FOUNDATIONAL LABS
Four instructor-led Labs (180 minutes each), each covering two foundational GenAI workflows. Function-agnostic by design — every cohort applies them to its own context.
The gap
Most teams have tried GenAI individually. Turning that into reliable, shared, day-to-day work habits is a different problem.
Webinars, demos, and tutorials raise awareness but don't change behavior. Without practice on real work, prompting and verification habits stay personal and inconsistent.
"How to use ChatGPT" is the same for everyone, whether the work is hiring decisions or board memos. Without workflow-specific practice, teams leave training unable to apply what they heard.
Teams need a structured, low-risk space to practice task framing, verification, and data-handling habits before consequences are on the line.
The Labs
Each Lab is a 180-minute, instructor-led session covering two related GenAI workflows. Your cohort applies them to real work. See the Lab format at /labs for per-Lab structure.
Plan → Outline → Produce
Structure a deliverable from scratch, scoping the task, generating an outline, and producing a polished first draft ready for review.
Ideate → Expand → Refine
Generate initial concepts, expand on the strongest ideas, and refine them into actionable proposals.
Draft → Verify → Share
Take a rough draft through verification and refinement, checking for accuracy, hallucinations, and tone before sharing with stakeholders.
Review → Redline → Approve
Accelerate document review by identifying issues, suggesting redlines, and preparing approval-ready summaries.
Summarize → Cite → Mark gaps
Distill long documents into actionable summaries with proper citations and flagged risks for compliance and decision-making.
Extract → Compare → Explain
Pull structured data from documents, compare across sources, and generate clear explanations of differences.
Map → Score → Articulate
Map decision options against explicit criteria, score systematic comparisons, and articulate the tradeoffs that drive a clear recommendation.
Frame → Compare → Recommend
Frame decision criteria, compare options systematically, and produce well-reasoned recommendations.
Skill areas reinforced
Every Lab reinforces the same skill model used across AGASI products. The Pulse measures these; Playbooks codify them; Labs build them through practice.
Task framing, context setting, and constraint definition.
Checking outputs for accuracy, hallucinations, and completeness.
Handling sensitive information safely when using GenAI tools.
Bias awareness, attribution, and organizational policy compliance.
Adapting outputs to real workflows and intended audiences.
Tell us about your team and we’ll come back with a cohort fit, dates, and how the founding cohort works.