Articles

AI engineering notes from real workflow work

Practical writing on agentic systems, orchestration, automation design, and the operating patterns behind reliable AI delivery.

AI
AI Security • Jun 18, 2026

Common Failure Modes: MCP connector security

The mistakes teams should identify before launch. how to connect tools and data sources without overexposing permissions

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AI
AI Engineering • Jun 18, 2026

Security Review: AI engineering operating model

The security and permission concerns that should be reviewed. how teams combine product thinking, model behavior, software architecture, testing, and operations into one AI delivery practice

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DA
Data Engineering • Jun 18, 2026

Evaluation Strategy: data pipeline orchestration

How to measure quality, reliability, and operational readiness. how batch jobs, DAGs, and transforms power reliable analytics

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AI
AI Workflows • Jun 17, 2026

Deployment Playbook: content workflow automation

How to prepare the workflow for CI/CD and production operations. how creators turn raw source material into reusable publishing assets

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MO
Mobile Engineering • Jun 17, 2026

Tooling Map: offline-first mobile AI

A map of useful tools, libraries, and platform decisions. how to design resilient mobile experiences around network and model constraints

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SO
Software Engineering • Jun 17, 2026

DropTicks Field Notes: event-driven architecture

Opinionated engineering notes for practical AI and software delivery. how streams, queues, and workflow engines coordinate systems

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CH
ChatGPT Tips, Productivity • Jun 17, 2026

ChatGPT Tip: Ask For Privacy Review

Before sharing sensitive data, ask what should be removed or anonymized.

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AI
AI Security • Jun 16, 2026

Implementation Checklist: MCP connector security

A practical checklist for building and reviewing the workflow. how to connect tools and data sources without overexposing permissions

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AI
AI Engineering • Jun 16, 2026

Evaluation Strategy: AI engineering operating model

How to measure quality, reliability, and operational readiness. how teams combine product thinking, model behavior, software architecture, testing, and operations into one AI delivery practice

Read article → Save
DA
Data Engineering • Jun 16, 2026

Common Failure Modes: data pipeline orchestration

The mistakes teams should identify before launch. how batch jobs, DAGs, and transforms power reliable analytics

Read article → Save
AI
AI Workflows • Jun 16, 2026

Security Review: content workflow automation

The security and permission concerns that should be reviewed. how creators turn raw source material into reusable publishing assets

Read article → Save
MO
Mobile Engineering • Jun 15, 2026

Team Workflow: offline-first mobile AI

How engineering, product, and operations teams should collaborate. how to design resilient mobile experiences around network and model constraints

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