How can you optimize your software development process and productivity using engineering principles?

This step requires a problem “Discovery” and a technical “Refinement”. The best teams I have worked with understand that coding is the very last step of a rich process that mostly happens away from keyboards and closer to whiteboards and post-it. They do these steps collaboratively with engineers, product people, designers, and business stakeholders. Because that’s the only way to build a high quality software that fulfills the customers needs.

There are some tips for it: 1. Clearly define your end product 2. Coding is the last thing you do, so never begin with coding in mind, always begin with the product 3. Direct all energy on clearly defining the product in sort of mathematical framework on paper, like inputs and outputs; this saves you time, energy and effort, and so you can throw away redundant parts 4. Always create an Architecture like model on paper clearly telling indicating what are the specific tasks in overall coding project 5. Make it streamlined process and do resource allocation for each task 6. Limit your resources (time and energy) on every coding task and keep safety limits in case if deadlines are not met!

Divide your problems into 1. Items that were reviewed in a previous development cycle and been dropped due to scope creep, time constraints etc,. 2. Items that are new and need spec-ing. 3. Technical debt. #1 can be picked right away. For #2 &#3, conduct workshops or sprint-0 to understand the problem statement, brainstorm and arrive at HLD. For process improvements, conduct frequent review and retrospective sessions and implement top 2 in the next cycle.

Understanding of the problem statement and then doing the impact analysis that would help in uncovering scenarios which need to be taken in consideration before making any new design changes.

You need metrics. People have opinions and that complicates the solution. Define metrics that capture the goals of your software and product. It’s hard sometimes which tells you that you need to learn how to align yourself with the product.

Choosing the best tools should be done objectively; not from one’s personal perspective based solely on career objectives or personal comfort zones. Introducing costly new architecture elements to a mature system disproportionate to the current problem’s scope under the guise of modernization can cause long term maintenance cost growth far outweighing the advantages being touted by those trained in the latest technology trend they desire to utilize on the system.

Tools should be objectively selected based on the project requirement, budget, cost, available expertise, support etc. There are lots of open source tools that may save cost however, it often, creates road blocks due to lack of dedicated support on production blocker issues. Hence timely tool support availability should also be a key factor in the tool selection.

There is no such thing as "best tool for all" - the best tool you have to pick differs based on the problem you want to solve. You can hack the wall with screwdriver and bolt to hang your picture, but it is not the best tool to do it because it's faster with a drill. But if you don't have a drill and you still need to spend on the other furniture, it probably not the best option to buy one and learn how to use it just for hanging 1 picture. Same thing goes with software development, make sure you see the bigger picture and pick the best tool for your condition, not blindly following the trend.

In software development, tool selection is a strategic decision that goes beyond mere familiarity or industry trends. The ideal tool is contingent upon the specific challenges at hand, the existing system's architecture, and long-term maintainability. It's essential to assess their relevance and cost-effectiveness for the given project. Just as one wouldn't use a screwdriver for a task best suited for a drill, in software, the tool should align with the problem's scope and the broader objectives of the project. It's about striking a balance between innovation and practicality, ensuring that the chosen tools enhance productivity without incurring unnecessary complexities or costs.

What is to be considered upon selecting a tool, are the following in my experience: - Is the selected solution mature enough to be used in production? - Do you have, or does your team have the knowledge to introduce something? If the later is missing, a dangerous one man standing show could start. - Is it really needed, or is it just something you want to try? Both have the place and time, but one must be aware of it.

Stick to Guidelines: Use design principles for clear software. Keep It Modular: Break software into manageable parts. Encapsulate & Abstract: Hide details, show essentials. Mind Cohesion & Coupling: Ensure relatedness and minimal dependencies. Embrace SOLID: It's a roadmap for robust software.

Write any software based on the fundamental principles. For example, programming in Java, C, C++ etc. has a proper format/style. Make sure you stick to the language principles, so it can be easily readable and digestible, and don't be innovative if unnecessary. It can make things complicated to understand.

Prototyping is an important step in the product development process to test a design or validate a concept. However, Just don’t turn your prototype to a product without checking user requirements

Design principles, like modularity, abstraction, and SOLID principles, are the building blocks of efficient software development. They encourage clean code that's easy to maintain and scale. Modularity keeps your codebase organized, abstraction simplifies complexity, and SOLID principles ensure your code is flexible and extensible. Embrace these principles, and you'll streamline your development process while producing high-quality software.

What one may consider a hard thing to beat is to define where lies the border between reusability/modularity and unnecessarily complex code. Always review your plans keeping in mind this.

Adhering to best practices invariably involves implementing a good review process. I believe that peer and senior code reviews, along with delivery reviews, are essential to maintaining the highest standards of practice.

I believe in uncovering better ways of doing software, not relying on "best practices". It is important to learn from the experience of others, and is often useful to have current "leading practices" as a staring point, but don't stop there. Look for people running trials/experiments and trying new things, and find the bright spots. Beware those that are re-litigating practices that were discovered to be less effective years ago. You'll be surprised at many of the practices you will find that are delivering outsized value but not yet widely known or practiced. As William Gibson said, "The future is already here – it's just not evenly distributed."

More often than not, best practices might seem to be overhead, especially when you are working on deadlines and in a rush to move your code. Getting in good code with reviews that are at least accepted in your team helps in managing your codebase as the project matures.

Don't reinvent the wheel all the time. Use templates and build on the top, code reviews, and version control online platforms like Git so that people can also look at your code and comment on it.

Stay Consistent: Follow coding standards. Review & Control: Use code reviews and version control. Document Everything: Keep clear records for clarity. Test & Debug: Ensure code is error-free. Refine & Deliver: Use refactoring and continuous delivery.

The feedback loop is crucial for developing a great product. It will never improve without it. The ability to accept feedback is just as important. They aren't insulting you. They aren't calling your baby ugly. They're asking for things that will make their experience better. Those same things will make your product better. Listen more than you speak.

Value all the customer feedback. That's the only way forward. Ensure you try to understand their requirement, think their way, and see the problem. Don't say no upfront. Don't resist change. Stagnant pool stinks. Flowing water is healthy for all.

It's crucial to learn from passive user feedback, like when users avoid certain actions or provide inaccurate information. Rather than blaming users, the challenge is to understand your target audience and optimize features and algorithms accordingly. For instance, in a location identification case, providing a map for users to pinpoint their addresses seemed like the default solution. However, after a month, it became clear that many users, especially those in tier two and three cities, were not proficient with maps. This bias had developed from interactions with delivery services, assuming everyone's familiarity with maps.

Feedback is like a party – everyone's invited, and they all bring their own flavor of advice. From users to pals, and even that one outspoken online troll, everyone's got their two cents. The trick? Keep your ears open, chuckle a bit, and then tweak that code. And hey, while you're at it, toss some feedback out there too. It's like a boomerang; you learn a ton when it comes back. Plus, giving feedback? It's like swapping dance shoes – you get to groove to someone else's coding beat for a change. Remember, feedback is the salsa on your coding nachos! 🌶️🎉

Easy, free and open communication with other company interfaces. Have retrospectives, post-mortems, monthly innovation meetings, joint work sessions. Don’t turn it into time sink, come to meetings with your points and questions, and strive to cover them all. Few examples: - Consider adopting new technology, support your claim with contained PoC. - Even in the face of repetitive rejection (company priorities notwithstanding), never stop raising points of improvement. - Agree to others’ ideas, most of them are easily implemented. - In lock-step with previous point, have A-B testable results for comparison. E.g., use different message queue, database engine, REST framework.

-Cross skill is crucial in the current state of the technology and competitive market. While the above mentioned techniques are standard there are few things managers and developers can do. -Managers can rotate devs based on their performance, flexibility and adaptability provided there are such opportunities in the team. -Devs can start ramp up on other projects of the team and slowly start contributing to them.

A great resource for navigating your career is the book "Apprenticeship Patterns". Don't be fooled by the name, as we're all an apprentice in some area of our career at any given point. They suggest many of the things outlined in the prompt, but I want to highlight that while a lot of individual effort is required to keep learning, it also can be more powerful as a collaborative effort. This is part of why I organize events (Software Crafters Unconference), meetups (SC Atlanta), and reading groups as a well facilitated gathering can be a powerful learning experience.

Being good in something should be the baseline, however it won't be enough forever. From time to time now possibilities will come up for you to not just deepen, but widen your knowledge. A developer with good devops and SQL skills will be always outstanding in any team, bringing in not just new opportunities but also good tasks to improve yourself further.

Focus on knowledge and skills shared in common. As knowledge and technology evolve 10x times every 5 years. Learning is an endless journey. When new things pop up every year, what's essential is your skills in problem-solving, learning, and thinking. Always work on the first principle that you can apply to every knowledge and technology by breaking it up and organizing it with your insights, transforming and digesting it in your model of view, and trying to understand it by linking it to other domains you are familiar with. For example, every year, there is always a new programming language and web dev framework. The only obstacle to entry is learning a new syntax, once you have understood the fundamentals of programming(CS).

1. Write less code 2. Be ruthless with prioritisation 3. Follow an iterative model and avoid Big Bang integration 4. Invest in DevOps

It is very important to understand the scope of different problems (other than agile) or stories (if you're following agile). Once scope is cleared it is easier to club together or break the stories and assign it to the specific engineer (UI/Backend/Full-stack/DB) and avoid the confusion during the development process. e.g. There could be different UI stories for different business cases. But once we discuss and clarify the scope, it could turn out that actually some of the UI stories for different business case are on the same UI module. Which could be done by one UI engineer in more quick and efficient manner than assigning it to multiple engineers. This is one of the major and common problem and could definitely boost productivity.

If you wish to optimize your productivity with programming anything is a code library of tried and trusted code. Most programs have repeated code in them. Package it in a way that is easy to implement as variables. Saves a lot of time.

Developing quality software with well-defined practices, informed by engineering principles: it's a team sport, and a long game. If you're writing throwaway code, they seem to matter less. I think they matter more. One-off code has a way of sticking around far longer than anyone expected. If it's an unreadable schmear, chances are the authors didn't put their name to it either -- why would they? Communication and debate amongst the team members is crucial. If consensus if often immediate, chances are no one's reading the code all that closely. That's the beginning of the end for any project you hope to sustain and maintain.

Conscious thinking about robust test automation and continuous integration into the early unit testing will go a long way improving the quality of the end product. Testing and test case development should be integrated into every phase of the product development life cycle, like early software architecture, design, implementation, testing and launch. Catching a bug early saves a lot on the downstream hence, testing should get more focus early in the project.