I recently delivered a presentation of our (outcome-based) roadmap. Several people approached me after the presentation to tell me that they found it useful and informative, so I thought I’d jot down some of the things that I think contributed to the warm reception of the presentation. Hopefully, these tips will come in handy both for others and for my future self.
Maybe Don't Inject That I’m actually always suspicious when I’m writing up a pattern or a technique if I can’t talk about reasons when you shouldn’t use and trade-offs against it. If I can’t find arguments against it, then I’m worrying that I’m not really analyzing things properly. –Martin Fowler, “Is TDD Dead?”, 35:00 DI is useful. It’s great. It makes your code more flexible, testable, etc. Dagger? Also useful. Great. My favorite DI library.
Maybe Don't Write That Test Testing seems to be like going to gym. Everyone feels like “yeah. I should be testing. I should be going to the gym everyday.” Koushik Goupal, Fragmented, “Episode 13,” 12:01 Remember those gimmicky fitness products that made you think you could “get fit” without actually going to the gym/dieting/etc? Because I live in Orlando and have seen the Carousel of Progress at the Magic Kingdom a bunch of times, the first example of this kind of gimmicky product that comes to mind is a thing called an “exercise belt.
A Neural Network in Kotlin (Pt. 1) !!!! This is just a draft of a post that I’ve published for review !!! Introduction Neural networks can be a good strategy for solving machine learning problems. Just like I did with gradient descent and linear regression, I want to try to give you an idea of how they work and how you’d implement one from scratch1 in Kotlin. I’ll be using the mnist handwritten digit data set.
An Intro to Gradient Descent for Kotlin Programmers Introduction Gradient descent is an algorithm that’s used to solve supervised learning and deep learning problems. Here I’m going to try to give you an idea of why the algorithm works and how you’d implement it in Kotlin. I’ll also show the algorithm working with a simple kaggle dataset involving video game sales and ratings. Everything I cover here is covered in Andrew Ng’s excellent Coursera machine learning course with the exception of the Kotlin implementation of gradient descent.
Dagger 2, 2 Years Later …in software, feedback cycles tend to be on the order of months, if not years…It’s during the full lifetime of a project that a developer gains experience writing code, source controlling it, modifying it, testing it, and living with previous design and architecture decisions during maintenance phases. With everything I’ve just described, a developer is lucky to have a first try of less than six months… –Erik Dietrich, “How Developers Stop Learning: Rise of the Expert Beginner”
Maybe we Should Stop Creating Inscrutable CLIs In the original Unix tradition, command-line options are single letters preceded by a single hyphen…The original Unix style evolved on slow ASR-33 teletypes that made terseness a virtue; thus the single-letter options. Eric Steven Raymond, The Art of Unix Programming Programs must be written for people to read, and only incidentally for machines to execute. Abelson et. al., Structure and Interpretation of Computer Programs I just wrote this little bash-ism the other day for removing all attachments from a jira ticket:
Some Tips for Delivering an Effective Roadmap Presentation
How to Automate Common Jira Tasks with Go Jira Custom Commands in all but small teams I typically recommend separate people for the separate roles [of product managment and project management]. But in every case I believe that developing strong project management skills is a big advantage for product managers – at the least your product will get to market faster, and it could make the difference between getting your product shipped at all. –Marty Cagan, “Ebay’s Secret Weapon”