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Give judges a clear story for Sky Lattice: AI as front door, durable intent and decisions under the copilots. Co-authored-by: Cursor <cursoragent@cursor.com>
77 lines
3.6 KiB
Markdown
77 lines
3.6 KiB
Markdown
# Sky Lattice — AI Hackathon Pitch (Narrative)
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Speaker notes and copy you can trim. Slides: open [`index.html`](index.html) in a browser (`←` / `→`).
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---
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## 30-second pitch (elevator)
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Snowflake gives you a blank cloud. Every customer, we rebuild isolation, RBAC, and data-product layout by hand — lately with AI chats that forget *why* we made exceptions. **Sky Lattice** is the layer under the copilots: a versioned blueprint, customer intent, durable decisions, and a deterministic planner. AI fills the forms; Terraform still ships the platform.
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---
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## 2-minute pitch (spoken narrative)
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**Hook.**
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We’ve all felt this: Snowflake looks empty, best practices live in people’s heads, and “let’s ask the LLM” turns into a week of clever SQL that nobody can re-run with confidence.
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**Problem.**
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Setting up a real platform — environments, zones, roles, warehouses, service users — is repetitive but never identical. Today’s AI-assisted workflow accelerates the typing. It does **not** create institutional memory. Terraform state tells you what exists. The next chat session still re-litigates judgment.
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**Insight.**
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Don’t fire the LLM. Put a lattice under it. Codify the recipe. Capture deviations as decisions. Make the agent drive files and a CLI — not invent production IAM from scratch every time.
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**Product.**
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Sky Lattice is that lattice:
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- a **blueprint** of how *we* set up Snowflake
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- per-customer **intent** and **decisions**
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- **`platformctl`** to validate, plan, drift, and apply
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- optional **Cursor/Claude skills** as the natural-language front door
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Same path for greenfield and brownfield: interview → durable artifacts → deterministic plan.
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**Why us / why now.**
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Platform teams are already using AI for infra. The winners won’t be who prompts harder — they’ll be who productizes the delivery system. We’re turning consulting tribal knowledge into software.
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**Status.**
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Working v0.1 scaffold: wizard, decision store, planner, inventory drift, skills, demo customers. Next: live Terraform→Snowflake vertical slice.
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**Close.**
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Sky Lattice — structure under the copilots. Help us harden it.
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---
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## Slide-by-slide talking points
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| # | Slide | Say this |
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|---|---|---|
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| 1 | Title | Name + one-liner. Don’t over-explain yet. |
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| 2 | Problem | Blank slate + amnesiac AI. Point at cost: time, inconsistency, audit. |
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| 3 | Insight | Quote beat. Pause. |
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| 4 | Product | Show the flow: NL → skill/intent → plan → TF. |
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| 5 | Demo arc | Walk Acme story; emphasize *decision* as the magic. |
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| 6 | Differentiation | Four cards — AI placement, memory, deviation, friction. |
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| 7 | Market | Consultancies + internal platform teams. |
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| 8 | Traction | Honest v0. What works / what’s next. |
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| 9 | Ask | Design partners / judges who feel the pain. |
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---
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## Objection handling
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| Objection | Response |
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|---|---|
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| “Just use Terraform modules.” | Modules are the engine. We add intent, decisions, wizard, policy, and an AI contract so modules get used the same way every time. |
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| “Just use the LLM.” | We do — as the driver. Without durable intent/decisions, you get speed without repeatability. |
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| “SnowDDL / DataOps.live already exist.” | Engines and platforms exist. Our IP is *our* blueprint + engagement memory model — and it’s agent-native. |
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| “v0 doesn’t apply to Snowflake yet.” | True and intentional. We proved the control plane first; next slice is live apply. Judges should score the architecture + working demo path. |
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---
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## Taglines (pick one)
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- Structure under the copilots.
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- Snowflake platforms with memory.
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- Codify. Tweak. Maintain.
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- AI drives the forms. The lattice holds the truth.
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