Choose a job worth productising
Recurring, valuable, digitally actionable work with a recognisable result and meaningful cost of repetition or error.
From opportunity to product
AI workbenches lower the barrier to research, design and development. A founder need not begin as the domain expert—but the product must acquire trustworthy domain truth and prove itself in real work.
Recurring, valuable, digitally actionable work with a recognisable result and meaningful cost of repetition or error.
Specify the user, outcome, inputs, outputs, exceptions and prohibited actions. Build truth from experts, official rules and real examples.
Give interpretation and adaptive creation to agents; give state, approval, validation and audit to deterministic controls; keep people responsible for goals and consequential decisions.
Confirm that file, API, browser or human-handoff paths genuinely exist, including stop conditions for identity, verification and platform risk.
Establish output quality, then safe action, then full-cycle efficiency, then adoption by someone outside the creation team.
Separate product from customer data; version, sign, license, install, update, migrate and support it.
A clean, signed and versioned capability with documentation, compatibility notes and an uninstall path.
The adopter's goals, brand, rules, account map, operational state and results—kept separate from the generic product.
Licences, seats or device rules, update entitlement and support define legitimate use without requiring source-code transfer.
WorkPacks are designed to operate close to the adopter's own work assets, inside an AI workbench. Product components may remain packaged and closed-source, while customer content and secrets remain locally or enterprise controlled.
C Community's planned WorkPack Hub will eventually connect discovery, licensing, distribution, updates and care. It is a strategic direction, not a service we claim is already open.