AI Literacy for the Modern Workplace
Course + quiz
bilingual reusable assets for self-study, facilitation, and understanding checks
Enablement means giving a team practical conditions to use AI without always depending on outside help. The package turns recurring decisions and tasks into editable playbooks, templates, rubrics, and guides with a defined audience, validation path, owner, and maintenance rule.
AI Literacy for the Modern Workplace
Course + quiz
bilingual reusable assets for self-study, facilitation, and understanding checks
Lapidador
23 techniques
a prompt-engineering repertoire turned into practical guidance inside a proprietary product
1-3 weeks
HR/L&D, corporate universities, and team managers
A validated, editable package ready for maintenance by its owners
Playbooks / assets
Formats are agreed based on the audience's channel and routine. Delivery includes editable source files and ready-to-use reference versions when appropriate; a platform, LMS, publication, or integration is included only when explicitly contracted.
Before final delivery, examples, language, and criteria are reviewed by users or subject-matter experts nominated by the company. Acceptance records what was reviewed, known gaps, and the context for which each asset was approved.
The company names an owner and receives source files, a versioning convention, and review guidance. Recurring maintenance is not assumed in the initial package, but it can be contracted separately.
To talk about this service, write to oi@dorly.com.br.
Before commissioning training, technology, or metrics, this engagement organizes the decisions: where to start, which pilot fits the context, who is accountable for it, and what needs to happen next. The scope ends with an approved design; execution, integrations, and operations are later workstreams.
Purchasable formats for a synchronous decision-making and practice experience: executive session, hands-on workshop, or modular path. Each format combines facilitation, real tasks, and feedback during the activity; it is not a generic lecture or a promise of behavior change without follow-through.
MVPs, automations, and demos to test an idea's value before scaling — using tools like ChatGPT, OpenAI API, n8n, TypeScript, and AWS to prove what works with a tight scope.
I design the model connecting reaction, learning, behavior, and impact without treating correlation as causation. The work defines what to measure, where the data comes from, and how to read the signals; business outcomes and integrated dashboards depend on data quality and later implementation.