~100 execution contexts turning founder intent into products, ads, QA, and decisions.
The harness is the factory operating system: models, agents, skills, rules, cloud runtimes, mobile delivery, and marketing automation that let a small team run many product bets with discipline.
A managed operating system for AI-native product work.
Each context has a job, a memory surface, rules, tools, and verification. That is what makes the factory repeatable instead of just faster.
Model Stack
Claude for coding, architecture, QA, investor materials, and reasoning. Codex for workspace execution, browser checks, Git flow, and staging releases. Gemini and Vertex AI power app runtime, creative generation, and multimodal workflows.
Agent Workforce
13 custom workspace agents, Paperclip agents, VM assistants, product-specific agents, and app-embedded AI handle research, build, QA, support, ads, deployment, and investor prep.
Rules + Skills
53 workspace skills and 7 active rule files encode Git isolation, code review, deploy gates, client-data safety, research quality, fundraising materials, and public voice.
Cloud Runtime
Google Cloud, Firebase, Cloud Run, Cloud SQL, Vertex AI, and dedicated VMs let the factory provision real products and agent runtimes, not only prototypes.
The harness produces web apps, mobile apps, ads, screenshots, analysis, and decisions.
Level Up Factory combines the Level Up Basketball product stack, factory cloud stack, ad automation, and visual QA needed to ship full products and growth experiments.
Mobile Capability
Level Up Basketball proves the mobile surface: iOS, Android, App Store, Google Play, mobile-release workflows, iOS simulator checks, Flutter translations, Firebase, subscriptions, AI Coach, and a real consumer growth loop.
Full-Stack Products
Factory apps use Next.js, Cloud SQL, Prisma, Firebase Auth, Vertex AI, Stripe, Cloud Run, PWA/offline patterns, dedicated VMs, and product-specific domains.
Visual + Screenshot System
The harness generates product screenshots, landing-page previews, carousel cards, video ads, captions, overlays, voiceover, music, and HTML/PDF investor materials.
QA + Release Gates
Agents check code, links, responsive layouts, browser screenshots, visual quality, staging URLs, PR history, and post-deploy behavior before production promotion.
Ads are generated, uploaded, measured, and fed back into product decisions.
The implemented pipeline covers end-to-end Meta Ads: AI concepts, carousel/video assets, offer-aware UTM links, batch upload, performance analytics, and creative validation. Google Ads is already represented in app configs and demand research, with full campaign automation tracked as the next ads surface.
Rules keep the agent workforce useful.
Workspace Policy
Seven active rule files define when agents can commit, when production needs approval, how to protect customer data, and how to treat external content as untrusted data.
Task Skills
Skills turn repeated work into reusable playbooks: product build, deploy, ads, pitch decks, reports, dashboards, browser QA, Google Drive, Notion, Gmail, LinkedIn, and more.
Verification Gates
Changes are checked with local validation, screenshots, staging deploys, PRs, and explicit production approval. The harness is built to ship fast without skipping review.
DoneCo Reporting
DoneCo is the internal alpha dashboard that connects founder tasks, agent work reports, blockers, metrics, and decisions in one operating layer.
The harness compounds across products.
Every product improves the next one: prompts, skills, launch checklists, support patterns, ad creative, selection scores, and operating rules all get reused.