WORKSHOP PORTFOLIO

AI & Data Workshop Offerings

Build internal capabilities and level up your workforce with structured, practical AI and Data programs.

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Strategic Scoping & SpecificationFor Founders

Architecture by Design: Scoping & Auditing Enterprise AI Systems

AI initiatives fail not due to bad code, but due to poorly scoped architectures. This session teaches product leaders and engineers how to translate ambiguous business bottlenecks into concrete technical blueprints using structured frameworks like The Spec Canvas.

Target Audience:Founders, PMs, CTOs, Architects
Duration:Half-Day Workshop

Key Topics Covered:

  • Ambiguity Resolution & Requirements Mapping
  • The Spec Canvas Framework
  • Stack Selection (LLM vs. RAG vs. Agentic Networks)
  • Cost & Latency Projection Modeling
Concrete Deliverable:
Completed Spec Canvas Blueprint
Production Agent EngineeringFor Engineers

Agentic Governance: Observability, Traceability, & Cost Guardrails

Moving autonomous agents from a local sandbox to production requires strict control. Participants learn how to build stateful multi-agent networks that are traceable, cost-controlled, and fully auditable using tools like LangGraph, OpenTelemetry, and Langfuse.

Target Audience:Developers, Tech Leads, DevOps, Data Engineers
Duration:Half-Day Workshop (Can be tailored to 1 or 2-day sessions)

Key Topics Covered:

  • Stateful Graphs (LangGraph topologies & validation)
  • Observability (OpenTelemetry & Langfuse tracing)
  • Output Engineering (JSON schemas & self-healing errors)
  • Financial Guardrails (token bounds & active rate limits)
Concrete Deliverable:
Langfuse-Integrated Stateful Agent Template
Workforce Enablement & AutomationFor Business & Ops

Low-Code / No-Code AI Workflows: Building the "Capability Capital" Workforce

Bridging the productivity gap for non-developers. This hands-on workshop equips operations, support, and business teams with the framework to leverage advanced AI tools (like Lovable, Make, and Zapier) to automate repetitive workflows.

Target Audience:Corporate Employees, Business Operations, Founders, Marketing Leads
Duration:Half-Day Workshop

Key Topics Covered:

  • The Capability Curve (chat loops vs. background pipelines)
  • Advanced Prompt Upgrading (role-play & context injection)
  • Functional Prototyping (databases & interfaces in Lovable)
  • Secure Automation (safe data connections & sheets)
Concrete Deliverable:
Working Automation Pipeline
AI-Accelerated Frontend DevelopmentFor Engineers

Velocity by Design: CSS, Design Systems, & Frontend AI Generation

Visual coherence and usability break down instantly when generating layouts with AI unless a constraint layer exists. This workshop shows designers and frontend engineers how to build a tokenized CSS design system that enables AI generators (like Claude Code, Lovable, v0) to write beautiful, consistent code without visual debt.

Target Audience:Frontend Developers, UI/UX Designers, Product Engineers
Duration:Half-Day Workshop

Key Topics Covered:

  • AI-Friendly CSS (HSL palettes & typography scales)
  • System Constraints (guiding AI models to respect grids)
  • Hover & Micro-Animations (making generated elements premium)
  • Preventing Vibe Coding (enforcing visual styling guardrails)
Concrete Deliverable:
Tokenized CSS Design System Boilerplate
KPI Architecture & VisualizationFor Business & Ops

KPI & Telemetry Blueprints: Building Actionable Decision Dashboards

Dashboards fail when they track vanity metrics instead of core decision indicators. This workshop covers how to connect data pipelines (e.g., BigQuery, SQL) to BI tools (Tableau, Power BI, Streamlit) to display actionable, context-rich data for both operations and executives.

Target Audience:Business Analysts, Operations Managers, Data Analysts, Product Directors
Duration:Half-Day Workshop

Key Topics Covered:

  • Metric Architecture (leading vs. lagging indicators)
  • Data Ingestion Design (flows from DB to BI endpoints)
  • Dashboard UX (structural grids & visual hierarchy)
  • Anomaly Alerting (Slack/Email triggers for deviations)
Concrete Deliverable:
Dashboard Wireframe Spec
MLOps & Model LifecycleFor Engineers

Production-Grade ML: Architecting Resilient & Auditable Prediction Models

Moving machine learning from fragile research notebooks to robust production pipelines. Learn how to train, evaluate, package, and monitor predictive models (classification, regression, time-series forecasting) that remain stable over time.

Target Audience:Data Scientists, ML Engineers, Technical Product Managers
Duration:Half-Day Workshop (Can be tailored to 1 or 2-day sessions)

Key Topics Covered:

  • Robust Pipelines (modular training & feature engineering)
  • Metric Standardization (automated verification benchmarks)
  • Drift & Performance Checks (prediction & data shifts)
  • Deterministic Fallbacks (safety nets for anomalies)
Concrete Deliverable:
MLOps Deployment Checklist
Legacy System TranslationFor Engineers

The Migration Blueprint: Modernizing Legacy SAS & R to Python

Highly technical, high-value calculations locked in legacy SAS/R scripts are expensive and hard to maintain. This technical session details how to leverage AI tools (such as Claude Code) to translate legacy code bases into clean, performant, and unit-tested Python packages without losing mathematical equivalence.

Target Audience:Lead Data Scientists, Finance/Insurance Engineering Teams, Data Architects
Duration:Half-Day Workshop (Can be tailored to 1 or 2-day sessions)

Key Topics Covered:

  • Equivalence Frameworks (automated math testing loops)
  • AI Migration Workflows (prompts for macros & DATA steps)
  • Modular Package Structure (maintainable, idiomatic Python)
  • Regression Integration (automated checks for semantic drift)
Concrete Deliverable:
SAS-to-Python Migration Playbook

Book a Custom Workshop

Ready to accelerate your team's capability capital? Request a custom session tailored to your industry, tech stack, and operational bottlenecks.

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