Theme 01
From AI experiments to governed operating workflows
How to move beyond isolated prompts and build AI systems with structured inputs, controlled outputs, review gates, audit trails, ownership, and rollback paths.
Speaking / Demos / Enterprise AI Workflows
Practical AI talks with the architecture underneath.
I speak from the builder seat: how AI systems are framed, prototyped, governed, tested, and turned into useful workflows for marketing automation, translation, campaign intelligence, and enterprise operations - with the controls senior teams need to trust the work.
Session Themes
Built for marketing leaders, enterprise teams, and serious AI builders.
Theme 02
AI systems for marketing automation and campaign operations
Practical AI patterns for translation workflows, campaign build support, marketing intelligence, reporting, asset operations, quality control, and governance.
Theme 03
Why demos change the AI conversation
A build-led talk on credibility, visible systems, proof-of-work, and how demos change the conversation with both technical teams and senior stakeholders.
Theme 04
Enterprise AI reality: trust, review, audit, and fallback
What needs to exist around the model: security, source control, approval states, data quality, logging, auditability, exception handling, and human ownership.
Session Formats
Sessions can be technical, strategic, or demo-led.
01
Live demo session
Show the system, explain the architecture, walk through the workflow, and make clear what is live, what is prototype, what is controlled, and what comes next.
02
Decision-maker briefing
For senior teams who need to understand where practical AI creates value, where risk sits, and what governance is required before scaling.
03
Builder workshop
A hands-on session for AI builders, developers, marketers, and operators who want to design workflow-first AI systems with real controls.
Session Value
Built to land with both technical teams and senior stakeholders.
Architecture
Show the control layer
The session explains the workflow, data path, review model, and delivery route - not just the model output.
Business value
Connect AI to operations
The focus is practical value: faster workflows, fewer handoffs, clearer review states, and better use of specialist time.
Risk control
Make trust visible
Review gates, audit trails, fallback paths, quality checks, and human ownership are treated as core parts of the system.
Demo proof
Use working examples
The conversation is grounded in real build surfaces: Translation AI, Marketing Intelligence AI, and the architecture decisions behind them.
Demo Track
The strongest sessions show the system, not just the theory.
The pl8ypus speaking track is designed around evidence: status panels, workflow diagrams, data quality gates, architecture options, and demos from the two active systems.
Audience Fit
One build story, different decision points.
AI builders
How the system is built
Architecture, tool choices, model routing, ingestion strategy, frontend simplicity, and why the control layer matters more than the demo polish.
Marketing leaders
Why it changes operating work
Efficiency gains, clearer review states, repeatable operations, faster insight, and better use of specialist human time in campaign and content workflows.
Enterprise teams
How to make AI controllable enough
Human review, source control, logs, protected terms, security boundaries, data classification, audit trails, and failure recovery.
Contact
Bring a practical AI systems story to the room.
Use the contact form for events, demos, workshops, panels, podcasts, or practical AI workflow sessions.