Precarious Infrastructure
Infrastructure teeters at the brink of collapse — but people carry on. Maybe that sounds like your team's software. Here's how to stop surviving and start building with intention.
Insights on software architecture, AI engineering, data privacy, and building efficient systems.
Infrastructure teeters at the brink of collapse — but people carry on. Maybe that sounds like your team's software. Here's how to stop surviving and start building with intention.
Learn to work with LLMs as context synthesizers, not instruction followers. Why command-based prompting fails and how information flow shapes better outputs.
Most software projects fail because teams build the wrong thing. How engineers can own requirements and build solutions that actually solve problems.
Exploring how the foundational principles of Unix continue to guide modern AI development, from modularity to transparency and human-centric design.
How we eliminated JSON parsing overhead and achieved 10-100x faster DeBERTa tokenizer startup with a custom binary format for production ML inference.
For forty years, engineering teams optimized for speed. Then came privacy laws. How the disconnect between performance and compliance is reshaping software.
Legacy privacy approaches stifle healthcare software innovation. How dynamic privacy protection unlocks better UX, lower costs, and faster development.
When doing the right thing drives wrong results. How zero-copy architecture transforms healthcare data compliance from expensive constraint to foundation.
Building AI systems that deliver real business value requires navigating a complex landscape of technical considerations that directly impact your bottom line.
Many companies demo AI capabilities they can't afford to operate. The sobering reality of AI economics and sustainable alternatives.
Your model is only as effective as the infrastructure it runs on. Learn how the right architecture can dramatically improve AI performance and cost-efficiency.
On-premises AI offers better control, data privacy, and long-term cost benefits vs. cloud alternatives. How to implement on-prem AI effectively.
Despite billions in investment, current ML approaches fail to deliver. Why 'bigger is better' has hit its ceiling and how targeted intelligence can help.
Moving beyond impressive AI demos to real business value requires infrastructure, talent, and expertise. How to achieve actual ROI from AI investments.
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