The goal of this page is to make you a more proficient developer. You'll find only resources that I've found truly inspiring, or that have become timeless classics.
Master](http://www.amazon.com/The-Pragmatic-Programmer-Journeyman-Master/dp/020161622X) 📖: hands-on the most inspiring and useful book I've read about programming.
Construction](http://www.amazon.com/Code-Complete-Practical-Handbook-Construction/dp/0735619670) 📖: a nice addition to The Pragmatic Programmer, gives you the necessary framework to talk about code.
* [Release It!](https://smile.amazon.com/Release-Design-Deploy-Production-Ready-Software/dp/1680502395) 📖: this books goes beyond code and gives you best practices for building production-ready software. It will give you about 3 years worth of real-world experience.
* [The Linux Programming Interface: A Linux and UNIX System Programming Handbook](http://www.amazon.com/The-Linux-Programming-Interface-Handbook/dp/1593272200) 📖: outside of teaching you almost everything you need to know about Linux, this book will give you insights into how software evolves, and the value of having simple & elegant interfaces.
* [Structure and interpretation of Computer Programs](https://web.mit.edu/alexmv/6.037/sicp.pdf) (free) 📖: One of the most influential textbooks in Computer Science (written and used at MIT), SICP has been influential in CS education. [Byte](https://en.wikipedia.org/wiki/Byte_(magazine)) recommended SICP "for professional programmers who are really interested in their profession".
* [Professional software development](http://mixmastamyk.bitbucket.io/pro_soft_dev/) 📖: pretty complete and a good companion to this page. The free chapters are mostly focused on software development processes: design, testing, code writing, etc. - and not so much about tech itself.
* [Practical Advice for New Software Engineers](http://product.hubspot.com/blog/practical-advice-for-new-software-engineers)
* [On Being A Senior Engineer](http://www.kitchensoap.com/2012/10/25/on-being-a-senior-engineer/)
* [Lessons Learned in Software Development](http://henrikwarne.com/2015/04/16/lessons-learned-in-software-development/): one of those articles that give you years of hard-earned lessons, all in one short article. Must read.
* [How to Build Good Software](https://www.csc.gov.sg/articles/how-to-build-good-software)
* A good high-level summary of fundamental engineering practices.
* The root cause of bad software has less to do with specific engineering choices, and more to do with how development projects are managed.
* There is no such thing as platonically good engineering: it depends on your needs and the practical problems you encounter.
* Software should be treated not as a static product, but as a living manifestation of the development team’s collective understanding.
* Software projects rarely fail because they are too small; they fail because they get too big.
* Beware of bureaucratic goals masquerading as problem statements. If our end goal is to make citizens’ lives better, we need to explicitly acknowledge the things that are making their lives worse.
* Building software is not about avoiding failure; it is about strategically failing as fast as possible to get the information you need to build something good.
* [The Imposter's Handbook](https://bigmachine.io/products/the-imposters-handbook) - $30. From the author: "Don't have a CS Degree? Neither do I - That's why I wrote this book."
* [mr-mig/every-programmer-should-know: a collection of (mostly) technical things every software developer should know](https://github.com/mr-mig/every-programmer-should-know)
* Read the [CLRS](https://mitpress.mit.edu/books/introduction-algorithms). You can watch and download the course on [OCW](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-introduction-to-algorithms-sma-5503-fall-2005/) - there are newer courses as well.
* Or [The Algorithm Design Manual](https://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1849967202?ie=UTF8&qid=1297127794&ref_=sr_1_1&sr=8-1)
* Try out some algorithms on [Project Euler](https://projecteuler.net/)
Let's be honest: algorithms can be a pretty dry topic. [This quora question](https://www.quora.com/Is-there-a-book-that-teaches-algorithms-data-structures-and-other-computer-science-basics-in-a-fun-way) lists some funnier learning alternative, including:
* [Why you should use links, not keys, to represent relationships in APIs](https://cloud.google.com/blog/products/application-development/api-design-why-you-should-use-links-not-keys-to-represent-relationships-in-apis), Martin Nally, Google
* "Using links instead of foreign keys to express relationships in APIs reduces the amount of information a client needs to know to use an API, and reduces the ways in which clients and servers are coupled to each other."
* [Ten minutes a day](https://blog.usejournal.com/ten-minutes-a-day-e2fa1084f924): how Alex Allain wrote a book in less than 200 hours, by writing 10 minutes *every* day.
* [The care and feeding of software engineers (or, why engineers are grumpy)](https://humanwhocodes.com/blog/2012/06/12/the-care-and-feeding-of-software-engineers-or-why-engineers-are-grumpy/)
* In the triumvirate of software, product managers, designers, and software engineers, only the engineers are expected to turn off their creative minds and just produce.
* Both engineers and product managers tend to think, incorrectly, that product specifications or requirements are equivalent to the furniture manual from Ikea.
* This is one of the top things that make engineers grumpy: constantly shifting priorities.
* Even though many engineers will complain that product managers change their minds, almost none will account for that in their time estimates.
* Computer science programs aren’t about preparing you for the tasks you’ll face in industry.
* When there are more engineers than can be used, engineering time ends up going away from developing and towards planning, synchronization, and coordination.
* Involve engineers in the creative process
* Give engineers opportunities to be creative.
* Encourage time off.
* Let 'em code
* Express appreciation
* [The Product-Minded Software Engineer](https://blog.pragmaticengineer.com/the-product-minded-engineer/), Gergely Orosz
* Great product engineers know that minimum lovable products need the right depth
* Product-minded engineers quickly map out edge cases and think of ways to reduce work on them: often bringing solutions that require no engineering work
* Engage in user research and customer support
* Bring well-backed product suggestions to the table
Biases don't only apply to hiring. For instance, the fundamental attribution bias also applies when criticizing somebody's code written a long time ago, in a totally different context.
* [The Conjoined Triangles of Senior-Level Development](http://frontside.io/blog/2016/07/07/the-conjoined-triangles-of-senior-level-development.html) looks into how to define a senior engineer.
* [Why Good Developers are Promoted into Unhappiness](https://robwalling.com/2007/06/27/why-good-developers-are-promoted-into-unhappiness/), Rob Walling. Or why management might not be for you.
* [The Absolute Minimum Every Software Developer Absolutely, Positively Must Know About Unicode and Character Sets (No Excuses!)](http://www.joelonsoftware.com/articles/Unicode.html)
* [Write code that is easy to delete, not easy to extend](http://programmingisterrible.com/post/139222674273/write-code-that-is-easy-to-delete-not-easy-to)
* [The Ten Commandments of Egoless Programming](http://blog.codinghorror.com/the-ten-commandments-of-egoless-programming/)
* [Clean Code: A Handbook of Agile Software Craftsmanship](https://www.goodreads.com/book/show/3735293-clean-code) 📖, Robert C. Martin. Describes numerous useful best practices. A bit long. There's also a [clean code cheatsheet](cheatsheets/Clean-Code-V2.4.pdf).
* [Safe Operations For High Volume PostgreSQL](https://www.braintreepayments.com/blog/safe-operations-for-high-volume-postgresql/) (this is for PostgreSQL but works great for other DBs as well).
* [Zero downtime database migrations](https://blog.rainforestqa.com/2014-06-27-zero-downtime-database-migrations/) (code examples are using Rails but this works great for any programming language)
* [The Infinite Hows](http://www.kitchensoap.com/2014/11/14/the-infinite-hows-or-the-dangers-of-the-five-whys/): this provides a strong criticism of the five whys method.
* [Linux Performance Analysis in 60,000 Milliseconds](http://techblog.netflix.com/2015/11/linux-performance-analysis-in-60s.html)
I highly recommend reading [The Non-Designer's Design Book](http://www.amazon.com/gp/product/0133966151/ref=pd_lpo_sbs_dp_ss_1?pf_rd_p=1944687602&pf_rd_s=lpo-top-stripe-1&pf_rd_t=201&pf_rd_i=0321534042&pf_rd_m=ATVPDKIKX0DER&pf_rd_r=1R7MVQP0BCP7GP9VZGYX). This is a pretty short book that will give you some very actionable design advices.
* If you're working on data, Edward Tufte's [The Visual Display of Quantitative Information](http://www.amazon.com/Visual-Display-Quantitative-Information/dp/0961392142/ref=sr_1_1?ie=UTF8&qid=1458046603&sr=8-1&keywords=tufte) is considered a classic.
* The [Universal Principles of Design](http://www.amazon.com/Universal-Principles-Design-Revised-Updated/dp/1592535879/ref=sr_1_1?ie=UTF8&qid=1458046663&sr=8-1&keywords=universal+principles+of+design) will give you enough vocabulary and concepts to describe design challenges into words.
* [Microsoft's Rest API guidelines](https://github.com/Microsoft/api-guidelines/blob/master/Guidelines.md)
* [Design Patterns: Elements of Reusable Object-Oriented Software](http://www.amazon.com/dp/0201633612/): dubbed "the gang of four", this is almost a required reading for any developer. A lot of those are a bit overkill for Python (because everything is an object, and dynamic typing), but the main idea (composition is better than inheritance) definitely is a good philosophy.
* [Patterns of Enterprise Application Architecture](http://www.amazon.com/dp/0321127420/?tag=stackoverfl08-20): learn about how database are used in real world applications. Mike Bayer's SQLAlchemy has been heavily influenced by this book.
* [Domain-Driven Design: Tackling Complexity in the Heart of Software](https://www.amazon.com/Domain-Driven-Design-Tackling-Complexity-Software/dp/0321125215) 📖, Eric Evans
* [Clean Architecture](https://www.goodreads.com/book/show/18043011-clean-architecture) 📖, Robert C. Martin. Uncle Bob proposes an architecture that leverages the Single Responsibility Principle to its fullest. A great way to start a new codebase. Also checkout the [clean architecture cheatsheet](cheatsheets/Clean-Architecture-V1.0.pdf).
* [Python Design Patterns: For Sleek And Fashionable Code](https://www.toptal.com/python/python-design-patterns): a pretty simple introduction to common design patterns (Facade, Adapter, Decorator). A more complete list of design patterns implementation in Python on [Github](https://github.com/faif/python-patterns). [Also a book here](http://python-3-patterns-idioms-test.readthedocs.io/en/latest/PatternConcept.html).
* SourceMaking's [Design Patterns](https://sourcemaking.com/design_patterns) seems to be a good web resource too.
* O'Reilly's [How to make mistakes in Python](http://www.oreilly.com/programming/free/files/how-to-make-mistakes-in-python.pdf)
* [Education of a Programmer](https://hackernoon.com/education-of-a-programmer-aaecf2d35312): a developer's thoughts after 35 years in the industry. There's a particularly good section about design & complexity (see "the end to end argument", "layering and componentization").
* Google's [API Design Guide](https://cloud.google.com/apis/design/): a general guide to design networked API.
* [Inheritance vs. composition](http://learnpythonthehardway.org/book/ex44.html): a concrete example in Python. [Another slightly longer one here](http://python-textbok.readthedocs.io/en/latest/Object_Oriented_Programming.html). [One last one, in Python 3](http://blog.thedigitalcatonline.com/blog/2014/08/20/python-3-oop-part-3-delegation-composition-and-inheritance/#.V7SZ4tB96Rs).
* [Composition Instead Of Inheritance](http://c2.com/cgi/wiki?CompositionInsteadOfInheritance)
* [Complexity and Strategy](https://hackernoon.com/complexity-and-strategy-325cd7f59a92): interesting perspective on complexity and flexibility with really good examples (e.g. Google Apps Suite vs. Microsoft Office).
* [Simple Made Easy](https://www.infoq.com/presentations/Simple-Made-Easy) 🎞, Rich Hickey. This is an incredibly inspiring talk redefining simplicity, ease and complexity, and showing that solutions that look easy may actually harm your design.
* [Writing automated tests for your documentation](https://krausefx.com/blog/writing-automated-tests-for-your-documentation): this should be required, IMO. Testing code samples in your documentation ensures they never get outdated.
* [Setting Up a Mac Dev Machine From Zero to Hero With Dotfiles](http://code.tutsplus.com/tutorials/setting-up-a-mac-dev-machine-from-zero-to-hero-with-dotfiles--net-35449)
* Bram Moolenaar (Vim author), [Seven habits of effective text editing](http://www.moolenaar.net/habits.html) ([presentation](http://www.moolenaar.net/habits_2007.pdf)). This is about Vim but it contains good lessons about why investing time in learning how to be productive with your text editors pays off.
* [VScode](https://code.visualstudio.com/) is one of the most popular text editors as of writing. [Visual Studio Code Can Do That?](https://www.smashingmagazine.com/2018/01/visual-studio-code/), Smashing Magazine.
* [Challenging projects every programmer should try](http://web.eecs.utk.edu/~azh/blog/challengingprojects.html): text editor, space invaders, compiler (Tiny Basic), mini OS, spreadsheet, video game console emulator.
* [My Philosophy On Alerting](https://linuxczar.net/sysadmin/philosophy-on-alerting/)
* Pages should be urgent, important, actionable, and real.
* Err on the side of removing noisy alerts – over-monitoring is a harder problem to solve than under-monitoring.
* Symptoms are a better way to capture more problems more comprehensively and robustly with less effort.
* Include cause-based information in symptom-based pages or on dashboards, but avoid alerting directly on causes.
* The further up your serving stack you go, the more distinct problems you catch in a single rule. But don’t go so far you can’t sufficiently distinguish what’s going on.
* If you want a quiet oncall rotation, it’s imperative to have a system for dealing with things that need timely response, but are not imminently critical.
* A great example of a [postmortem from Gitlab (01/31/2017)](https://about.gitlab.com/2017/02/01/gitlab-dot-com-database-incident/) for an outage during which an engineer's action caused the irremediable loss of 6 hours of data.
Note: this is about you as an interviewee, **not** as an interviewer. To check out my list of resources for interviewers, go to my [engineering-management repository](https://github.com/charlax/engineering-management#hiring-interviews).
* [I spent 3 months applying to jobs after a coding bootcamp. Here’s what I learned.](https://medium.freecodecamp.com/5-key-learnings-from-the-post-bootcamp-job-search-9a07468d2331#.uq7vbbjfx)
* [Questions to ask the company during your interview](https://github.com/viraptor/reverse-interview)
* [A complete computer science study plan to become a software engineer](https://github.com/jwasham/coding-interview-university), jwasham/coding-interview-university
* [How I Rewired My Brain to Become Fluent in Math](http://nautil.us/issue/40/learning/how-i-rewired-my-brain-to-become-fluent-in-math-rp): subtitled *the building blocks of understanding are memorization and repetition*.
* [One Sure-Fire Way to Improve Your Coding](https://changelog.com/posts/one-sure-fire-way-to-improve-your-coding): reading code!
* [Tips for learning programming](http://blog.hiphipjorge.com/tips-for-learning-programming/)
* [You can increase your intelligence: 5 ways to maximize your cognitive potential](https://blogs.scientificamerican.com/guest-blog/you-can-increase-your-intelligence-5-ways-to-maximize-your-cognitive-potential/): forgive the clickbait title, it’s actually a good article.
* [Learning How to Learn](https://www.coursera.org/learn/learning-how-to-learn): powerful mental tools to help you master tough subjects
* [Why books don’t work](https://andymatuschak.org/books/), Andy Matuschak.
* "As a medium, books are surprisingly bad at conveying knowledge, and readers mostly don’t realize it."
* "In learning sciences, we call this model “transmissionism.” It’s the notion that knowledge can be directly transmitted from teacher to student, like transcribing text from one page onto another. If only!"
* "By re-testing yourself on material you’ve learned over expanding intervals, you can cheaply and reliably commit huge volumes of information to long-term memory."
* [Strategies, Tips, and Tricks for Anki](https://senrigan.io/blog/everything-i-know-strategies-tips-and-tricks-for-spaced-repetition-anki/): those advices work for any tool actually
* Add images. Our brains are wired visually, so this helps retention.
* Don't add things you don't understand.
* Don't add cards memorizing entire lists.
* Write it out. For wrong answers, I'll write it on paper. The act of writing is meditative. I really enjoy this.
* Keep on asking yourself why? why does this work? why does it work this way? Force yourself to understand the root of a topic.
* Cornell Method: when reading a topic, write out questions on the margins to quiz yourself.
* Pretend you have to teach it
* Use mnemonics phrases like PEMDAS for lists and other hard-to-remember topics.
* Delete cards that don't make sense or you don't want to remember anymore.
* [Effective learning: Twenty rules of formulating knowledge](https://www.supermemo.com/en/archives1990-2015/articles/20rules)
* Build upon the basics
* Stick to the minimum information principle: the material you learn must be formulated in as simple way as it is
* Cloze deletion is easy and effective: Kaleida's mission was to create a ... It finally produced one, called Script X. But it took three years
* Graphic deletion is as good as cloze deletion
* Avoid sets
* Avoid enumerations
* Combat interference - even the simplest items can be completely intractable if they are similar to other items. Use examples, context cues, vivid illustrations, refer to emotions, and to your personal life
* Personalize and provide examples - personalization might be the most effective way of building upon other memories. Your personal life is a gold mine of facts and events to refer to. As long as you build a collection for yourself, use personalization richly to build upon well established memories
* Provide sources - sources help you manage the learning process, updating your knowledge, judging its reliability, or importance
* Prioritize - effective learning is all about prioritizing.
* [How to Remember Anything You Really Want to Remember, Backed by Science](https://www.inc.com/jeff-haden/how-to-remember-anything-you-really-want-to-remember-backed-by-science.html)
* Quiz yourself
* Summarize and share with someone else.
* Connect what you just learned to experiences you previously had.
> Frankly, though, I think most people can learn a lot more than they think they can. They sell themselves short without trying.
> One bit of advice: it is important to view knowledge as sort of a semantic tree—make sure you understand the fundamental principles, ie the trunk and big branches, before you get into the details/leaves or there is nothing for them to hang on to.
* [Back to Basics](https://www.joelonsoftware.com/2001/12/11/back-to-basics/), Joel Spolsky. Explains why learning low level programming is important.
* I think that some of the biggest mistakes people make even at the highest architectural levels come from having a weak or broken understanding of a few simple things at the very lowest levels.
### Network
* [The Great Confusion About URIs](https://benbernardblog.com/the-great-confusion-about-uris/)
* A URI is a string of characters that identifies a resource. Its syntax is `<scheme>:<authority><path>?<query>#<fragment>`, where only `<scheme>` and `<path>` are mandatory. URL and URN are URIs.
* A URL is a string of characters that identifies a resource located on a computer network. Its syntax depends on its scheme. E.g. `mailto:billg@microsoft.com`.
* A URN is a string of characters that uniquely identifies a resource. Its syntax is `urn:<namespace identifier>:<namespace specific string>`. E.g. `urn:isbn:9780062301239`
* JavaScript and maybe another interpreted language (Python, Ruby, etc.). Interpreted languages are useful for quick one-off automation scripts, and fastest to write for interviews. JavaScript is ubiquitous.
* [Effective Programs - 10 Years of Clojure](https://www.youtube.com/watch?v=2V1FtfBDsLU) 🎞, Rich Hickey. The author of Clojure reflects on his programming experience and explains the rationale behind some of Clojure's key design decisions.
* [Learn more programming languages, even if you won't use them](https://thorstenball.com/blog/2019/04/09/learn-more-programming-languages/), Thorsten Ball
* These new perspectives, these ideas and patterns — they linger, they stay with you, even if you end up in another language. And that is powerful enough to keep on learning new languages, because one of the best things that can happen to you when you’re trying to solve a problem is a change of perspective.
JavaScript is such a pervasive language that it's almost required learning.
* [mbeaudru/modern-js-cheatsheet](https://github.com/mbeaudru/modern-js-cheatsheet): cheatsheet for the JavaScript knowledge you will frequently encounter in modern projects.
* [Functional Programming Fundamentals](https://www.matthewgerstman.com/functional-programming-fundamentals/): short introduction to FP and its advantages.
* [OO vs FP](https://blog.cleancoder.com/uncle-bob/2014/11/24/FPvsOO.html), Robert C. Martin, The Clean Code Blog. A pretty interesting take on the differences between OOP and FP from an expert in OOP.
* OO is not about state. Objects are bags of functions, not bags of data.
* Functional Programs, like OO Programs, are composed of functions that operate on data.
* FP imposes discipline upon assignment.
* OO imposes discipline on function pointers.
* The principles of software design still apply, regardless of your programming style. The fact that you’ve decided to use a language that doesn’t have an assignment operator does not mean that you can ignore the Single Responsibility Principle.
* [10 modern software over-engineering mistakes](https://medium.com/@rdsubhas/10-modern-software-engineering-mistakes-bc67fbef4fc8#.da6dvzyne)
* [A good example of over-engineering: the Juicero press](https://blog.bolt.io/heres-why-juicero-s-press-is-so-expensive-6add74594e50) (April 2017)
> “A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over, beginning with a working simple system.”
* [Papers we love](https://github.com/papers-we-love/papers-we-love): papers from the computer science community to read and discuss. Can be a good source of inspiration of solving your design problems.
* [My First 10 Minutes On a Server - Primer for Securing Ubuntu](http://www.codelitt.com/blog/my-first-10-minutes-on-a-server-primer-for-securing-ubuntu/)
* [Reckon you've seen some stupid security things?](https://www.troyhunt.com/reckon-youve-seen-some-stupid-security-things-here-hold-my-beer/): everything *not* to do.
* [Checklist of the most important security countermeasures when designing, testing, and releasing your API](https://github.com/shieldfy/API-Security-Checklist)
* [OWASP Cheat Sheet Series](https://cheatsheetseries.owasp.org/): a series of
* [High Scalability](http://highscalability.com/): great blog about system architecture, its weekly review article are packed with numerous insights and interesting technology reviews. Checkout the [all-times favorites](http://highscalability.com/all-time-favorites/).
* [Deep Lessons From Google And EBay On Building Ecosystems Of Microservices](http://highscalability.com/blog/2015/12/1/deep-lessons-from-google-and-ebay-on-building-ecosystems-of.html)
* [Service oriented architecture: scaling the Uber engineering codebase as we grow](https://eng.uber.com/soa/)
* [The Log: What every software engineer should know about real-time data's unifying abstraction](https://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying): one of those classical articles that everyone should read.
* I already mentioned the book Scalability rules above, but there's also a [presentation](http://www.slideshare.net/cyrilwang/scalability-rules) about it.
#### Stability
* I already mentioned the book Release it! above. There's also a [presentation](http://www.slideshare.net/justindorfman/stability-patterns-presentation) from the author.
* [The Walking Dead - A Survival Guide to Resilient Applications](https://speakerdeck.com/daschl/the-walking-dead-a-survival-guide-to-resilient-applications)
* [Defensive Programming & Resilient systems in Real World (TM)](https://speakerdeck.com/tuenti/defensive-programming-and-resilient-systems-in-real-world-tm)
* [Full Stack Fest: Architectural Patterns of Resilient Distributed Systems](https://speakerdeck.com/randommood/full-stack-fest-architectural-patterns-of-resilient-distributed-systems)
* Written by members of Google's SRE team, with a comprehensive analysis of the entire software lifecycle - how to build, deploy, monitor, and maintain large scale systems.
* [Graduating from Bootcamp and interested in becoming a Site Reliability Engineer?](https://medium.com/@tammybutow/graduating-from-bootcamp-and-interested-in-becoming-a-site-reliability-engineer-b69a38ce858b): a great collection of resources to learn about SRE.
* [Operating a Large, Distributed System in a Reliable Way: Practices I Learned](https://blog.pragmaticengineer.com/operating-a-high-scale-distributed-system/)
* [Testing Strategies in a Microservices Architecture](http://martinfowler.com/articles/microservice-testing/) (Martin Fowler) is an awesome resources explaining how to test a service properly.
* [A Quick Puzzle to Test Your Problem Solving](http://www.nytimes.com/interactive/2015/07/03/upshot/a-quick-puzzle-to-test-your-problem-solving.html?_r=0)... and a great way to learn about confirmation bias and why you're mostly writing positive test cases.
* [The test pyramid](http://martinfowler.com/bliki/TestPyramid.html)
* [Move fast and don't break things](https://docs.google.com/presentation/d/15gNk21rjer3xo-b1ZqyQVGebOp_aPvHU3YH7YnOMxtE/edit#slide=id.g437663ce1_53_591) (presentation)
* [Eradicating Non-Determinism in Tests](http://www.martinfowler.com/articles/nonDeterminism.html), Martin Fowler
* [Write tests. Not too many. Mostly integration.](https://blog.kentcdodds.com/write-tests-not-too-many-mostly-integration-5e8c7fff591c) for a contrarian take about unit testing...
* [Testing is Not for Beginners](https://www.calhoun.io/testing-is-not-for-beginners/): why learning to test is hard. This shouldn't demotivate you though!
* [Your non-linear problem of 90% utilization](https://blog.asmartbear.com/utilization.html), Jason Cohen: why constantly running at 90% utilization is actually counter-productive.
* [Evidence-based advice on how to be successful in any jobs](https://80000hours.org/career-guide/how-to-be-successful/): most self-help advices are not research-based. The ones listed in this article are.
* [Makers, Don't Let Yourself Be Forced Into the 'Manager Schedule'](https://blog.nuclino.com/makers-don-t-let-yourself-be-forced-into-the-manager-schedule)
* Research shows that it takes as long as 30 minutes for makers to get into the flow
* Use maker-manager office hours
* Communication can happen at a quieter asynchronous frequency in the form of thoughtful, written discussions rather than soul-sucking meetings or erratic one-line-at-a-time chat messages
* Build a team knowledge base to minimize repetitive questions and allow self-onboarding.
* From the HN discussion: "Writing a couple of pages of design docs or an Amazon-style 6 pager or whatever might take a few days of work, but can save weeks or more of wasted implementation time when you realise your system design was flawed or it doesn't address any real user needs."
