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Building software has become dramatically easier. It's exciting! And also a little dangerous. When the cost of building a prototype drops, the difficult work is no longer implementation. It shifts to more important up-front decisions. Deciding: • What problem is genuinely worth solving? • Who experiences it often enough to change behavior? • What should be simple, and what complexity is unavoidable? • What has to be true for a promising idea to become a reliable product? The best product work still begins with curiosity and a willingness to sit with the problem longer than feels comfortable, to obsess over details that others might not notice. A fast demo can create momentum. I have built my share of these! But customer trust is earned through the less glamorous things: clarity, resilience, thoughtful defaults, and an experience that holds up when real work happens. New tools, including AI, can help teams explore more possibilities. That is a gift. But they do not remove the need for product judgment. If anything, when we can build almost anything, judgment becomes more valuable: knowing what not to build, what to simplify, and what must be excellent.

One of the hardest technology decisions I've started appreciating is knowing when not to build. A business process feels slow. ➤ "We need software for this." A task is repetitive. ➤ "Let's automate it." Customers keep asking the same questions. ➤ "Let's build an app." The team needs better visibility. ➤ "Let's add another dashboard." Sometimes those are exactly the right decisions. But sometimes the technology is solving a problem that shouldn't exist in the first place. A process may be slow because there are too many unnecessary steps. A task may be repetitive because nobody questioned why it is being done manually. A dashboard may be needed because information is scattered across systems that should have been connected differently. And sometimes the simplest solution is to remove the work entirely. The more I work across both the business and technical sides of projects, the more I think this question deserves to come before "What should we build?" ➤ "Should this process exist at all?" That question changes the conversation. Instead of immediately choosing a technology, you start examining the work itself. • What is the actual business outcome? • Which steps genuinely contribute to it? • Which steps exist only because "that's how we've always done it"? • Can the process be simplified? • Can the work be removed? • And only then: does technology have a role? This is where I think good technology decisions differ from simply adopting technology. The goal isn't to put technology into every part of the business. The goal is to use technology where it creates a meaningful business advantage. Sometimes that means building. Sometimes it means automating. Sometimes it means buying. And sometimes the best solution is deleting a step from the process. I'm becoming increasingly convinced that one principle is worth keeping in mind: ➤ Don't digitize unnecessary work. Eliminate it first. As technology becomes easier and cheaper to adopt, the temptation to build will only increase. The real discipline may be knowing what not to build. Have you ever seen a technology project where simplifying the process would have been better than building another system?

One of the easiest mistakes in product building is automating a bad process. The workflow already feels slow. People repeat the same steps. Information moves between too many places. So the instinct is to build software around it. But automation doesn't fix confusion. It just makes confusion move faster. Before writing code, we try to ask a more basic question: 𝘚𝘩𝘰𝘶𝘭𝘥 𝘵𝘩𝘪𝘴 𝘴𝘵𝘦𝘱 𝘦𝘹𝘪𝘴𝘵 𝘢𝘵 𝘢𝘭𝘭? Sometimes the biggest improvement comes from removing a handoff. Combining two decisions. Clarifying who owns the next action. Or cutting a step nobody can explain. 𝗕𝗲𝘁𝘁𝗲𝗿 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗰𝗮𝗻𝗻𝗼𝘁 𝗿𝗲𝘀𝗰𝘂𝗲 𝗮 𝗯𝗮𝗱𝗹𝘆 𝗱𝗲𝘀𝗶𝗴𝗻𝗲𝗱 𝘀𝘆𝘀𝘁𝗲𝗺. That thinking has shaped how we approach 𝗟𝗲𝗺𝗧𝗮𝘀𝗸. The goal isn't to digitise every part of a workflow. It's to make the workflow easier to execute in the first place. Because once a process is clear, software can create real leverage. Before that, it usually creates a faster version of the same problem. #WorkflowDesign #ProductDevelopment #BuildInPublic #LemStudio

Some technical decisions don't stay technical for long. Especially once the business starts asking more of your product. Maybe you've gotten your first pilot running, and customers can sign up and use the core features. Then, the business moves. A larger customer wants something your current setup doesn't support easily. What looked like a fairly straightforward feature turns out to need considerably more work. Or maybe you discover that moving away from one service means moving two or three others too, because they all depended on the first. Suddenly, a decision buried somewhere in the build is affecting cost, timelines, and customers. This is one of the less obvious parts of building software with AI. The tool has to make tonnes of choices to turn your idea into a working product. Some might be exactly what your product needs. Some are sensible for where you are now. And some are worth noticing early, because they could make the next feature or stage of growth much harder than it needs to be. That's when a technical decision becomes a business one. It's useful not only to ask "does this work today?", but also "is there anything likely to get in the way of where we're heading next?"

A lot of software projects do not need more ideas. They need better constraints. When a project feels stuck, the instinct is often to brainstorm: more features, more options, more workflows, more ways to make the product useful. That can help, but it can also make the problem harder. Too many options create the feeling of progress while making the next decision less clear. Constraints are underrated because they feel limiting. But good constraints create focus. They force you to decide who the feature is for, what problem it solves, what trade-off you are willing to accept, and what you are intentionally not building yet. A useful planning question is: What constraint would make this decision easier? Maybe the constraint is time: we need to ship in two weeks. Maybe it is audience: this version is only for solo developers, not teams. Maybe it is behavior: the feature only matters if users repeat this workflow more than once. Maybe it is architecture: we will support one ownership model before adding flexibility. Without constraints, every idea can sound reasonable. With constraints, the shape of the work becomes clearer. That is one of the ideas behind https://gohakkle.com: helping developers think through planning, architecture, prioritization, and trade-offs while building real software. Curious how others approach this: what constraint usually helps you make better product or engineering decisions? #SoftwareEngineering #ProductDevelopment #SaaS #BuildInPublic

Building software is expensive. Building the wrong software is even more expensive. Many teams jump straight into development because they already have an idea of what customers want. Months later, they discover that the feature isn't solving the right problem, adoption is low, or the product needs major rework. The code wasn't the problem. The assumptions were. That's why a Blueprint Sprint starts with validation instead of development. Before a single line of production code is written, your team aligns on the business problem, creates a realistic prototype, and gathers feedback from real users. By the time development begins, you're building with evidence instead of guesswork. The result? ✓ Fewer unnecessary features ✓ Less costly rework ✓ Faster development with clearer priorities ✓ Greater confidence that you're building something customers actually need The cheapest feature is the one you never have to build. If you're planning a new product, platform, or AI initiative, a Blueprint Sprint can help you validate your direction before making a major investment. Ready to reduce product risk before development begins? Let's talk about how Cameo Labs can help.

The first version of a tool is rarely the final version. We ship rough. We get the core working. The main flow. The hero feature. We make it usable but not polished. Then we put it in front of the team and watch. What do they actually click? What do they ignore? What do they break in ways we did not predict? What do they ask for that we did not think of? What workaround do they invent that tells us the design is wrong? This is the most valuable information in software development. It only exists after real people use the tool. No amount of pre-design covers it. Then we refine. Most software projects try to build the final version on the first attempt. They spend six months getting it perfect, ship it, and discover that the team uses it differently than expected. Now they need another six months to fix it. They have spent a year. They have one tool. They are tired. We compress that cycle. Ship rough in two weeks. Refine for two more. The final tool is the one shaped by actual use, not assumption. This sounds risky. It is actually the opposite. Shipping rough exposes the real problems early, when they are cheap to fix. Shipping polished hides them until they are expensive. This is what Deeper Designs does. We ship rough fast and refine based on real use. Total time, usually three to five weeks. Total cost, much less than the polished alternative. If you are six months into a vendor build and nothing has shipped, message us. We will show you the rough version that should have shipped in week two. Message us: wa.me/919968716498 #BuildProcess #ShippingCulture #AIforSMB

Remember this when developing systems for other people's businesses: - What looks simple is complicated in reality - What appears hard is usually WAY harder in reality I've seen so many people theorize or scaffold elegant and complex system. But a normal user would find it unusable because they haven't been listened to or even included in the development process. We simply can't solve any problems and find a great solution unless we consistently talk to the people facing the problems. They might not be able to articulate a great solution but they know their problems and what a crap solution looks like.

More and more, I just want software to work without the frills, the shiny gimmicks, the feature bloat, the unreliability and the "we got rid of [x] thing, it's now part of [y] feature!" I just want it to bloody work without requiring me to be an Olympic athlete and jump through hoops! This year we seem to have traded reliability and user experience to get things in front of people faster. Software has always had bugs - no denying that, it's always an iteration process - it's just this problem is being magnified by development speed offered by AI. It moves so fast you never get to ask yourself if what you're doing is right. Review, iteration and refinement used to be the natural handbrakes. Companies should remember that features are fine, but your product is vulnerable if it constantly frustrates your users and eventually someone comes in with something more reliable. In my mind, doing several things well is more important that doing a lot of things terribly.

Great software doesn't expect human perfection. It plans for human reality. In my last two posts, I talked about keeping code simple and keeping user interfaces clear. But there’s another critical layer to software design that often gets overlooked: defensive UI. Software isn't used in a sterile lab by hyper-focused robots. Humans use it in the messy real world. Users get distracted. They skim text instead of reading carefully. Or, as anyone working from home knows, the cat jumps onto the desk, jostles your elbow, and your cursor slips two centimetres to the left just as you click. Suddenly, an important piece of data is gone. When an accidental click causes a minor catastrophe, that isn't the user's fault. It is a failure of software design to protect the user from themselves. Designing for human error requires two core principles: compassion and intentional friction. Nobody likes pop-ups that slow them down. If every single click triggers a "Do you want to proceed?" modal, users instantly develop "dialogue fatigue" and click "OK" without thinking. Friction needs to be applied intentionally: ⭐ Reserve hard stops for irreversible actions. If clicking a button permanently wipes data, make it red. Require confirmation. For critical deletions, make the user type "DELETE" into a box. ⭐ Warn on loss of context. If a user accidentally hits "Back" while typing a 500-word response, prompt them: "Are you sure you want to leave? Your unsaved changes will be lost." ⭐ Provide non-intrusive safety nets. For actions that can be undone, don't block the screen with a pop-up. Show a clean, temporary "Undo" notification at the bottom of the screen instead. Respecting the user means accepting that we all make mistakes, get distracted, and don't always read every word on the screen. Good software doesn't penalise people for being human; it builds a safety net beneath them. Designers and engineers, how do you balance creating a smooth user flow with building safety rails against accidental clicks? #UXDesign #SoftwareEngineering #UserExperience