Show Notes
Architecture Corner Newsletter Podcast - When redundancy and graceful degradation aren't enough, it's time to think beyond single regions and prepare for the worst-case scenarios that can take down entire data centers. In this episode we will cover: Why single-region availability zones have limitations and when you need multi-region strategies Four disaster recovery approaches: backup and restore, pilot light, warm standby, and active-active setups Trade-offs between recovery time, data loss, cost, and operational complexity Non-availability reasons for going multi-region: latency optimization and regulatory compliance How cloud providers like AWS support different disaster recovery patterns Planning considerations for geographical distribution of your infrastructure
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Architecture Corner Newsletter Podcast AI coding budgets are getting torched, and 2026 is the year the bill finally came due. In this episode, we dig into how token consumption became a productivity metric (and why that backfired), and what the industry is doing about it now that the free-for-all is ending. We will cover: Why token usage became a proxy for developer productivity — and how Goodhart's Law caught up with it The provider-side shifts (usage windows, model restrictions, pricing model changes) that reshaped agentic coding through early 2026 What's really driving your AI bill: subscriptions vs. API, caching mechanics, and model/thinking-effort tradeoffs Practical tokenmining strategies — from scripting deterministic steps to tuning your harness and mixing models Where the industry goes next as cost-conscious AI development becomes the norm
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Once you ship a public API, you've made a promise. Keeping it while still moving forward turns out to be harder than most teams expect. In this episode, we will cover: What qualifies as a backward-compatible change, and what doesn't Why does introducing a new API version cost more than just writing new code The real reason clients delay upgrades, and what you can do about it How to support multiple versions without duplicating your entire codebase The adapter pattern is a practical way to isolate version changes at the edges Know more here: https://medium.com/itnext/the-challenges-of-evolving-your-service-api-versioning-8008349a1154 Subscribe, for free, to the Architecture Corner Newsletter at https://architecturecorner.substack.com
The AI development landscape keeps shifting, leaving many developers frustrated as they try to keep up with each new model, tool, and workflow. But what if the answer isn't chasing every update, but building a more intentional approach?
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