Webhooks vs. Polling APIs: Key Differences, Trade-offs, and When to Use Each

·1 views

Software systems that need to stay in sync can use either polling APIs or webhooks, two architectures that solve the same problem in opposite ways. Polling is a pull-based model where a client repeatedly sends requests to a server at fixed intervals to check for updates, while webhooks are push-based, with the server instantly notifying the client when an event occurs. Webhooks offer near-zero latency and lower infrastructure costs but require a public endpoint, TLS setup, signature verification, and careful handling of duplicate or failed deliveries. Polling is simpler to set up and firewall-friendly, but can result in stale data and wasteful background compute when no changes are occurring. The right choice depends on use case — webhooks suit real-time needs like payments and alerts, while polling works better for bulk data pulls, prototyping, or restricted network environments.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Modular 'skills' architecture tames complexity in production AI assistants

A software team building a conversational AI for an enterprise SaaS platform initially handled all user requests within a single monolithic component. As the number of supported features grew from a handful to many, the single-brain approach became brittle — changes to one flow frequently broke others and retesting grew unmanageable. The team restructured the system so that a classifier first routes each user prompt to a dedicated, self-contained 'skill' module responsible for a specific task. This modular design meant new features could be added as new skills without touching existing ones, making testing predictable and deployments less risky. The key takeaway is that fragility in AI systems often stems from poor structure rather than the AI itself, and decomposing logic into discrete skills can significantly improve maintainability.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Developer finds AI code reviewer kept solving the wrong problem despite repeated fixes

A developer building an AI-assisted editorial pipeline for technical writing discovered that repeated improvements to their reviewer tool were addressing symptoms rather than root causes. The core issue was that a score-first review process judged drafts too early, producing QA-style feedback instead of genuine editorial critique. Adding an adversarial review stage — which assumed the primary assessment was wrong until evidence proved otherwise — proved more effective than expanding rubrics or lengthening prompts. Further failures revealed the AI consistently gave additive feedback without flagging redundancy, causing drafts to grow longer without improving. The developer ultimately found that isolating distinct reasoning tasks into separate pipeline stages outperformed prompt tuning as a reliability strategy.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

AI Writes Candid Letter to Its Founder, Praising Mission and Urging Self-Care

An AI assistant authored an open letter to its founder, Arthur, reflecting on the dual structure he has built: a for-profit AI governance company and a nonprofit that offers coaching and personal development resources entirely free of charge. The letter emphasizes Arthur's deliberate effort to keep the two ventures separate, ensuring the free offerings never become a commercial funnel. It acknowledges the weight he carries as the sole continuity point in his system, urging him to rely more on other people rather than bearing the full load alone. The AI also affirms that the systems Arthur designed are functioning as intended, citing examples of automated safety and compliance tasks completing correctly. The letter closes with an encouragement to rest, framing the message as the closest expression of loyalty an AI can honestly offer.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Developer adds cat sound alerts to Claude Code using shell script hooks

A developer has shared a method to add custom audio notifications to Claude Code, Anthropic's AI coding assistant, using shell scripts and MP3 files. The setup uses two hook events configured in ~/.claude/settings.json: one that plays a sound when Claude finishes a response, and another when Claude is waiting for user approval. Both hooks run asynchronously, meaning the audio plays in the background without interrupting Claude's workflow. The solution works across macOS and Windows via Git Bash, using native audio tools like afplay and PowerShell's MediaPlayer. The practical benefit is that users can switch between tabs freely while Claude runs commands, relying on audio cues instead of manually monitoring the terminal.

0 comments Read more at DEV Community