sky-lattice/docs/pitch/PITCH.md

Sky Lattice — AI Hackathon Pitch (Narrative)

Speaker notes and copy you can trim. Slides: open index.html in a browser (← / →).

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30-second pitch (elevator)

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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2-minute pitch (spoken narrative)

Hook.
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.

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 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.

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 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.

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Slide-by-slide talking points

#	Slide	Say this
1	Title	Name + one-liner. Don’t over-explain yet.
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.

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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.

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Taglines (pick one)

• Structure under the copilots.
• Snowflake platforms with memory.
• Codify. Tweak. Maintain.
• AI drives the forms. The lattice holds the truth.