Learning Paths
Knowledge Base
Structured tutorials and reference knowledge—organized for learning and lookup
Generating Book Insights at Scale: How We Cut LLM Latency by 82% and Costs by $14k/Month with Semantic Chunking and Adaptive Caching
Current Situation Analysis We processed 50,000 books monthly to generate structured insights: character arcs, thematic summaries, and sentiment trajectories. The naive pipeline used a standard RecursiveCharacterTextSplitter with a fixed chunk size of 512 tokens.
How I Reduced MTTR by 85% and Saved $40k/Month with a Distributed Decision Engine: A Staff Engineer's Playbook
Current Situation Analysis When I joined the platform team at a Series C fintech, our engineering organization was bleeding efficiency. We had 45 microservices, 120 engineers, and a "hero culture" that was destroying retention. Our Mean Time To Recovery (MTTR) sat at 42 minutes.
How We Cut LLM Token Spend by 62% and Reduced API Latency to 14ms with Predictive Token Economics
Current Situation Analysis Enterprise AI platforms burn through API tokens like oxygen in a vacuum. Most engineering teams treat token allocation as a static quota problem: assign 10,000 tokens/minute per tenant, cap it with a Redis counter, and return 429 Too Many Requests when the bucket empties.
Cutting API Gateway Overhead by 68%: A Production-Ready Go/TypeScript Proxy with Adaptive Backpressure Routing
Current Situation Analysis When we migrated our internal platform from Kong 3.4 to a custom Go 1.22 gateway, we didn't do it for fun. We did it because the declarative YAML routing model was bleeding us dry. At 12,000 RPS, our p95 latency sat at 340ms. Connection pools starved.
Automating Portfolio Rebalancing: Achieving <0.05% Drift with 42ms Latency and 96% Cost Reduction in Go 1.23
Current Situation Analysis The Real Problem: Naive Rebalancing Bleeds Money At scale, portfolio rebalancing is not a math problem; it is a distributed systems problem. Most engineering teams build rebalancers that work perfectly in backtests but fail catastrophically in production.
How I Cut Custody Latency by 96% and HSM Costs by 78% Using Ephemeral Session Rings
Current Situation Analysis Digital asset custody at scale is not a cryptographic problem. It is a systems engineering problem disguised as one. Most production failures I've audited stem from treating private keys as persistent artifacts rather than transient computational states.
How We Cut On-Chain Analytics Latency by 83% and Saved $14,200/Month with Parallel Log Bloom Indexing
Current Situation Analysis Processing EVM transaction logs at scale breaks naive architectures. At 45k TPS on Ethereum mainnet, a single analytics query was taking 850ms and costing us $21,300/month in AWS RDS and RPC credits.
How I Cut API Gateway Costs by 62% and Eliminated 429 Spikes with Cost-Weighted Token Economics
Current Situation Analysis Most engineering teams treat rate limiting as a static configuration problem. You set 100 requests per minute per API key, deploy a Redis counter, and call it done.