From 4f86848ebbde4db87c79f9a770df27c622cbd706 Mon Sep 17 00:00:00 2001 From: Scott Scoble Date: Wed, 29 Apr 2026 17:26:01 -0700 Subject: [PATCH] =?UTF-8?q?Remove=20emojis=20from=20landing=20page=20?= =?UTF-8?q?=E2=80=94=20too=20AI-looking?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- landing/index.html | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/landing/index.html b/landing/index.html index 1c7b9d3..fa38a1a 100644 --- a/landing/index.html +++ b/landing/index.html @@ -212,19 +212,19 @@
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📝 SpeckDL Language

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SpeckDL Language

A constraint-based specification language that defines what a system does, not how. Specs are small, stable, and machine-verifiable — the audit surface for regulated systems.

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🔗 Dark Provenance

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Dark Provenance

A methodology where every behavior traces back to its source — a regulation, a design decision, a conversation. The provenance graph is always present, materialized on demand for audits or debugging.

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🧩 Reference Implementations

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Reference Implementations

Minimal reference tools for SpeckDL parsing, Z3 constraint verification, and provenance graph generation. The building blocks for tooling, not a production system.

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🏗️ Ecosystem-First

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Ecosystem-First

The standard is the foundation. Consulting, SaaS tooling, and compliance APIs will build on it — validated through real-world use before they ship.

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📦

Small and Stable

Specs are orders of magnitude smaller than the code they generate. They change less often. The audit surface stays tractable.

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🔍

Review the Boundary

If Speck→WASM compilation preserves semantics, human review at the spec boundary satisfies assurance requirements.

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AI-Generated, Human-Owned

Agents generate code. Humans own specifications. The chain of custody for intent stays intact.