sourabh86

The webapp does have some challenges which can only be solved with a native app. For example, a very useful feature will be to create an AR view of sun's path. That way it is helpful to plan your shoot in a granular way but apart from that, webapp does the job pretty well as it has all the location data it needs.

An interactive guide to service workers which help with offline capabilities and enabling PWA (progressive web apps)

I wrote an explainer on classic edge detection algorithms (Sobel, Canny, Laplacian) while building an interactive tool that lets you upload an image and compare their outputs side by side.

The post focuses on:

- What each algorithm is actually doing under the hood

- Where each one works well (and where it doesn’t)

- Why Canny feels “better” in many cases but costs more compute

- Practical tradeoffs rather than just theory

The tool runs entirely client-side, so no images are uploaded to a server.

Would love feedback from folks who’ve used these algorithms in production or teaching.

Most Git tutorials assume you’re an engineer, but with the rise in vibe coding tools, PM role is changing to a more collaborative builder role. Vibe coding PMs also need to understand branches, pull requests, code reviews, and how to collaborate effectively with dev teams. I put together a concise, no-nonsense guide that explains Git concepts using product-friendly examples and shows how PMs can use Git to vibe-code, explore repos, understand changes, and communicate better with engineers. Would love feedback from PMs, EMs, and devs: – What do PMs struggle with the most when learning Git? – Does this level of depth feel right? – What else should be added to make it truly useful in real workflows? Open to critique, improvements, and additional topic suggestions.

Many teams end up gluing their app to a background job queue through n8n webhooks, and then discover all the sharp edges: duplicate callbacks, mismatched job states, retries that corrupt data, and workflows that quietly stall under load.

This post walks through a pattern for wiring a custom job queue into n8n using webhook callbacks, with a focus on idempotency, explicit job state transitions, and failure recovery rather than “happy path” demos.

Curious how others are handling this in production: - How do you design your callback contracts and job state machine? - What patterns have worked (or failed) for idempotent callbacks and retries? - Any war stories from running webhook-heavy n8n (or similar) setups at scale?

I've seen too many comments on how production automation workflows fail silently or bring down entire systems when a single API call times out. Just published a guide covering the error handling, retry logic, and security patterns that prevent this:

Some problems: - Single unhandled error cascades through your entire workflow - No visibility into what failed or why - No automatic recovery from transient failures - Webhooks are wide-open security holes

General Solutions: - Centralized error workflows that capture full failure context - Exponential backoff retry logic - Try/Catch blocks for risky operations - Webhook authentication with HMAC validation

Also included: An interactive retry logic simulator, webhook security tester, and a complete production deployment checklist.

Would love feedback from HN on what else should be covered for production n8n deployments.