Buglyst Blog
Learn to debug under pressure.
Playbooks for fast pattern recognition, guides for the full investigation, and articles for the engineering judgment around the edges.
17 playbooks · 509 guides · 95 articles · 12 linked practice labs ·skip to practice
Fast pattern recognition for the production failures engineers see most often.
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Structured investigations for the failure modes engineers meet in real systems.
Flutter FutureBuilder Rebuilds Infinitely: The Real Causes and Fixes
A practical guide to stopping FutureBuilder from rebuilding endlessly in Flutter, with root causes, diagnosis steps, and real war stories.
Debugging PyTorch Tensor Shape Mismatch Runtime Errors
A practical guide to diagnosing and resolving shape mismatch errors in PyTorch, covering common causes, debugging commands, and fixes.
PyTorch Gradient Explosion Producing NaN Loss
Diagnose and fix NaN losses caused by gradient explosion in PyTorch models. Covers gradient clipping, weight initialization, and data normalization.
TensorFlow Incompatible Shapes Error: Debugging Shape Mismatch in Production
A practical guide to diagnosing and fixing TensorFlow shape mismatches, from understanding error messages to verifying the fix.
Long-form thinking on debugging habits, observability, and the systems around the bug.
How to Debug Legacy Code Without Losing Your Mind
A pragmatic approach to debugging code you didn't write, with techniques for tracing execution, isolating side effects, and making safe edits.
Debugging Feature Flag Rollouts: Tracing the Live-at-5 Incident
A misconfigured feature flag triggered a cascading failure in production. Here's how we traced the root cause and built a better debugging toolkit.
How to Ask for Debugging Help Without Wasting Everyone's Time
Asking for debugging help is a skill. Here's how to provide enough context, show your work, and frame the problem so others can actually help you.
Documenting Bugs: A Postmortem-Driven Approach That Cut Recurrence by 60%
Most bug write-ups are useless. Here's a structured, postmortem-driven approach that reduced bug recurrence by 60% in our team — with templates and a real incident walkthrough.
Debugging as Hypothesis Testing: A Mental Model for Systematic Root Cause Analysis
Most debugging is frantic guessing dressed up as experience. Here's a mental model that treats debugging as a scientific process — form hypotheses, design experiments, and isolate root causes systematically.
How to Read Error Messages: A Debugging Protocol
Most engineers skim error messages and miss the signal. Here's a repeatable protocol for extracting maximum information from stack traces, log lines, and crash dumps — with a real incident walkthrough.