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Em dash removal, nav/form/terms updates

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- Replace all em dashes with hyphens site-wide (22 files)
- Add Safety to nav
- Remove Express Interest button from enterprise header (form is the path now)
- Enterprise form: secondary headcount selection shows honest odds message; yes disables submit button
- Terms §5: add network layer indemnification (patent pending 64/036,821); no proprietary names
- Terms §4: Neuron Inference is live now, not Q3 2026
This commit is contained in:
Will Anderson
2026-04-29 17:14:56 -05:00
parent 235662c2a4
commit 51d2e64c22
22 changed files with 174 additions and 151 deletions
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src/environmental.el
+6 -6
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@@ -1,7 +1,7 @@
// components/environmental.el — Environmental impact section.
// components/environmental.el - Environmental impact section.
//
// The honest case for why local-first AI has a lower footprint than cloud AI.
// Not greenwashing — a structural argument. The benefit follows from the
// Not greenwashing - a structural argument. The benefit follows from the
// architecture; it wasn't engineered as a feature, but it's real.
fn environmental() -> String {
@@ -26,7 +26,7 @@ fn environmental() -> String {
</p>
<p class=\"reveal\" style=\"transition-delay:220ms;font-family:var(--body);font-weight:300;font-size:1rem;color:var(--t2);line-height:1.8;margin-bottom:1.25rem\">
Neuron&#39;s memory graph persists. The context tax &#8212; the repeated re-inference of who you are and what you&#39;re working on &#8212; doesn&#39;t accumulate. Over months of use, that compounds into a meaningful reduction in total computation.
Neuron&#39;s memory graph persists. The context tax - the repeated re-inference of who you are and what you&#39;re working on - doesn&#39;t accumulate. Over months of use, that compounds into a meaningful reduction in total computation.
</p>
<p class=\"reveal\" style=\"transition-delay:280ms;font-family:var(--body);font-weight:300;font-size:1rem;color:var(--t2);line-height:1.8\">
@@ -40,7 +40,7 @@ fn environmental() -> String {
<p style=\"font-family:var(--body);font-size:0.7rem;font-weight:600;letter-spacing:0.18em;text-transform:uppercase;color:rgba(0,120,84,.70);margin-bottom:0.75rem\">Local inference</p>
<p style=\"font-family:var(--body);font-weight:400;font-size:0.9375rem;color:var(--t1);margin-bottom:0.5rem\">Your GPU, already powered on</p>
<p style=\"font-family:var(--body);font-weight:300;font-size:0.875rem;color:var(--t2);line-height:1.7\">
When you run inference locally via Ollama, your device&#39;s GPU handles it &#8212; hardware that&#39;s already consuming power. No data center spins up a cluster for your query. No round-trip. No idle servers waiting at scale.
When you run inference locally via Ollama, your device&#39;s GPU handles it - hardware that&#39;s already consuming power. No data center spins up a cluster for your query. No round-trip. No idle servers waiting at scale.
</p>
</div>
@@ -54,7 +54,7 @@ fn environmental() -> String {
<div class=\"reveal card-dark\" style=\"transition-delay:300ms;padding:1.75rem 2rem;border-left:3px solid rgba(0,120,84,.40)\">
<p style=\"font-family:var(--body);font-size:0.7rem;font-weight:600;letter-spacing:0.18em;text-transform:uppercase;color:rgba(0,120,84,.70);margin-bottom:0.75rem\">Persistent context = less recomputation</p>
<p style=\"font-family:var(--body);font-weight:400;font-size:0.9375rem;color:var(--t1);margin-bottom:0.5rem\">Remembered once, retrieved — not re-derived</p>
<p style=\"font-family:var(--body);font-weight:400;font-size:0.9375rem;color:var(--t1);margin-bottom:0.5rem\">Remembered once, retrieved - not re-derived</p>
<p style=\"font-family:var(--body);font-weight:300;font-size:0.875rem;color:var(--t2);line-height:1.7\">
The structured memory graph means Neuron retrieves relevant context rather than re-inferring it from long conversation histories. Shorter, more targeted prompts. Less total token processing per useful outcome.
</p>
@@ -62,7 +62,7 @@ fn environmental() -> String {
<div class=\"reveal\" style=\"transition-delay:400ms;padding:1.25rem 1.75rem;background:rgba(0,0,0,.03);border:1px solid rgba(0,0,0,.07);border-radius:2px\">
<p style=\"font-family:var(--body);font-size:0.8125rem;font-weight:300;color:var(--t3);line-height:1.7\">
<strong style=\"font-weight:500;color:var(--t2)\">The honest picture:</strong> When you use Neuron with BYOK providers (OpenAI, Anthropic, Groq) or Neuron Inference, those queries travel to inference servers &#8212; that footprint exists. The savings come from the architecture: persistent memory and local-first design reduce the total computation required to get the same work done.
<strong style=\"font-weight:500;color:var(--t2)\">The honest picture:</strong> When you use Neuron with BYOK providers (OpenAI, Anthropic, Groq) or Neuron Inference, those queries travel to inference servers - that footprint exists. The savings come from the architecture: persistent memory and local-first design reduce the total computation required to get the same work done.
</p>
</div>