# Media Pitch Variants

## 1) Research/Academic Reporter
Subject: A formal trigger for **growth** in neural architectures

Hi {FirstName},

Most continual‑learning stories still assume static models. GrowNet flips that: it grows structure when data looks meaningfully new—slots, layers, or regions—only when a formal utility test says specialization beats further adaptation. Think “decision‑theoretic growth events,” with full logging to trace *why* the model changed. Public repo + docs here: https://github.com/nectario/grownet. Happy to share a short explainer and early benchmarks.

Best,  
Nektarios

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## 2) Developer/Infra Reporter
Subject: When to **add structure** instead of fine‑tuning

Hey {FirstName},

We’re exploring a practical rule for growth in production‑style models: allocate new capacity when novelty hits and specialization should win. It’s auditable (growth events are logged), measurable (utility deltas), and reversible (merge/prune). Could be relevant for teams battling drift. Code + docs: https://github.com/nectario/grownet. Open to a quick briefing or demo.

Thanks!  
Nektarios

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## 3) Newsletter/Community
Subject: A simple Golden Rule for models that grow

Hi {FirstName},

GrowNet proposes a Golden Rule for structural growth under novelty: *grow iff specialization’s expected utility > adaptation inside the current parameters.* We’re sharing code, a plain‑language explainer, and early tasks (MNIST variants, Morse code). Might be a neat item for your readers interested in continual learning + systems thinking: https://github.com/nectario/grownet.

Cheers,  
Nektarios

**Follow‑up (3–4 days later):**
Just floating this back to the top of your inbox—happy to send a 2‑page explainer or a short Loom walkthrough.
