sky-lattice/docs/pitch/PITCH.md
VG 3e4f8577bd Refine pitch opening with ice crystal lattice metaphor.
Lead with the nature analogy so Sky Lattice reads as structure for a blank Snowflake account.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-07-15 02:02:57 -04:00

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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 peoples heads, and “lets 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. Todays 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.
Dont 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
  • platformctl to 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 wont be who prompts harder — theyll be who productizes the delivery system. Were 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 / whats 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 its agent-native.
“v0 doesnt 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.