You’re reading The Steady Beat, a weekly round-up of hand-picked articles and resources for people who make software products: designers, engineers, product managers, and organizational leaders.
By the Numbers - Air Tagging
- 1.46 billion - The effectiveness of an AirTag, Apple’s tracking device, largely depends on the number of iPhones in its proximity. Considering there are around 1.46 billion iPhone users in the world, your odds of locating lost items are pretty good.
- 2 seconds - An AirTag broadcasts its public key every 2 seconds over Bluetooth Low Energy (BLE), which is then picked up by a nearby iPhone. The iPhone encrypts its location data and timestamp using the received public key and uploads the encrypted data to the Apple server.
- 0 - The number of GPS, WiFi, or cellular networks an AirTag uses for communication. Instead, it uses low-power Bluetooth Low Energy (BLE) or Ultra Wideband for precision and efficiency.
- 1 - One iPhone is necessary to relay location data in the AirTag system, meaning an AirTag won’t work if there aren’t any iPhones nearby.
— System Design Newsletter, 12m, #system-design, #airtags, #networks, #engineering
Design Leadership in the Age of AI
As AI continues to revolutionize creative processes and tech platforms evolve with lightning speed, the role of design leadership has significantly broadened. It’s no longer just about product impact and craftsmanship; design leaders are now expected to instigate enterprise-wide transformation and wield strategic influence. However, this growing influence brings with it increased complexity. Design executives today must strike a balance between business transformation and creative excellence, scaling impact while maintaining quality, adapting to emerging technologies while keeping user needs in focus, and building organizational capabilities while delivering immediate results. Whew. Success in this environment demands new strategic approaches and continuous reflection. Leaders must have a clear vision of design’s transformative potential, make daring moves that position design as a strategic influencer, redefine design’s unique value in the AI-augmented world, and aim to shape business strategy rather than merely respond to it.
— Defining Experience, 10m, #design-leadership, #strategy, #innovation
Don’t Conflate OKRs
Are your team’s OKRs nothing more than a reiteration of the roadmap? According @jessitron, this duplication of effort isn’t just unproductive, it’s a sign that your team may not be striving for improvement. Jessica argues that OKRs should highlight what’s unique or innovative about the current quarter – think shifts in focus, process changes, or new issues to tackle – rather than merely restating regular, ongoing work. For instance, while regular software updates might be part of an engineering team’s core job, it’s the new features or critical launches that should feature in the OKRs. Similarly, while marketing teams have ongoing tasks like running ads and webinars, their OKRs should focus on new campaigns, audiences or channels. Bottom line: Let OKRs illuminate your special focus, rather than trying to squeeze in everything you do.
— Jessitron, 6m, #okr, #software-development, #marketing
AI and Coding: Hype vs Reality
AI-assisted coding has been a trending topic in software engineering, with predictions ranging from fully automated coding to significant job loss among developers. However, experts like Addy Osmani, Head of Chrome Developer Experience at Google, provide a grounded perspective. According to Addy, AI will indeed transform parts of software engineering, but not in the drastic ways often projected. Currently, about 75% of developers utilize some form of AI tool for their work, and this trend is likely to continue, with AI software engineering agents predicted to be at the center of innovation in 2025. AI’s strengths in code writing are undeniable, given the simpler grammar of programming and the vast amount of accessible high-quality training data. Yet, Osmani also underscores the limitations of AI tools and advises developers to take a ‘trust but verify’ approach. He suggests that a shift towards AI collaboration, multi-modal capabilities, and guided autonomy is imminent. However, the art of software craftsmanship is far from obsolete.
— Pragmatic Engineer, 12m, #ai-assisted-coding, #software-engineering, #future-tech
The Human Loop Spectrum
Pawel Rzeszucinski dives into the various ways humans interact with AI systems, a concept often referred to as “Human-in-the-loop” (HITL). However, the involvement of humans in AI doesn’t stop there. Beyond HITL, where humans and AI work in a collaborative decision-making process, there are also “Human-on-the-loop”, “Human-above-the-loop”, and “Human-behind-the-loop” configurations. Each represents a different level of human involvement, from direct interaction to strategic governance. For instance, Human-on-the-loop (HOTL) configurations involve AI systems operating autonomously while being supervised by a human ready to intervene as necessary. Understanding these different configurations is key to ensuring ethical considerations, legal compliance, and high-quality AI system output. So, whether you’re in, on, above, or behind the loop, remember: human involvement is critical in the world of AI.
— Medium, 8m, #artificial-intelligence, #human-in-the-loop, #product-development
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