Labs
Outcome-first, hands-on experiments: build a website, model a financial strategy, ship an internal tool, create a proposal, red-team critical work, and other real use cases.
WL / 001
Learning by doingWorkingLab is a field guide for becoming AI-native. Follow complete experiments, see why the work succeeds, and pull in the fundamentals exactly when you need them.
Choose an outcome. We’ll assemble the intelligence, context, a stack of tools based on your preferences, and the human judgment needed to reach it.
Build the mental model — the pattern machine, the window, and why models differ — before any tool matters.
Set up ChatGPT and Claude side by side, make one thing in each, and leave with your own translation card.
Learn the shapes AI failure takes — and the window move that answers each one — before you meet them in the wild.
Turn a raw client call into a polished, deployed site.
Extract decisions, owners, timelines, and a living project brief.
Go from a broad question to a reliable, source-backed point of view.
Transform discovery notes into a persuasive, client-ready proposal.
Interrogate a dataset, test scenarios, and surface decision-ready insights.
Prototype and deploy a useful app without waiting on a backlog.
Triage messages, draft replies, and protect the decisions that matter.
Give AI a durable source of truth it can reliably work from.
Move from customer pain to testable interface and feedback plan.
Create the strategy, concepts, assets, and production workflow together.
Split complex work across focused agents without losing the thread.
Use independent review loops to find assumptions, gaps, and errors.
Every rival's offer and pricing in one table — each cell traceable to a source.
You won’t memorize a tool, but you’ll learn to design the conditions for the tool to do the work.
No prerequisites. Pause any experiment, learn a concept in minutes, and return to the work without losing your place.
WorkingLab helps you move from AI-curious to AI-native by learning through real work.
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WorkingLab is not a course catalog. Members enter through practical Labs built around real outcomes, then use the Library, live experiments, and cohorts as needed.
Outcome-first, hands-on experiments: build a website, model a financial strategy, ship an internal tool, create a proposal, red-team critical work, and other real use cases.
Searchable reference for platforms, tools, skills, concepts, and glossary terms. Fundamentals are available just in time rather than as prerequisites.
Regular sessions where practitioners attempt meaningful work in real time — mistakes, inspection, and refinement included.
Time-bound groups that work through larger challenges together and translate Labs into their own work. Begins with a pilot cohort after launch.
For people who already know how to do their jobs, but want to explore what they can do now that AI has changed what is possible.
Draft launch pricing — nothing is for sale yet, and there is no account to create and no payment to make. When membership opens it will be governed by the Terms & Conditions.
See the proposed member setup.
Simulated access first, then the one-time context that would carry across every experiment. No account is created, no payment is possible, and no answers are saved or sent.
Preview member onboardingOne individual membership and one team membership — no tier proliferation. Labs and Live Experiments are included; bespoke cohorts and custom Labs are premium services.
Be first to know when the founding cohort opens.
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