Instructional Design Basics

"Why cognitive load (not clean code) is what really matters in coding" What truly matters in software development isn't following trendy practices - it's minimizing mental effort for other developers. I've witnessed numerous projects where brilliant developers created sophisticated architectures using cutting-edge patterns and microservices. Yet when new team members attempted modifications, they struggled for weeks just to grasp how components interconnected. This cognitive burden drastically reduced productivity and increased defects. Ironically, many of these complexity-inducing patterns were implemented pursuing "clean code." The essential goal should be reducing unnecessary mental strain. This might mean: - Fewer, deeper modules instead of many shallow ones - Keeping related logic together rather than fragmenting it - Choosing straightforward solutions over clever ones The best code isn't the most elegant - it's what future developers (including yourself) can quickly comprehend. When making architectural decisions or reviewing code, ask: "How much mental effort will others need to understand this?" Focus on minimizing cognitive load to create truly maintainable systems, not just theoretically clean ones. Remember, code is read far more often than written. #programming #softwareengineering #tech

I got a faster treadmill. Last Friday I hit a wall mid-afternoon: generating output, skimming AI responses, missing errors I'd have caught an hour earlier. My RAM was full. I closed the laptop and went for a run. Turns out there's a name for it: AI brain fry. Gabriella Rosen Kellerman, MD and team at BCG define it as "acute cognitive overload from marshaling oversight beyond capacity." It's not burnout, I'm actually pretty excited about the potential–but it can take me past my limits. 14% of US workers are already experiencing brain fry. They're the heaviest users of AI, and they're 39% more likely to be thinking about quitting. The types of people Cisco research says are 40% more likely to be "critical to retain." Want to make it worse? They're also 39% more likely to be making major errors: not typos, but customer-facing, safety-critical and outcome-altering mistakes. As Melissa Painter put it: "We designed a workday that's too busy, our tech enabled it, and now we're adding more tech and wondering why people are burning out." The fix isn't resilience training. I interviewed Gabriella and Melissa, and here's what I heard: 🔹 Cap the agent load. Adverse effects start at three simultaneous AI agents. Map your team's oversight load before adding more. 🔹 Make managers AI coaches. Workers whose managers actively engage with their team about how and where to use AI experience 15% lower fatigue. Going it alone adds a measurable "AI orphan tax." 🔹 Shift the adoption metric. Move from individual usage rates to team-level integration. When one "builder" embeds AI into shared workflows, the whole team benefits, without everyone bearing the overhead. Huge bonus: reducing toil is the one place where burnout goes down—for everyone! 🔹 Model taking breaks. Past Slack research showed that only 38% of people take breaks during the day. If leaders don't role model stepping away from devices to recover, that won't change. As Gabriella told me: "Being there to help humanize the experience of work, to help make it feel like a collective effort — that's what managers should be doing right now." 👉 Read on, my latest linked in comments! [Special added bonus: insights from Boston Consulting Group (BCG)'s Julie Bedard's interview with Casey Newton & Kevin Roose on Hard Fork!] Are you feeling the faster treadmill?

𝐑𝐞𝐬𝐭 𝐈𝐬 𝐍𝐨𝐭 𝐑𝐞𝐜𝐨𝐯𝐞𝐫𝐲. 𝐌𝐞𝐧𝐭𝐚𝐥 𝐔𝐧𝐥𝐨𝐚𝐝𝐢𝐧𝐠 𝐈𝐬. . . Have you noticed this? You take a weekend off. Even a 𝐩𝐫𝐨𝐩𝐞𝐫 𝐯𝐚𝐜𝐚𝐭𝐢𝐨𝐧. Yet the 𝐡𝐞𝐚𝐯𝐢𝐧𝐞𝐬𝐬 𝐬𝐭𝐚𝐲𝐬. You 𝐰𝐨𝐫𝐤𝐞𝐝 𝐥𝐞𝐬𝐬. But you 𝐝𝐢𝐝 𝐧𝐨𝐭 𝐟𝐞𝐞𝐥 𝐥𝐢𝐠𝐡𝐭𝐞𝐫. Why? Because this is not physical fatigue. It is cognitive load. It is emotional carryover. Your body may be resting. Your mind is not. Decisions replay. Expectations linger. Unfinished loops stay open. 𝑅𝑒𝑠𝑒𝑎𝑟𝑐ℎ 𝑣𝑎𝑙𝑖𝑑𝑎𝑡𝑒𝑠 𝑡ℎ𝑖𝑠 𝑝𝑎𝑡𝑡𝑒𝑟𝑛. 𝑯𝒂𝒓𝒗𝒂𝒓𝒅 𝑩𝒖𝒔𝒊𝒏𝒆𝒔𝒔 𝑹𝒆𝒗𝒊𝒆𝒘 ℎ𝑖𝑔ℎ𝑙𝑖𝑔ℎ𝑡𝑠 𝑡ℎ𝑎𝑡 𝑚𝑒𝑛𝑡𝑎𝑙 𝑓𝑎𝑡𝑖𝑔𝑢𝑒 𝑎𝑐𝑐𝑢𝑚𝑢𝑙𝑎𝑡𝑒𝑠 𝑓𝑟𝑜𝑚 𝑑𝑒𝑐𝑖𝑠𝑖𝑜𝑛 𝑙𝑜𝑎𝑑 𝑎𝑛𝑑 𝑒𝑚𝑜𝑡𝑖𝑜𝑛𝑎𝑙 𝑟𝑒𝑔𝑢𝑙𝑎𝑡𝑖𝑜𝑛, 𝑛𝑜𝑡 𝑗𝑢𝑠𝑡 𝑤𝑜𝑟𝑘 ℎ𝑜𝑢𝑟𝑠. 𝑻𝒉𝒆 𝑨𝒎𝒆𝒓𝒊𝒄𝒂𝒏 𝑷𝒔𝒚𝒄𝒉𝒐𝒍𝒐𝒈𝒊𝒄𝒂𝒍 𝑨𝒔𝒔𝒐𝒄𝒊𝒂𝒕𝒊𝒐𝒏 𝑛𝑜𝑡𝑒𝑠 𝑡ℎ𝑎𝑡 𝑝𝑠𝑦𝑐ℎ𝑜𝑙𝑜𝑔𝑖𝑐𝑎𝑙 𝑑𝑒𝑡𝑎𝑐ℎ𝑚𝑒𝑛𝑡 𝑓𝑟𝑜𝑚 𝑤𝑜𝑟𝑘 𝑖𝑠 𝑐𝑟𝑖𝑡𝑖𝑐𝑎𝑙 𝑓𝑜𝑟 𝑡𝑟𝑢𝑒 𝑟𝑒𝑐𝑜𝑣𝑒𝑟𝑦 𝑎𝑛𝑑 𝑒𝑛𝑒𝑟𝑔𝑦 𝑟𝑒𝑠𝑡𝑜𝑟𝑎𝑡𝑖𝑜𝑛. So when you return to work, Within two days, The same heaviness returns. Not because rest failed. But because unloading never happened. This is a recalibration phase. And what quietly works here Is 𝐌𝐞𝐧𝐭𝐚𝐥 𝐔𝐧𝐥𝐨𝐚𝐝𝐢𝐧𝐠. 1️⃣ Write before you sleep. Transfer thoughts from mind to paper. Close open cognitive loops. 2️⃣ Stop solving everything instantly. Not every decision needs midnight processing. 3️⃣ Practice intentional silence. No phone. No stimulation. Let the nervous system settle. 𝐑𝐞𝐜𝐨𝐯𝐞𝐫𝐲 𝐢𝐬 𝐧𝐨𝐭 𝐚𝐛𝐬𝐞𝐧𝐜𝐞 𝐨𝐟 𝐰𝐨𝐫𝐤. 𝐈𝐭 𝐢𝐬 𝐚𝐛𝐬𝐞𝐧𝐜𝐞 𝐨𝐟 𝐦𝐞𝐧𝐭𝐚𝐥 𝐜𝐚𝐫𝐫𝐲. The deeper question is not, “When will I feel fresh again?” The better question is, “What am I carrying that prevents rest?” To your Leadership, Coach Vandana Dubey 𝐸𝑙𝑒𝑣𝑎𝑡𝑖𝑛𝑔 𝐿𝑒𝑎𝑑𝑒𝑟𝑠, 𝐸𝑛𝑟𝑖𝑐ℎ𝑖𝑛𝑔 𝑆𝑜𝑢𝑙𝑠 𝑅𝑒𝑠𝑒𝑎𝑟𝑐ℎ 𝑆𝑜𝑢𝑟𝑐𝑒𝑠: 𝐻𝑎𝑟𝑣𝑎𝑟𝑑 𝐵𝑢𝑠𝑖𝑛𝑒𝑠𝑠 𝑅𝑒𝑣𝑖𝑒𝑤 – “𝑀𝑎𝑛𝑎𝑔𝑒 𝑌𝑜𝑢𝑟 𝐸𝑛𝑒𝑟𝑔𝑦, 𝑁𝑜𝑡 𝑌𝑜𝑢𝑟 𝑇𝑖𝑚𝑒” ℎ𝑡𝑡𝑝𝑠://ℎ𝑏𝑟.𝑜𝑟𝑔 𝐴𝑚𝑒𝑟𝑖𝑐𝑎𝑛 𝑃𝑠𝑦𝑐ℎ𝑜𝑙𝑜𝑔𝑖𝑐𝑎𝑙 𝐴𝑠𝑠𝑜𝑐𝑖𝑎𝑡𝑖𝑜𝑛 – “𝑊𝑜𝑟𝑘, 𝑆𝑡𝑟𝑒𝑠𝑠, 𝑎𝑛𝑑 𝐻𝑒𝑎𝑙𝑡ℎ 𝑅𝑒𝑠𝑒𝑎𝑟𝑐ℎ” ℎ𝑡𝑡𝑝𝑠://𝑤𝑤𝑤.𝑎𝑝𝑎.𝑜𝑟𝑔 #LeadershipWellbeing #MentalClarity #SustainableLeadership

In the face of an overwhelming volume of to-dos, turning to time management as a solution is a dead end. What do people who are really good at time management get? More work! Time management is important, but it's a productivity tool - not a solution to pressure. Instead, take aim at the three things that create volume pressure in the first place: tasks, decisions, and distractions. When you're faced with what feels like an overwhelming pile, consider the following: 1) What tasks have I taken on that are not linked to my major goals? Can they be deferred or deprioritized? 2) What decisions regularly create cognitive load for me? Are there any that can be replaced with policies or principles so I don't need to carefully weigh them each time? 3) How can I use structure to stop relying on will-power to reduce distractions? This can be as simple as a pomodoro timer, going on airplane mode for 30 mins, or physically isolating yourself in a conference room. If you pair time management with task, decision and distraction management you'll have a more sustainable approach over the long haul.

Heavy AI users are twice as likely to quit and report 88% higher burnout. I have been writing about this for years through the hourglass lens. Top management widens. The frontline stays wide. The middle is thinned to fund AI. All the sand accelerates through the pinch. That pinch is people. It is context switching, shifting priorities, and a permanent feeling of more. This morning at dawn I spoke with a Chief Digital Officer of one of the largest manufacturers in the world. Zero debate. We both want the same thing. Make people’s lives more sustainable. Help them reconnect with society, friends, and family. Treat time as the central value. What if we made jobs suck less. What if we made people happier. What if we actually rewarded meaningful dialogue. Europe still struggles to see this, and even fewer can relate. We call it efficiency. What it feels like on the ground is the infinite workday. Superworkers build stronger bonds with their AI agents than with colleagues. They know their worth. They produce four times more. Too often they are not valued accordingly, so they go where leaders know how to use their talent. I worry most about older, larger companies. AI adoption is slow. Leadership keeps delegating and expecting more while not upskilling themselves. Talent reads that signal instantly. It says the best years are behind you. There is a different path. Start with time. Give the middle real capacity and clear decision rights so coaching, debriefs, and real decisions actually happen. Treat AI load the way you treat any resource. Set limits before cognitive strain becomes culture. Measure value, not only speed. Learning rate. Time to opportunity. Customer impact. Use AI to build new revenue and better experiences, not just to squeeze. If you want to lead here, lead with time and meaning. The outcome is not only less burnout. It is better product, faster learning, stronger teams, and a company people want to stay in. Your best AI adopters are your edge. If they are breaking, the system is breaking. The fix is not another dashboard. The fix is how we spend our time together. Augmentation over automation. #FutureOfWork

A Soviet psychologist walked into a café in 1927 and noticed something strange. A waiter could recall every open order in the room, perfectly, without notes or hesitation. Yet the moment a table paid and left, the memory disappeared. Not faded, gone. This became known as the Zeigarnik Effect, the tendency for unfinished work to stay active in our minds. But the real insight isn’t about memory, it’s about stress. Every unfinished task creates an open loop, and every open loop creates tension. Over time, that tension builds into cognitive overload. You don’t need a psychology experiment to see this, you see it every day in organisations where people are juggling too many priorities, starting work they don’t finish, raising problems that aren’t resolved, and agreeing actions that are never followed through. The system quietly trains people to carry unfinished work in their heads, and over time, that becomes exhausting. This is where Lean Leadership changes the game, not by asking people to cope better, but by designing systems that reduce the number of open loops in the first place. Clear priorities reduce competing demand, Visual Management takes work out of people’s heads and makes it visible, Daily Management creates a rhythm of review and closure, and problem solving ensures issues are resolved rather than recycled. The goal isn’t to improve memory, it’s to remove the need for it. When work is visible, structured, and closed deliberately, the mental burden drops, and when the mental burden drops, people think more clearly, make better decisions, and experience less stress. That’s not a soft benefit, that’s system design. Because the real question isn’t how we help people remember more, it’s why we are asking them to carry so much unfinished work in the first place. #leanleadership #leadingwithlean #leadingleanbylivinglean #thesimplicityoflean #PDCA #BTFA

🎯 You can have clear objectives, great content, and fancy tools, but if you ignore Cognitive Load Theory (CLT), your course might still fail your learners. CLT is about how our brain handles learning. It reminds us: mental effort is limited. If we overload learners, they disconnect. Instead, let’s design smarter — so people learn because of your course, not despite it. 🧠 CLT breaks mental load into three types: 1. Intrinsic Load (natural complexity) 📌 What it is: The difficulty of the material itself. ✅ Tip: Break it down into digestible chunks and build up step by step. 2. Extraneous Load (distracting noise) 📌 What it is: Unnecessary info or poor design that gets in the way. ✅ Tip: Cut the clutter. Clean visuals. Simple words. Clear structure. 3. Germane Load (productive effort) 📌 What it is: Mental effort that helps learning stick. ✅ Tip: Add practice, reflection, real examples, comparisons. 💡 Design smarter with CLT: Manage complexity with structure and flow Reduce distractions and overload Boost engagement with meaningful tasks 🔍 Before you ship your course, ask: Will learners understand, remember, and use this, or just survive it? CLT isn’t theory. It’s your secret weapon for creating training that works.

Every unresolved task in your head is an open loop draining your focus. Psychologists call it the Zeigarnik effect - your brain fixates on incomplete tasks until they're resolved or captured somewhere. The fix is a cognitive load dump. 1. Brain dump (pen and paper, not digital) Write down everything that's on your mind. Tasks, worries, random thoughts, open loops. The physical act of writing engages your visual and motor cortex together, which creates a stronger cognitive offloading effect than typing. Once you think you're done, keep going. Hold for another 3-5 minutes. There's always another layer. 2. Organize the dump For each item, make one decision: - Do it now (under 2 minutes) - Schedule it (specific time on the calendar) - Delete it (cross it out - it wasn't that important) - Delegate it (name the person) This is the step that actually matters. Writing things down helps, but the loose ends are still open. Your brain won't release an item until it knows the item has a fate. Deciding what happens to each one is what closes the loop. 3. Release and reset Fold the paper. Put it somewhere out of sight - a drawer, a folder, just away. The physical act of removing it creates a psychological boundary. Then: three deep breaths. In for 3, hold for 2, out for 10. This breathing ratio activates the parasympathetic nervous system and starts clearing the stress hormones that accumulate when cognitive load is high.

Most teams don’t have a capacity problem - it's a cognitive load problem. NASA—the NASA Task Load Index (NASA-TLX)—measures mental demand, effort, frustration, and perceived performance. Pair that with Cognitive Load Theory (Sweller, 1988; Paas & van Merriënboer, 2020): working memory is limited, and when it is overloaded, performance drops. High performers aren’t working harder. They’re thinking cleaner and acting on it. Struggling systems and performers are high effort, high frustration. More rework. More noise. That gap is cognitive inefficiency. Here’s what some leaders miss: that inefficiency spreads. When one person, process, or tech is unclear or inconsistent, the team absorbs it. Others fix avoidable mistakes, and manage delays. Utterly unacceptable. If you want a raised standard, look at Artemis II. It’s a multi-day crewed mission sending four astronauts farther than any human has traveled since Apollo. It integrates thousands of procedures across launch, Earth orbit, translunar injection, deep space flight, lunar flyby, and high-speed reentry. At any given phase, the crew and ground are managing: – spacecraft systems (propulsion, life support, navigation) – tight timing windows for burns and trajectory corrections – continuous communication loops with mission control – real-time monitoring and contingency readiness All under conditions where delay, confusion, or rework compounds risk instantly. So they design differently. They pre-decide flight rules—thousands of “if/then” scenarios so astronauts don’t burn cognitive energy figuring things out mid-flight. They externalize memory with detailed checklists. They enforce closed-loop communication so nothing slips through. They run simulations that layer failures on top of nominal operations to push the team to the cognitive limits before it matters. And they distribute work—crew, mission control, and onboard systems—so the right thinking happens in the right place. They’re not optimizing for effort. They’re optimizing for cognitive efficiency. Differing kinds of contributors emerge. The ones who reduce load—clarify, simplify, anticipate, and move faster. The neutral ones own their work cleanly. And the ones who amplify load—create rework, ambiguity, and dependency. One load amplifier can quietly consume the bandwidth of the team. So stop asking if people are working hard enough. Start asking what they’re doing to the team’s ability to think. Tighten roles and decision rights. Automate anything that can be. Train deliberately, not reactively. And make it explicit in performance: the expectation isn’t just output—it’s reducing the cognitive load of the system. If someone or process or tech consistently increases rework, and delay, that’s not an effort issue. That’s a standard issue. High-performing environments pay close attention to protect outcomes. The teams that win aren’t doing the most work. They’re carrying the least unnecessary load. #Artemis IIinspired

AI adoption without cognitive load management is setting teams up for mental overload. So many organizations are rushing to integrate AI tools across workflows, but ignoring the neuroscience of how much new information and decision-making the brain can handle before performance degrades. Here's what we know from the research: Working memory has hard capacity limits, and every new tool, interface, or decision point draws from the same finite cognitive resources. Studies on cognitive load theory consistently show that when task complexity exceeds available working memory capacity, learning and performance both decline. Introducing AI without structure adds extraneous load, the kind that doesn't contribute to better outcomes but still taxes the prefrontal cortex. Here are 15 ways we can deploy AI while protecting our teams' cognitive bandwidth: - Introduce one AI tool at a time rather than bundling multiple new systems - Automate repetitive low-stakes decisions first, freeing working memory for complex judgment - Use AI to pre-filter information so teams receive curated, not raw, data - Build standardized prompts so people aren't reinventing their approach each session - Let AI handle meeting summaries and action items to reduce encoding burden - Create clear guidelines for when to use AI versus human judgment - Schedule AI training during circadian peaks for better retention - Use AI to reduce context-switching by consolidating communication channels - Pilot tools with small groups before organization-wide rollouts - Provide decision frameworks so AI outputs don't create new ambiguity - Automate status updates and progress tracking to lower monitoring load - Use AI for first-draft generation, letting humans focus on refinement - Designate "tool-free" deep work blocks to allow cognitive recovery - Collect feedback on perceived mental effort, not just productivity metrics - Revisit and retire tools that aren't reducing load as intended When we exceed working memory thresholds, things can go wrong very fast. People's accuracy drops, their errors increase, and burnout, which was already a problem prior to the AI boom, accelerates even faster. AI should reduce the cognitive demands on our teams, not add another layer of complexity they have to manage.