentials, customer data, or unreleased product details.

Role Snapshot

The public description of the company is a creative studio combining human filmmaking craft with generative-AI workflows. My engineering work supports that production process: ingesting creative material, structuring briefs, planning scenes and storyboards, generating and managing media, and giving operators reliable tools to inspect the pipeline.

Verified GitHub Audit

Audit date: July 6, 2026

Source: authenticated GitHub data for the purbayan62 account only.

Contribution distribution

The 13 closed-without-merge PRs are not described as shipped work. Several were early slices or superseded changes; they are still useful evidence of exploration, but the resume headline uses only the 57 merged PRs.

Why the GitHub profile graph looks empty

GitHub’s contribution calendar reported only the account-creation event even though authenticated search returned the work above. The repositories are private and private contribution visibility is not enabled for the profile. The profile graph is therefore not a reliable measure of this work.

Contribution Map

1. Story-first creative brief pipeline

I helped take a creative deck from an uploaded source to a structured, inspectable brief suitable for downstream generation.

The work covered:

• durable parser infrastructure and a reproducible local stack;
• PowerPoint ingestion with validation for invalid or unsupported sources;
• extraction of embedded video and representative keyframes;
• prioritized visual inputs and automated visual captioning;
• safe URL classification and metadata fetching;
• a typed creative-brief schema, taxonomy, and JSON Schema export;
• provider abstractions so extraction logic was not coupled to one model implementation;
• an OpenAI-backed brief extraction step;
• step-by-step persistence of ingest, evidence, media, and final-brief results;
• final results plus debug diagnostics;
• a golden-deck evaluation harness for regression testing;
• project/file deletion and source-bucket seeding;
• API-key protection for parser endpoints;
• an authenticated operator console with job search, live job details, artifact previews, and brief export;
• CI, type checking, server integration tests, smoke testing, API contracts, and a deployment runbook.

The important engineering idea was observability. A document pipeline should not behave like one opaque model call. Each stage records what it consumed and produced, so failures can be isolated and operators can inspect the evidence behind the final brief.

2. Multi-scene storyboard architecture

I delivered a scene-owned storyboard model across backend and frontend while preserving compatibility with the older project-level workflow.

Backend work included:

• a Scene domain model and migration for scene-owned storyboard data;
• default-scene resolution for existing projects;
• create, list, rename, reorder, and delete APIs;
• scene-scoped project form data;
• scene-scoped frames, version history, snapshots, restore, edit, regenerate, and render flows;
• project-level aggregation of final storyboards from individual scenes;
• legacy route compatibility;
• migration guards and shared fixtures;
• regression coverage for scene scope, versioning, snapshot restoration, and legacy behavior.

Frontend work included:

• a multi-scene workspace;
• route separation for the scene builder;
• API integration and state synchronization;
• scene-aware loading and skeleton states;
• final-storyboard and candidate-selection interfaces;
• follow-up simplification when the product direction changed.

This is my strongest end-to-end architecture story. It required a data-model migration, API design, compatibility decisions, UI restructuring, and tests that proved one scene could not leak state into another.

3. Image and video generation workflows

I worked on turning story beats and reference media into observable generation runs.

The delivered capabilities included:

• reference-image support for image generation;
• an image-generation gallery;
• per-beat video generation across Runway, Veo, and Seedance;
• final-clip generation with Kling image-to-video;
• continuity prompts to reduce visual drift between storyboard beats;
• persisted video prompts;
• run monitoring and clearer operational states;
• provider usage logging and a usage view;
• actionable error and warning toasts;
• real-time workspace separation and centralized data mapping;
• tests and CI for the lab workflow.

The product problem was larger than calling model APIs. The system needed consistent prompt context, provider-specific handling, progress visibility, recoverable errors, and enough usage information to understand expensive generation runs.

4. Media delivery and Gen Space

I improved how generated media is stored, served, selected, and inspected.

Key contributions:

• sharper WebP thumbnail generation;
• distinct media URL roles instead of overloading a single image URL;
• preview derivatives exposed through backend APIs;
• preview-aware frontend rendering;
• responsive aspect-ratio preservation;
• a Gen Space gallery and selected-asset inspector;
• navigation scoped to the visible asset set;
• regression tests for gallery and inspector behavior.

The main lesson was to make media intent explicit. A tiny card preview, a gallery image, and an original generation have different cost and quality requirements. Giving each role an explicit contract improved both rendering quality and frontend predictability.

5. Frontend architecture and product polish

I worked from low-level shared primitives up to complete storyboard and animatic workspaces.

This included:

• a shared Button, Modal, and Dropdown foundation;
• a compound MediaCard component for project and workspace tiles;
• shared sidebar and dashboard modules;
• a CSS-first design-system module;
• migration to Tailwind CSS v4 theme tokens;
• responsive media tiles, tooltips, info tips, and loading skeletons;
• optimistic data updates and cleanup of inconsistent fetching behavior;
• extracted form, beat-editor, and reference-shot components;
• a 16:9 reference-shot asset grid;
• a dedicated animatic workspace with compact render controls and clip-detail modals;
• authentication-entry cleanup and fixes for login/logout flashes;
• removal of obsolete product paths as requirements evolved.

This work is useful evidence that I do not treat “frontend” as cosmetic. The changes covered component API design, async state, route behavior, accessibility-adjacent interaction details, loading states, and maintainable styling architecture.

6. Reliability, tests, and delivery

Quality work was part of the feature work rather than an afterthought:

• Vitest and Jest coverage for generation and storyboard behavior;
• Playwright slide rendering;
• parser server integration tests;
• golden evaluation fixtures;
• local admin smoke tests;
• type checking and lint/format enforcement;
• GitHub Actions workflows;
• split CI for interactive rendering;
• API contracts and deployment/runbook documentation;
• safer provider authentication changes.

Chronological Narrative

April 2026: foundation and product cleanup

I started with engineering hygiene and product reliability: formatter/linter enforcement, pagination and rendering performance, environment validation, shared API clients, modal scroll behavior, reusable form components, and unified delete confirmations.

In parallel, I began work in the prompt lab: improving readability, moving the app to Vite, adding multi-prompt editing and specialized lab modes, supporting reference images, and building the first generation gallery.

Early May 2026: media contracts and generation

The next phase focused on media. I improved thumbnail quality, introduced preview derivatives and explicit image roles across backend and frontend, and built provider-backed image/video generation workflows. Usage logging, run monitoring, persisted prompts, continuity context, and error handling made those workflows operable rather than demo-only.

Mid-May 2026: storyboards become scene-aware

I then shipped the multi-scene storyboard architecture across the database, APIs, frontend routes, versioning, snapshot restoration, and tests. At the same time, I refined the final storyboard and Gen Space experiences.

Late May 2026: document intelligence vertical slice

I built out the creative-document pipeline from infrastructure through operator UX. The work progressed in narrow, verifiable slices: ingest, evidence, media, brief extraction, diagnostics, evaluation, authentication, operator views, search, preview, export, smoke testing, and runbooks.

June 2026: shared UI and workflow simplification

June focused on consolidating the product UI around shared primitives and a CSS-first design system, then simplifying storyboard, dashboard, landing, and animatic flows. Some earlier final-storyboard work was deliberately removed as the product direction changed. That is not wasted work: the useful engineering signal is being able to add a system, validate it, and later remove it cleanly without leaving orphaned state or APIs.

Strong Interview Stories

End-to-end ownership

Situation: Storyboards were project-owned, which limited larger productions that needed multiple scenes.

Task: Introduce scene-owned workspaces without breaking existing projects.

Action: I added the scene data model and migration, default-scene compatibility, scene CRUD, scoped frames and snapshots, version restoration, aggregate project views, frontend route separation, shared fixtures, and regression tests.

Result: The product could support multiple isolated scene workspaces while legacy projects continued to function.

Designing an inspectable AI pipeline

Situation: A creative deck contains text, images, links, and embedded video. A single model call would be difficult to debug and evaluate.

Task: Produce a structured creative brief while keeping intermediate evidence visible.

Action: I separated ingestion, evidence extraction, media processing, and brief generation; persisted stage results; added diagnostics and golden evaluations; and built an authenticated operator console.

Result: The pipeline became testable and inspectable, with failures attributable to a specific stage instead of an opaque final response.

Multi-provider generation

Situation: Video providers expose different models, inputs, operational states, and usage behavior.

Task: Support several providers without fragmenting the product workflow.

Action: I added per-beat generation, persisted prompts, continuity context, run monitoring, usage logging, warnings, and centralized mappings.

Result: Operators could generate and monitor media through one coherent workflow while retaining provider-specific capabilities.

Simplifying after requirements changed

Situation: An earlier final-storyboard path no longer matched the product direction.

Task: Remove it without leaving stale navigation, tests, persistence, or APIs.

Action: I traced the feature across frontend and backend, removed the UI and persistence paths, updated neighboring workflows, and cleaned up tests.

Result: The product became simpler and the codebase no longer carried a parallel workflow that users were not meant to follow.

Resume-Safe Summary

Use the concise version publicly:

Software Engineer at SamurAI Studios, building AI-assisted creative production systems. Shipped 57 merged PRs across four codebases spanning document intelligence, multi-scene storyboards, image/video generation, frontend and backend architecture, tests, and CI.

Do not use raw additions/deletions as an impact metric. GitHub reports large line movement because several PRs contain migrations, generated fixtures, or deletion of obsolete paths. Merged PR count, shipped systems, and end-to-end ownership are more honest signals.

Accuracy Notes

• “57 merged PRs” is verified against authenticated GitHub data as of July 6, 2026.
• “Four codebases” is verified from the authored PR set.
• The contribution calendar is incomplete because private contribution visibility is disabled.
• PR authorship proves contribution, not sole ownership. Use “built,” “delivered,” or “implemented” only for the parts personally authored; use “helped” where the team contribution cannot be cleanly separated.
• Employment type and exact title should match the signed agreement and LinkedIn before public publication.