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Cloud Tasks + Firestore: The Durable Queue Pattern Most Tutorials Miss

Cloud Tasks + Firestore: The Durable Queue Pattern Most Tutorials Miss

Cloud Tasks alone is not a durable queue. Pair it with Firestore as the source of truth and you get rate control, retry, visibility, and real durability on Cloud Run.

Building a Reusable Firestore Migration Runner in Go

Building a Reusable Firestore Migration Runner in Go

A reusable Go library for Firestore collection migrations with cursor-based pagination, batch writes, checkpoint resume, rate limiting, and dry-run. Built for real production use.

Solving CHALLENGEs in Browser Automation with Custom OCR

Solving CHALLENGEs in Browser Automation with Custom OCR

Integrate a custom-trained OCR model into browser automation to solve text-based CHALLENGEs. The OCR service, confidence thresholds, and retry logic.

Running Claude Code in Batches for Automated Workflows

Running Claude Code in Batches for Automated Workflows

Learn how to run Claude Code in batches using Python. Automate long-running AI coding tasks with process control, timeouts, and graceful termination.

Why CRNN Works for OCR: A First-Principles Explanation for Developers New to AI

Why CRNN Works for OCR: A First-Principles Explanation for Developers New to AI

Understanding why Convolutional Recurrent Neural Networks with CTC loss became the standard for text recognition. No PhD required - just curiosity about why certain architectures fit certain problems.

Teaching AI to Distrust Itself: How I Built a 98% Accurate OCR Model by Learning to Question Everything

Teaching AI to Distrust Itself: How I Built a 98% Accurate OCR Model by Learning to Question Everything

Building an OCR model taught me that the hardest part of machine learning isn't the model - it's the labels. Here's how iterative outlier detection and healthy skepticism got us to 98% accuracy.

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