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Issue #659
Essential Reading For Engineering Leaders
Friday 17th October issue is presented by Queue-it
Even well-architected systems have scalability limits. Queue-it’s virtual waiting room ensures resilience when load exceeds capacity, regulating requests at the edge to protect APIs, databases, and third-party dependencies. With Queue-it, you can:
Handle surges without overloading systems
Control scaling costs by controlling traffic flow
Block bots before they hit your stack
— Wes Kao
tl;dr: Instead of only asking your manager where you can help, I recommend observing, asserting, and validating where you can help. Wes outlines each step and provides examples of how this is effective.
CareerAdvice
— Gergely Orosz, Elin Nilsson
tl;dr: “Which tools do software engineers use for observability, oncall tooling, feature flags, frontend & mobile work, and for developer tooling? Results from our survey, based on 3,000+ responses.”
Leadership Management
— Jose Quaresma, Tristan Watson
tl;dr: In this podcast episode, platform engineer Tristan Watson explores the mechanics of scaling for hype events, where traffic increases up to 10x in minutes. He explains gaps in autoscaling, the pain of database saturation, and why real traffic spikes surface weaknesses load tests rarely catch. You’ll hear how engineering teams keep throughput steady when the usual playbooks break.
Promoted by Queue-it
Management Scale
— Mike Fisher
tl;dr: “This is where leadership has to step in. Only those with a cross-silo view can escape the gravity of local minima. But it’s not enough to simply “be aware.” Leaders must actively create the connective tissue between functions, ensuring that efficiency in one part of the system doesn’t translate into fragility in another. In other words, someone needs to own the global maximum, not just applaud a collection of local wins.”
Leadership Management
“Any sufficiently advanced technology is equivalent to magic.”
— Laura Tacho
tl;dr: “As engineering leaders are busy putting together their 2026 budgets, questions about AI spending and AI tool ROI have been common conversation topics. Earlier this month, DX surveyed 50 engineering budget holders to gauge their approaches to AI spending in 2026. Most of these leaders were actively drafting or had just recently finalised their budgets, and here is what we found.”
Leadership Management
Learn from the team at Tilt how Augment Code improved review cycles and empowered their engineering team by systematically documenting engineering knowledge. Augment Code has saved this international company valuable time; learn how it can help your team improve first-time PR approval rates, build a knowledge base using AI, and test strategies for AI development.
Promoted by Augment Code
AI CodeReview
— Gregor Ojstersek, Steven Levey
tl;dr: “The C.R.A.F.T.E.D. prompt framework for software engineers provides a structured, repeatable method for constructing high-quality prompts to get the best possible results from AI models for software engineering tasks. It builds on the core concepts of providing persona, context, and clear instructions, but organizes them into a logical workflow that mirrors how a developer might approach a problem.”
AI BestPractices
— Przemek Kusiak
tl;dr: “If you need to parametrize your application at runtime by passing a few ad-hoc variables, you’re doomed to a pretty awkward, outdated interface: Environment variables. There are no namespaces for them, no types. Just a flat, embarrassingly global dictionary of strings. But what exactly are these envvars? Is it some kind of special dictionary inside the OS? If not, who owns them and how do they propagate?”
DeepDive
— Jono Alderson
tl;dr: “Countless sites ship with fragile, inconsistent, or outright broken caching policies. They leave money on the table in infrastructure costs, frustrate users with sluggish performance, and collapse under load that better-configured systems would sail through. This guide exists to fix that. Over the next chapters, we’ll unpack the ecosystem of HTTP caching in detail.”
HTTP Cache
Null Pointer
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Notable Links
Amplifier: Supercharged AI dev environment.
Beads: Memory upgrade for your coding agent.
Jsonriver: Parse JSON incrementally as it streams.
Nitro: NextGen server toolkit.
Tinker: Training API for developers.
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