Lead with the nature analogy so Sky Lattice reads as structure for a blank Snowflake account. Co-authored-by: Cursor <cursoragent@cursor.com>
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Sky Lattice — AI Hackathon Pitch (Narrative)
Speaker notes and copy you can trim. Slides: open index.html in a browser (← / →).
30-second pitch (elevator)
In nature, a snowflake is made of an ice crystal lattice. Sky Lattice is that structure for a Snowflake account. Snowflake itself is a blank slate. Every customer, we rebuild platforms by hand — lately with AI chats that forget why. Sky Lattice is the layer under the copilots: blueprint + intent + decisions + deterministic plan. AI fills the forms; Terraform still ships the platform.
2-minute pitch (spoken narrative)
Hook.
In nature, a snowflake is made of an ice crystal lattice. Sky Lattice is that structure for a Snowflake account — because the product itself is a blank slate. 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.
Problem.
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.
Insight.
Don’t fire the LLM. Put an ice crystal lattice under it — structure that holds shape. Codify the recipe. Capture deviations as decisions. Make the agent drive files and a CLI — not invent production IAM from scratch every time.
Product.
Sky Lattice is that lattice:
- a blueprint of how we set up Snowflake
- per-customer intent and decisions
platformctlto validate, plan, drift, and apply- optional Cursor/Claude skills as the natural-language front door
Same path for greenfield and brownfield: interview → durable artifacts → deterministic plan.
Why us / why now.
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.
Status.
Working v0.1 scaffold: wizard, decision store, planner, inventory drift, skills, demo customers. Next: live Terraform→Snowflake vertical slice.
Close.
Sky Lattice — structure under the copilots. Help us harden it.
Slide-by-slide talking points
| # | Slide | Say this |
|---|---|---|
| 1 | Title | Nature metaphor first (ice crystal lattice), then blank-slate problem + product one-liner. |
| 2 | Problem | Blank slate + amnesiac AI. Point at cost: time, inconsistency, audit. |
| 3 | Insight | Quote beat. Pause. |
| 4 | Product | Show the flow: NL → skill/intent → plan → TF. |
| 5 | Demo arc | Walk Acme story; emphasize decision as the magic. |
| 6 | Differentiation | Four cards — AI placement, memory, deviation, friction. |
| 7 | Market | Consultancies + internal platform teams. |
| 8 | Traction | Honest v0. What works / what’s next. |
| 9 | Ask | Design partners / judges who feel the pain. |
Objection handling
| Objection | Response |
|---|---|
| “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. |
| “Just use the LLM.” | We do — as the driver. Without durable intent/decisions, you get speed without repeatability. |
| “SnowDDL / DataOps.live already exist.” | Engines and platforms exist. Our IP is our blueprint + engagement memory model — and it’s agent-native. |
| “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. |
Taglines (pick one)
- Structure under the copilots.
- Snowflake platforms with memory.
- Codify. Tweak. Maintain.
- AI drives the forms. The lattice holds the truth.