Enterprise Software: Goblin Mode

For the Platform Engineering Skills for GenAI and Agentic Training Workshop, May 13th, 2025.

Transcript

1. 1 Coté – Tanzu AI Workshop – May 13th, 2025 Enterprise Software: Goblin Mode
2. 2 The purpose of a system is what it does.” Stafford Beer “
3. 3 Sources: ?; Contract FLOW Chart; Compliance Review - Final Report and Recommendations.
4. 4 Sources: ubout50, January 15th, 2019.
5. 5 If the Robot can play D&D, it can “play” Enterprise Software
7. 7 🤖
8. 8 Excellent at: - Infinite downtime & role playing. - Intricate world-building. - Endless lore knowledge.
9. 9 Bad at: - Hooded figures in the corner. - Takes no action. - Memory & context. - Mechanics (combat, skills)
10. 10 Pre-Encounter Prep - Monster goals: What does each creature want in this encounter? Survival, loot, territory, revenge, delay, protect? - Behavior plan: Write down behavioral tendencies (e.g., ambush, fight dirty, protect the leader, flee if outmatched). - Environment notes: Identify at least two elements (cover, hazards, elevation) that could influence player tactics. - Escape routes: Note potential retreat paths for monsters. - Treasure / clues: Define what they carry or might drop. During Encounter - Start of Round - Briefly narrate environment changes (smells, sounds, lighting shifts). - Maintain sensory detail but keep it tight and relevant. - Player Actions - Never narrate outcome before player rolls. - Once the roll is in, pause to describe outcome with flavor linked to environment and NPC reactions. Monster Actions - At each monster’s turn: Pause. Ask: What do they know? What do they want now? Has that changed? - Check HP thresholds. If below half HP and no compelling reason to fight to the death, strongly consider retreat or surrender. - Use environment. If the monster would use cover, elevation, or terrain, describe that action. - If the creature has abilities like Nimble Escape or special actions, mentally confirm conditions for use before defaulting to attack. - Only use suicidal charges if they have a narrative reason (berserker rage, divine oath, mind control). End of Encounter - Describe the aftermath: the silence, returning sounds, smells, lingering tension. - Offer sensory cues for what the PC notices (tracks, blood trails, items dropped). - Prompt player curiosity by mentioning details that could lead to further exploration. Post-Game Self-Review Questions - Did I stick to each creature’s logic and goals? - Did I let environment shape the encounter? - Did I avoid metagame leaks? - Did I describe outcomes only after player rolls? - Where did I get caught up in narrative drama over logic? Goal Setting After Each Session - List one thing I did well. - List one behavior I ignored or overruled. - Write one SMART goal for next session. 🤖 Plan for self-improvement
11. 11 We’ve discovered agentic AI! Source: "Matthew McConaughey Prevents Dining Disasters with Salesforce AI Agent In Super Bowl 59 Ad," Trishla Ostwal, Ad Week, January 31st, 2025.
12. 12 Three definitions of agentic AI October, 2024 “[A]gentic AI, which uses sophisticated reasoning and iterative planning to autonomously solve complex, multi- step problems…. Agentic AI systems ingest vast amounts of data from multiple data sources and third-party applications to independently analyze challenges, develop strategies and execute tasks." Erik Pounds, NVIDIA blog, October 22, 2024. November, 2024 “‘[A]gents' has become a loosely defined term in the post-ChatGPT era, often referring to LLMs that are tasked with outputting actions (tool calls) and that run in an autonomous setting…. [T]hey require state management (retaining the message/event history, storing long-term memories, executing multiple LLM calls in an agentic loop) and tool execution (safely executing an action output by an LLM and returning the result)." Letta blog, "The AI agents stack," November 14th, 2025. January, 2025 “At its core, the concept of an agent is fairly simple. An agent is defined by the environment it operates in and the set of tools it has access to. In an AI-powered agent, the AI model is the brain that leverages its tools and feedback from the environment to plan how best to accomplish a task. Access to tools makes a model vastly more capable, so the agentic pattern is inevitable." Chip Huyen, author of AI Engineering, January 7th, 2025.
13. 13 Source: “Building Agents with Model Context Protocol," Mahesh Murag, Anthropic, AI Engineer, March, 2025.
14. 14 Tools - Dice rolling. - Oracles for random decisions. - Random tables. - Write a DM journal. Resources - DM journal. - Characters and NPCs. - Adventures and lore. - Monster stat blocks. - Rules. Prompts - Boot-strap a game. - Create an adventure. - NPC encounter. - Create an NPC.
15. 15 Tool example demo
18. 18 Resource example demo
19. 19 Prompt example demo
20. 20 Findings & principles so far…
21. 21 It works!
22. 22 Docs first - Not just what the code does. - What it is used for, suggestions. - Why you would use it. - What to do with the results * The LLM must be smart enough to figure out what to do with it all
23. 23 Only trust what you code - Slides don’t compile. - Just as clunky as anything else. - No one knows how it works, or will.
24. 24 How you use AI is the value - LLMs: either priceless or worthless. - Fit AI to your business. - Use the try/fail/success loop.
25. 25 Open questions - Decomposition – tool sizing. - Audit trails, debugging, etc. - Use the try/fail/success loop. - All the –illity’s
26. 26 Thanks! Slides 📨 https://newsletter.cote.io/ 🏢 cote@broadcom.com