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From Karpathy's LLM Wiki to a Working Second Brain: My Implementation with Amazon Quick Desktop
Karpathy's LLM Wiki framework reframed how I think about AI memory. Here's how I implemented a working second brain using Amazon Quick Desktop's connected tools and knowledge graph.
AWS Bedrock Knowledge Base Implementation: What I Learned Building a Production Policy Audit System
What I learned shipping an AWS Bedrock Knowledge Base policy audit system to production: architecture choices, chunking mistakes, cost surprises, and undocumented gotchas.
K3s vs K8s: choosing the right Kubernetes distribution for your workload
K3s vs K8s: compare architecture, resource requirements, production readiness, and day-2 operations to choose the right Kubernetes distribution for your team
The AI Spending Data Your Board Is About to Ask You About
A Guide to AWS AI: SageMaker vs. Bedrock
AWS Bedrock and SageMaker have converged in 2026, blurring the line between managed AI and custom ML. Here's how to choose based on lifecycle, ROI, and data sovereignty.
Why Your Amazon Redshift Concurrency Scaling Costs Keep Growing (And How to Fix It)
A practical walkthrough of a Redshift cost investigation. Why Concurrency Scaling can quietly become baseline capacity, how to spot it in CloudWatch and WLM, and a phased remediation plan.
The 5 best MongoDB alternatives for engineering teams in 2026
MongoDB's licensing, Atlas pricing, and lock-in are pushing teams to look elsewhere. Here are the 5 strongest alternatives in 2026 and how to choose the right fit.
DoiT Launches PerfectScale™ for Commitments, Bringing Autonomous Rate Optimization to Every Cloud
DoiT unveils PerfectScale for Commitments, applying workload-aware AI and continuous behavioral analysis to autonomously manage Savings Plans and CUDs across AWS and Google Cloud.
The Gemini Ecosystem: A Guide to Google’s AI Naming
Google's 'Gemini' brand now spans models, APIs, and enterprise platforms. Here's how to navigate the ecosystem and choose the right service for your AI workloads.
Datadog pricing explained: How to Forecast, Control, and Optimize Observability Costs
Datadog bills across five-plus independent dimensions, and most teams see bills 2-3x their initial estimate. Here's how to forecast, control, and optimize observability spend.
Snowflake competitors compared: cost, performance, and multi-cloud tradeoffs
A side-by-side look at Snowflake's top competitors across hyperscaler warehouses, lakehouse platforms, and legacy vendors, with a framework to evaluate cost, performance, and multi-cloud tradeoffs.