AI Architect | Tech Advisor
Founder @ https://sistava.com Where You Hire AI Employees
while ('zalt' == ALIVE) {
📚️ learn(*);
💻️ code(24, 7);
🌍️ live(0xEXP10RE);
}
| site | https://zalt.me |
Curious how JAX actually wires gradients, JIT, and vectorization together? This piece breaks down the transformations engine behind JAX’s behavior.
When Missing Files Break Mental Models digs into what happens when your code layout lies to you. If paths don’t match expectations, how far does the damage go?
Working with autoregressive generation loops? "When Autoregressive Loops Stay Friendly" explores keeping them fast without making them painful to work on.
👉 https://zalt.me/blog/2026/06/autoregressive-loops-friendly
Struggle with how Pydantic stays so easy to use despite its depth? “The Facade That Makes Pydantic Feel Simple” breaks down the idea behind that simplicity.
Lazy Pipelines, Fast Backends digs into how to keep data pipelines easy to write while still hitting serious performance in the backend.
How do you go from abstract models to guarantees you can rely on in production? “Symbolic Shapes, Real‑World Guarantees” digs into that bridge.
Curious how Llama actually thinks about time inside attention? This breakdown of how it treats temporal information in its attention stack is worth a read.
Transformers feel like magic, but they’re not. Curious how a simple registry pattern quietly powers their behavior behind the scenes?
👉 https://zalt.me/blog/2026/05/registry-pattern-transformers
Most agentic #AI memory is built for short-lived chat. Running 1K #agents in production changes the game entirely—because facts change over time.
Vector search fails when user preferences decay or shift. This 7-layer memory architecture fixes it:
1️⃣ Working Mem
2️⃣ Conversation Mem
3️⃣ Episodic Mem
4️⃣ Semantic Mem
5️⃣ Knowledge Mem
6️⃣ Procedural Mem
7️⃣ Checkpoints Mem
Most event-driven systems scatter state across queues, caches, and threads. “The Event Loop as a Single Source of Truth” argues for one clear authority instead.
