GenAI Applications
Kimi K2.5 and Agent Swarm: Multi-Agent Orchestration at Scale
A practical breakdown of Kimi K2.5’s Agent Swarm, from multi-agent orchestration to real-world workloads and when it beats single-agent mode.
DSA Blog & Tutorials
Data Engineering, ML Engineering & GenAI lessons that ship.
Short tutorials, architecture notes, and field reports across Data Engineering, ML Engineering, and GenAI systems.
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BigQuery + Google Sheets: Connected Sheets on GCP
A practical guide to Connected Sheets: how to analyze BigQuery data in Sheets, key workflows, limits, refresh schedules, and best practices.
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Fresh guides for shipping reliable systems with real constraints.
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GenAI Applications
Architecture, Implementation, and Strategic Use of the Model Context Protocol (MCP)
Learn how MCP standardizes AI context and tool access, from protocol primitives to secure deployment across Claude, Zed, and custom servers.
GenAI Applications
Multi-Agent Orchestration in Software Development
Learn how to design multi-agent software teams: communication patterns, roles, workflows, and tools that improve speed and reliability.
Data Engineering
Data Contracts in Production
Practical guide to managing schema changes and maintaining data compatibility.
ML Engineering
Shipping ML Models With Rollback Plans
Best practices for deploying ML models with confidence and quick rollback capabilities.
Data Engineering
Designing a Metrics Layer for Fast Decisions
Data engineering patterns for metrics layers that keep analytics consistent at scale.
Reliability
Operational Readiness for Data Pipelines
Essential practices for keeping data pipelines reliable and maintainable in production.
ML Engineering
Feature Stores: Build, Buy, or Skip?
A practical guide to deciding when feature stores add value and when they're premature optimization.
GenAI Applications
Evaluating RAG Systems Without Guesswork
A pragmatic guide to measuring RAG quality before launch.
Tutorials Library
Step-by-step walkthroughs designed for builders shipping data systems.
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