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Deep Engineering #22: Richard D Avila on Why AI Systems Need Architecture

The prototype–production gap in AI—and the architectural discipline to close it.
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Quantum Computing for Leaders (Online)
Accelerate your organization’s quantum readiness—build leadership skills, secure your enterprise, and unlock innovation with a two-day, executive-grade…
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From Prototype to Production: Why AI Systems Need Architecture Discipline
How architecture makes model- and data-driven systems production-ready
 • 
Richard D Avila
Deep Engineering #21: Mojo–Python Interop in Late 2025 with Ivo Balbaert
Free-threaded CPython meets Mojo 0.25.6—practical patterns for calling across the Python↔Mojo boundary.
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Converting a Python program to Mojo, and exploring how they interact.
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Opinions held lightly, business outcomes held closely: what “good taste” means with AI in the loop.
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Deep Engineering #20: When Mapping Becomes the Algorithm with Elías F. Combarro & Samuel González-Castillo
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Interviews

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From Enablement to Reliability: How Platform Engineering Aligns with SRE Goals – A conversation with Sean P Alvarez and Ajay Chankramath
On distinguishing SRE from Platform Engineering, building developer-first platforms, and the practical lessons behind treating platforms as products.
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Sushma Reddy
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Srishti Seth
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AJ Chan
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Pragmatic Clean Architecture in Python: A Conversation with Sam Keen
Applying DDD and the dependency rule in real-world Python—keeping frameworks at the edge, modeling with dataclasses/Pydantic, and using AI without…
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Divya Anne Selvaraj
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Inside Go Systems Programming: A Conversation with Mihalis Tsoukalos
Concurrency patterns, runtime optimizations, and memory management in modern Go
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Divya Anne Selvaraj
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Mihalis Tsoukalos
Designing for Decades: A Conversation with Alexander Kushnir on Longevity, Maintainability, and Embedded Systems at Scale
A MedTech systems engineer unpacks what it means to build software that must survive regulatory cycles, hardware obsolescence, and engineering turnover.
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Divya Anne Selvaraj
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Building Emergency-Ready AI: A Conversation with Tony Dunsworth
How open models, synthetic data, and lightweight infrastructure are enabling secure, cost-effective AI for 911 systems and public safety operations.
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Inside LLVM Backends: A Conversation with Quentin Colombet
From instruction selection to MLIR: how modern compilers generate code—and what’s next for LLVM backend development.
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