Usability Heuristics Explained

☂️ Designing For Edge Cases and Exceptions. Practical design guidelines to prevent dead-ends, lock-outs and other UX failures ↓ 🚫 People are never edge cases; “average” users don’t exist. ✅ Exceptions will occur eventually, it’s just a matter of time. ✅ To prevent failure, we need to explore unhappy paths early. ✅ Design full UI stack: blank, loading, partial, error, ideal states. ✅ Design defaults deliberately to prevent slips and mistakes. ✅ Start by designing the core flow, then scrutinize every part of it. ✅ Allow users to override validators, or add an option manually. ✅ Design for incompatibility: contradicting filters, prefs, settings. 🚫 Avoid generic error messages: they are often main blockers. ✅ Suggest presets, templates, starter kits for quick recovery. ✅ Design extreme scales: extra long/short, wide/tall, offline/slow. ✅ Design irreversible actions, e.g. Delete, Forget, Cancel, Exit. ✅ Allow users to undo critical actions for some period of time. ✅ Design a recovery UX due to delays, lock-outs, missing data. ✅ Accessibility is a reliable way to ensure design resilience. Good design paves happy paths for everyone, but also casts a wide safety net when things go sideways. I love to explore unhappy paths by setting up a dedicated design review to discover exceptions proactively. It can be helpful to also ask AI tooling to come up with alternate scenarios. Once we start discussing exceptions, we start thinking outside of the box. We have to actively challenge generic expectations, stereotypes and assumptions that we as designers typically embed in our work, often unconsciously. And to me, that’s one of the most valuable assets of such discussions. And: whenever possible, flag any mentions of average users in your design discussions. Such people don’t exist, and often it’s merely an aggregated average of assumptions and hunches. Nothing stress tests your UX better then testing it in realistic conditions with realistic data sets with real people. Useful resources: How To Fix A Bad User Interface, by Scott Hurff https://lnkd.in/ecj6PGPU How To Design Edge Cases, by Tanner Christensen https://lnkd.in/ecs3kr8z How To Find Edge Cases In UX, by Edward Chechique https://lnkd.in/e2pfqqen Just About Everyone Is an Edge Case, by Kevin Ferris https://lnkd.in/eDdUVHyj Edge Cases In UX, by Krisztina Szerovay https://lnkd.in/eM2Xynba Recommended books: – Design For Real Life, by Sara Wachter-Boettcher, Eric Meyer – The End of Average, by Todd Rose – Think Like a UX Researcher, by David Travis, Philip Hodgson – Mismatch: How Inclusion Shapes Design, by Kat Holmes #ux #design

Recently, I met the most “mysterious” AC remote ever. Four buttons. Only four. On/off, temperature up, temperature down, and fan. My first reaction: “Wow, minimalism!” My second reaction (2 minutes later): “Wait… where’s the mode button?” My third reaction (after mild wrestling with the remote): “Oh… it’s hidden under a secret flap. Of course. Because nothing says ‘great UX’ like a treasure hunt.” Let’s be honest, this is the classic trap we fall into in product design: 👉 Confusing minimalism with usability. 👉 Hiding essential actions in the name of simplicity. 👉 Assuming users will ‘figure it out’. In reality, users don’t want to “figure it out.” They want clarity. Visibility. Immediate affordance. Not an escape room challenge disguised as an AC remote. Takeaways? Visibility beats minimalism. Simplicity is not about fewer buttons, it’s about fewer surprises. If a core action requires a hidden door, a sliding panel, or divine intervention… the design has failed. As product leaders, we must ensure that: • Essential actions stay visible. • Minimalist interfaces stay intuitive. • “Clean design” doesn’t come at the cost of discoverability. Sometimes, the best UX is just… showing the buttons. #userexperience #minimalism #design

Resilience is a design choice, not a lucky break. Two reads worth your time from Cloudera on a theme that matters right now: keeping data and critical services available when things go wrong. First, architecting for data resilience and business continuity. The core idea is to design for disruption. Build clean failover paths. Keep data portable across on-prem, edge, and cloud. Test recovery, do not assume it. When incidents happen, the difference between minutes and hours shows up in revenue, trust, and compliance. Second, why hybrid needs multi-cloud resilience. Outages are inevitable. Single-cloud dependencies turn into single points of failure. A consistent platform across environments lets teams move workloads where they can run, without big rewrites. Governance and controls must travel with the data so handoffs stay compliant and auditable. Why this matters: - Incidents are normal. Downtime should not be. - Portability gives you options under pressure. - Practiced recovery beats theoretical plans. - Consistent governance speeds safe failover. Practical next steps: - Map tier-1 workloads and their failover targets. - Define RTO and RPO you can actually meet. - Run recovery drills and measure the results. - Reduce hard vendor lock-ins where they hurt resilience. Full reads: Architecting for Data Resilience: https://lnkd.in/dERfqTBv Hybrid Needs Multi-Cloud Resilience: https://lnkd.in/dHCURFWY If you own a data platform or lead operations, this is a good checklist to pressure test your plan before the next incident. #data #ai #cloudera #resilience #hybrid #iceberg #governance #cloud #theravitshow

It’s 2:07 a.m., when Murphy loves to visit. A storm rolls in, a node naps, and yet the customer never notices. That’s the goal: “boringly brilliant” resilience. Reliable enough to be forgettable. Amit Meshram wrote about how we’re approaching resiliency at Chase in a new post on the Next at Chase blog. A few takeaways that resonated for me as an architect: • Resilience is the product. Not a feature we bolt on. We design for the inevitable, failures happen; losing customer trust cannot. Every choice in our data architecture starts with that lens. • Choose your two, deliberately. CAP tradeoffs are leadership moments. For transactional integrity, we lean into consistency and partition tolerance with relational stores; for high-velocity, geo-distributed workloads, we bias toward availability and partition tolerance with distributed NoSQL. Clarity of purpose beats wishful thinking. • Practice makes reliable. Policy-driven failover, multi-region replication tailored per workload, chaos drills and GameDays under real load. Recovery should be predictable, not surprising. • Backups are a product feature. Strong, immutable, multi-region, with rehearsed restores and verified RPO/RTO. Telemetry as an early warning system. Think self-cleaning oven for databases: quietly isolating, rerouting and replacing before anyone feels heat. • Measure what matters. SLOs on critical paths, error budgets and burn rates, hot-partition detection, restore verification, and time-to-first-byte on recovery. We improve what we instrument. • Govern the blast radius. Architecture reviews that make CAP choices explicit, define failure domains, and test data correctness. Post-incident reviews that feed patterns, not blame. If we encode resilience into our blueprints, our controls and our culture, customers experience what we’re aiming for: everything just works. If this topic resonates, I highly recommend reading the full piece. There’s a lot more detail on how we design, test, and operate for “boringly brilliant” resilience. Give it a read and let me know your takeaways in the comments.

𝗔𝗳𝗳𝗼𝗿𝗱𝗮𝗻𝗰𝗲 𝗶𝗻 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 - 𝘄𝗵𝗮𝘁 𝘂𝘀𝗲𝗿𝘀 𝘁𝗵𝗶𝗻𝗸 𝘁𝗵𝗲𝘆 𝗰𝗮𝗻 𝗱𝗼 Affordance is a core UX principle: it’s about what an object 𝘴𝘶𝘨𝘨𝘦𝘴𝘵𝘴 you can do with it. Think door handles vs push plates - the design hints at the interaction. In Power BI, affordance matters more than we realise. If a user 𝘵𝘩𝘪𝘯𝘬𝘴 they can click something, they’ll try. If it 𝘭𝘰𝘰𝘬𝘴 like text, they’ll read it, not interact with it. • Buttons that don’t look clickable? Users miss them. • Slicers styled like KPIs? Users think they’re static. • Charts with hover effects? Now they feel interactive. • Tooltips, shadows, underlines - all signal affordance. 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: Power BI is a self-service tool. If your users feel unsure where to click or explore, they’ll stop trying. Improve affordance with: • Clear, consistent button styles • Visual cues like icons, shadows, and hover effects • Avoiding ambiguity: KPIs are not slicers, and vice versa • Following web UX patterns – users bring those expectations with them Small tweaks = major usability gains. #PowerBI #UIUX #DataViz

Designers just don’t want to admit it: “UX is getting manipulative.” We talk about “user-centered design.” But let’s be honest. Most interfaces are built to: - Nudge - Push - Or trap users… … into decisions they didn’t mean to make. Dark patterns? ↳ Still everywhere. Consent? ↳ Barely meaningful. Autonomy? ↳ Almost gone. But here’s the twist: Good UX doesn’t mean removing persuasion. It means balancing it with freedom. When users choose, they trust. When they trust, they stay. So instead of manipulating users into conversion, What if we designed for autonomy instead? That’s where these 8 UX frameworks come in. Each one helps users make: - Informed - Empowered - And ethical choices. No manipulation. No trickery. Just clarity, consent, and control. 🧩 C-O-N-S-E-N-T ⚖️ A-U-T-O-N-O-M-Y 🔒 T-R-U-S-T 🎯 C-H-O-I-C-E ⚖️ F-A-I-R 💡 C-L-A-R-I-T-Y 🤝 R-E-S-P-E-C-T ❤️ H-U-M-A-N Because the future of UX isn’t about making people click faster. It’s about making people feel safe, respected, and in control. If you’re designing for real people, not metrics, You need to see this. 👇 Check out the full infographic: 8 UX Frameworks To Design for User Autonomy What’s one UX principle you never compromise on?

What happens when your system fails at 2 AM? If your answer is “panic,” it’s time to rethink your architecture. Fault-tolerant systems are built to expect failure and keep going. Here are 10 essential principles every engineer should know 👇 1. Design for Failure, Not Perfection Assume networks, services, even your logic can fail. Build and test for failure scenarios, not just the happy path. 2. Redundancy & Degradation Duplicate key components and degrade gracefully, so even if one service crashes, your system keeps functioning in a limited mode. 3. Limit Cascading Failures Use circuit breakers, retries with backoff, and timeout limits to isolate issues and avoid full-system meltdowns. 4. Stay Resilient Under Load Drop non-critical tasks during high demand using load shedding. Use loose coupling to reduce dependency between components. 5. Test & Monitor Continuously Chaos testing helps you find weak spots before real failures occur. Pair it with smart monitoring to catch problems early and alert the right way. Fault-tolerant systems don’t eliminate failure, they embrace it. When done right, you build resilient software that recovers fast and serves users reliably, even in the worst conditions. Which of these principles have you already implemented?

Most people start a business for "freedom." But somewhere between client meetings, drowning in admin and working weekends to "keep up"... It slips away. (I get it. I've been there.) I'd work 16-hour days, 7 days a week for 12 months (including EVERY bank holiday). I drank 2-3 Red Bulls/day I slept 4-5 hrs per night I put on 17kg of pure fat. Not healthy. Not sustainable. Would I do it again? Absolutely! It built my foundation. But now, I'm in a strong enough financial position to restructure my biz around 3 types of freedom: ✅ Time – schedule isn’t dictated by work. ✅ Location – to work from anywhere. ✅ Choice – to decide what I work on. Want more autonomy in YOUR business? Here are 3 things I do that might help you: _____ 1. Productising services. Most service businesses suffer from the "custom everything" trap. Every client wants something slightly different, which *can* mean endless admin and calls. I solve this by: → Offering clearly packaged, high-value and repeatable services instead of endless ad-hoc requests. → Removing dependency on live work. 90% of client comms are async (WhatsApp, Notion, or email). → Creating clear deliverables with set turnaround times, so I can plan & deliver work to high standards. Does your business require you to be on call 24/7? Reality check: That’s not a business. It's a full-time job. ____ 2. Controlling capacity. I used to overcommit, say yes to everything and wonder why I burnt out. Then I realised: freedom comes from setting hard limits. Here’s how I protect my time: → Capping my workload. I only take on projects that fit in a 4-day workweek. That extra day? A built-in buffer for deep work and diversifying income streams. → Pre-qualifying clients. If someone needs round-the-clock availability, I’m not their person. I set expectations before signing contracts. → Booking work in advance. No more “can you squeeze this in?” Clients know my schedule fills fast, so they communicate in advance. If you’re always "busy", you don’t need more time. You need fewer commitments. ____ 3. Alignment checking. Every opportunity, task, meeting or business enquiry gets filtered through my "freedom lens" "Does this align with the business and life I want?" → If it can be handled async, it is. I prioritise meetings for client strategy, onboarding and reporting. → If it doesn’t drive a positive impact, it’s a no. If I can't deliver top results for you, I'll tell you from day one. → If it requires a meeting, it must have a purpose, a time limit and clear action points. Not all money is worth it. And sometimes, you're not the right person to do the "thing" presented to you. The fastest way to lose freedom? Chase work that doesn't align with your dream life. ____ REMEMBER THIS: Freedom isn’t something you "get" after building a business. It’s what you design your biz around. FYI: I'm not fully there yet. But I'm on my way!

The AWS downtime this week shook more systems than expected - here’s what you can learn from this real-world case study. 1. Redundancy isn’t optional Even the most reliable platforms can face downtime. Distributing workloads across multiple AZs isn’t enough.. design for multi-region failover. 2. Visibility can’t be one-sided When any cloud provider goes dark, so do its dashboards. Use independent monitoring and alerting to stay informed when your provider can’t. 3. Recovery plans must be tested A document isn’t a disaster recovery strategy. Inject a little chaos ~ run failover drills and chaos tests before the real outage does it for you. 4. Dependencies amplify impact One failing service can ripple across everything. You must map critical dependencies and eliminate single points of failure early. These moments are a powerful reminder that reliability and disaster recovery aren’t checkboxes .. They’re habits built into every design decision.

Retries are baked into most of our calls, but on their own, they’re selfish. They help you succeed, but they can push others over the edge. Retries don’t create resilience unless you combine them with timeouts, backoff, jitter, and idempotency. Without those, retries don’t fix problems; they amplify them. Here’s the basic playbook: 1. Timeouts Waiting forever is a trap. If a request drags on, cut it off. The longer it lingers, the more resources it hogs: - Threads - Memory - DB connections. Enough of those, and everything slows down. 2. Backoff Don’t hammer a struggling service. Spread out your retries. Give it room to recover. 3. Jitter If everyone retries at the same time, it’s a stampede. Add randomness. Spread the load. Be kind to your backend. Way safer. 4. Idempotency Some APIs have side effects, like sending emails or charging cards. If retries run wild, things break. Make those endpoints idempotent: Same input → same result → no duplicates. Retries should work with the system, not against it. If your retries add pressure, you're part of the problem. Design for recovery, not retries.