200 Matching Annotations
  1. Feb 2021
    1. A second trap is thinking that you just need to work on yourself in order to grow your career. For example, "To progress, I just need to get better at [insert skill.]" But you are only one part of the equation.There is a whole other part of the equation, which is your environment. Your environment either limits or amplifies your own ability to get better at a skill.
      • Trap: "I just need to work on myself more"
      • Assumption: You need to focus on improving X
      • Impact: You need to consider the environment. if you don't, you could end up in a place that limits your ability to work on that skill instead of amplify it.
    2. Evaluating impact isn't easy. It is complicated by a few factors:Impact is the result of multiple other variables.Those variables are interrelated and have confounding factors.Impact can be subjective to the individual.A lot of times you aren't even aware of what is holding you back, or what to evaluate on.

      If impact is the input that powers career progression, what are the complicating factors and why?

    3. "Should I leave my current role?""How do I compare or choose between two or more opportunities?""What is preventing me from moving forward?"
      • do we switch projects?
      • teams?
      • career paths?
      • what projects do we take on, vs not, and why?
  2. Jan 2021
    1. I can't recommend the Data Engineer career enough for junior developers. It's how I started and what I pursued for 6 years (and I would love doing it again), and I feel like it gave me such an incredible foundation for future roles :- Actually big data (so, not something you could grep...) will trigger your code in every possible way. You quickly learn that with trillions of input, the probabily to reach a bug is either 0% or 100%. In turn, you quickly learn to write good tests.- You will learn distributed processing at a macro level, which in turn enlighten your thinking at a micro level. For example, even though the order of magnitudes are different, hitting data over network versus on disk is very much like hitting data on disk versus in cache. Except that when the difference ends up being in hours or days, you become much more sensible to that, so it's good training for your thoughts.- Data engineering is full of product decisions. What's often called data "cleaning" is in fact one of the import product decisions made in a company, and a data engineer will be consistently exposed to his company product, which I think makes for great personal development- Data engineering is fascinating. In adtech for example, logs of where ads are displayed are an unfiltered window on the rest of humanity, for the better or the worse. But it definitely expands your views on what the "average" person actually does on its computer (spoiler : it's mainly watching porn...), and challenges quite a bit what you might think is "normal"- You'll be plumbing technologies from all over the web, which might or might not be good news for you.So yeah, data engineering is great ! It's not harder than other specialties for developers, but imo, it's one of the fun ones !

      Many reasons why Data Engineer is a great starting position for junior developers

    1. Downloading a pretrained model off the Tensorflow website on the Iris dataset probably is no longer enough to get that data science job. It’s clear, however, with the large number of ML engineer openings that companies often want a hybrid data practitioner: someone that can build and deploy models. Or said more succinctly, someone that can use Tensorflow but can also build it from source.

      Who the industry really needs

    2. When machine learning become hot 🔥 5-8 years ago, companies decided they need people that can make classifiers on data. But then frameworks like Tensorflow and PyTorch became really good, democratizing the ability to get started with deep learning and machine learning. This commoditized the data modelling skillset. Today, the bottleneck in helping companies get machine learning and modelling insights to production center on data problems.

      Why Data Engineering became more important

    3. Overall the consolidation made the differences even more pronounced! There are ~70% more open data engineer than data scientist positions. In addition, there are ~40% more open ML engineer than data scientist positions. There are also only ~30% as many ML scientist as data scientist positions.

      Takeaway from the analysis:

      • ~70% more open data engineer than data scientist positions
      • ~40% more open ML engineer than data scientist positions
      • only ~30% as many ML scientist as data scientist positions
    4. Data scientist: Use various techniques in statistics and machine learning to process and analyse data. Often responsible for building models to probe what can be learned from some data source, though often at a prototype rather than production level. Data engineer: Develops a robust and scalable set of data processing tools/platforms. Must be comfortable with SQL/NoSQL database wrangling and building/maintaining ETL pipelines. Machine Learning (ML) Engineer: Often responsible for both training models and productionizing them. Requires familiarity with some high-level ML framework and also must be comfortable building scalable training, inference, and deployment pipelines for models. Machine Learning (ML) Scientist: Works on cutting-edge research. Typically responsible for exploring new ideas that can be published at academic conferences. Often only needs to prototype new state-of-the-art models before handing off to ML engineers for productionization.

      4 different data profiles (and more): consolidated:

    5. I scraped the homepage URLs of every YC company since 2012, producing an initial pool of ~1400 companies. Why stop at 2012? Well, 2012 was the year that AlexNet won the ImageNet competition, effectively kickstarting the machine learning and data-modelling wave we are now living through. It’s fair to say that this birthed some of the earliest generations of data-first companies. From this initial pool, I performed keyword filtering to reduce the number of relevant companies I would have to look through. In particular, I only considered companies whose websites included at least one of the following terms: AI, CV, NLP, natural language processing, computer vision, artificial intelligence, machine, ML, data. I also disregarded companies whose website links were broken.

      How data was collected

    6. There are 70% more open roles at companies in data engineering as compared to data science. As we train the next generation of data and machine learning practitioners, let’s place more emphasis on engineering skills.

      The resulting 70% is based on a real analysis

    7. When you think about it, a data scientist can be responsible for any subset of the following: machine learning modelling, visualization, data cleaning and processing (i.e. SQL wrangling), engineering, and production deployment.

      What tasks can Data Scientist be responsible for

    1. BERT engineer is now a full time job. Qualifications include:Some bash scriptingDeep knowledge of pip (starting a new environment is the suckier version of practicing scales)Waiting for new HuggingFace models to be releasedWatching Yannic Kilcher’s new Transformer paper the day it comes outRepeating what Yannic said at your team reading group

      Structure of a BERT engineer job

  3. Dec 2020
  4. Nov 2020
    1. There’s a story about an art teacher that split their class in half. They told one half of the students that they’d be graded based on a single piece of work, and the other half that they would be graded on the quantity of work produced. The half that was being graded on quantity ended up producing higher quality pieces. By iterating and learning from their mistakes they actually ended up producing better work than the students that only had to produce one piece. Quantity leads to quality. Share your work Sharing work helps you to think and develop. The feedback you get feeds into the next iteration.

      Share your work as often as you can as quantity leads to quality

  5. Oct 2020
    1. Junior school is great because you don’t learn to find a job. You’re at school to grow as a citizen, not to prepare to your future life, and actually you’re better not to think about your future if you don’t want to question yourself about the meaning of your existence. This is the same thing for side projects. See them as a way to discover a new topic and enlarge your horizon, not as something that you could action in your current position or to find a new job.

      Comparing school to side projects

    2. Even from a purely technical point of view, you will not really understand a library or a framework by just sticking to the tutorial or its basic features. You’ll have to dig into and to face its most painful aspects to deeply understand it.

      Way to deeply learn technologies

    3. Today, I recommend not hiding your side projects, but to not displaying them as a primary part of your identity, to not scare the recruiter and let him feel that you have a secondary plan.

      Why not to talk too much about your personal projects

    4. You can generally assume that a developer coming from a cutting-edge company has better chances to be a great developer than a developer coming from a Java 1.4 shop. He may not be smarter, but he has been hired by a company with a most demanding hiring process, and has been surrounded by some of the smartest developers.
    5. First, most recruiters don’t care about your personal projects or how many meetups you went during the year. What matters the most is your current company - and by that I mean the name of your current company.

      True in most cases

    1. Daydreaming at Work Can Fuel Creativity

      Summary of the article:

      • We spend nearly half of each day daydreaming, and usually think that it’s a bad thing, but it turns out that highly demanding tasks make us daydream more.
      • It allows us to turn off our surroundings, and can be a way of imagining solutions to the problem at hand.
      • To find this out, researchers did two studies of employees and managers in South America, including mainly surveys about daydreaming.
      • Daydreaming turned out to happen more when the tasks required a lot of focus - it can boost creative problem-solving as long as we’re personally invested in our work.
      • However, for people who don’t identify with their work, daydreaming was linked to worse performance.
    1. What the question does is that it creates a powerful anchoring effect. A candidate who gives this information away will typically ask for only a bit more than what she is currently getting. The human resources dude will then have a big internal smile: the candidate's expected salary is below the range that was decided for that position. He will then happily give the candidate 3.000 dollars more than what the candidate asks for.

      Why it's not worth answering "what's your current salary" question

    1. I’ve written for 15 years, 569 essays, and 2.9 million words and counting. You can read a quick intro or my best work, which I curate below.
  6. Sep 2020
    1. To be reliably able to focus on something, you need to be intuitively, emotionally invested in the outcome.

      Without emotions, you might not get the right focus level on the problem

    2. The output of knowledge workers is extremely skewed based on focus. The productivity tiers seem to be:<10% focused on the job at hand: meaningful risk of getting fired.10-50% focus: “meets expectations,” gets regular raises.50%+ focus: superstar, 10x engineer, destined for greatness.

      3 focus levels in a career

    1. What you actually need from an ML/Data Science person:- Experience with data cleaning (this is most of the gig)- A solid understanding of linear and logistic regression, along with cross-validation- Some reasonable coding skills (in both R and Python, with a side of SQL).

      Basic skills to seek for in Data Scientists

    2. deep learning is good in some scenarios and not in others, so anyone who's just a deep learning developer is not going to be useful to most companies.
    3. Having worked with researchy vs more product/business driven teams, I found that the best results came when a researchy person took the time to understand the product domain, but many of them believe they're too good for business (in which case you should head back to academia).

      Problem of PhD profiles in business

    4. but companies will discover that ML is (for the vast majority) a shiny object with no discernible ROI. Like Big Data, I think we'll see a few companies execute well and actually get some value, while most will just jump to the next shiny thing in a year or two.

      As long as ROI isn't clearly visible in ML, as long it might not bring more ML positions

    1. It turns out that during a meeting, he asked them how long it would take to remove staff cars from the lot and start digging the first hole for the Boring Company tunnel. The answer: two weeks. Musk asked why, and when he gathered the necessary information, he concluded, “Let’s get started today and see what’s the biggest hole we can dig between now and Sunday afternoon, running 24 hours a day.” Within three hours, the cars were gone and there was a hole in the ground.

      The way Elon Musks motivates his employees

  7. Aug 2020
    1. Online courses tend to be based around linear playlists of videos, along with associated readings and other activities. These often look like university courses filmed and translated more or less directly to online form. More internet native courses tend to be shorter and more focused, but still just as linear and video-centric.

      agree with this.

      I've often thought that at times learning feels more like the Path fo Exile skill spider-web than a linear path.

      Many 'road maps', 'how to' feels like a ladder - and then it's not always clear how much you need to learn about a certain step before moving onto the next step, while also failing to realize that you may have learned the outcomes from the step in another way.

  8. Jul 2020
    1. Your coworkers being an important part of your day-to-day experience is unsurprising, and what I’ve found increasingly true is that your current coworkers also have an outsized influence on your career long after you’ve stopped working together.

      Bangun jaringan teman kerja yang kuat, seandainya udah ga kerja ditempat tersebut, kesempatan kerja bisa datang dari mereka.

      Cari teman kerja yang bisa menjadi rival, ngepush kemampuan diri sendiri ke ambang batas.

    2. Consequently, the best roles are only accessible if you’re already financially stable, whether it’s stability from an existing role that’s you can interview from, or from savings and investments that allow you to pause between roles to rest and explore.

      Dengan keamanan keuangan, kamu bisa memberi jeda dan memilih mana yang sesuai

    3. Financial security is a prerequisite to own your pace and learning.

      Keamanan keuangan adalah sebuah keuntungan.

    4. Each year identify one or two new things–things that you’re uncomfortable with–and do them! You’ll continue growing yourself, adding more and more pieces to your toolkit.

      Ketika kamu merasa tidak nyaman, artinya kamu sedang belajar

    1. For this study, researchers conducted technical interviews of 48 computer science undergraduates and graduate students. Half of the study participants were given a conventional technical interview, with an interviewer looking on. The other half of the participants were asked to solve their problem on a whiteboard in a private room. The private interviews did not require study participants to explain their solutions aloud, and had no interviewers looking over their shoulders. Researchers measured each study participant’s interview performance by assessing the accuracy and efficiency of each solution. In other words, they wanted to know whether the code they wrote would work, and the amount of computing resources needed to run it. “People who took the traditional interview performed half as well as people that were able to interview in private,” Parnin says. “In short, the findings suggest that companies are missing out on really good programmers because those programmers aren’t good at writing on a whiteboard and explaining their work out loud while coding.”

      Interesting experiment focused on recruitment. "Candidates" who are able to solve the challenge alone in quiet rooms perform better

    1. Although the impact will not be distributed evenly, digital transformation will touch virtually every corner of the global workforce — from food production (324,000 new jobs) to healthcare (2 million) and the automotive industry (6 million).

      The main industries affected:

      • automotive (6 million)
      • healthcare (2 million)
      • food production (324k)

      check the PowerBI visualisation below for more info

    2. Over the next five years, we estimate that the global workforce can absorb around 149 million new technology-oriented jobs. Software development accounts for the largest single share of this forecast, but roles in related fields like data analysis, cyber security, and privacy protection are also poised to grow substantially.

      It is estimated that 2025 will require 4.6 times more IT profiles than 2020.

      Data source: Microsoft Data Science utilising LinkedIn data

  9. Jun 2020
  10. May 2020
    1. If you, on the other hand, want to go the student-like route (living in Wohngemeinschaft, not eating out too much) and try to save, you can easily live on 1,500-2,000 CHF per month and save the majority of your salary.

      If you leave cheaply, you can spend around 1500 - 2000 CHF a month and save majority of your salary

    2. We are now cooperating with Credit Agricole Bank and Revolut - if you have already moved to Switzerland you can open a free bank account and get 100 CHF bonus - email us to get the bonus code.

      100 CHF bonus for opening a bank account in Switzerland

    3. 120,000 CHF annually according to this calculator gets you 7,746.20 CHF net per month.

      120 000 CHF gets you around 7 746 CHF net per month

    4. 2) Rent only a room - it might be a good option if you come without family (in Switzerland it’s called living in a Wohngemeinschaft).

      Renting a room in Switzerland = Living in a Wohngemeinschaft :o

    5. Choose health insurance (Krankenkasse) - in Switzerland you have to pay your health insurance separately (it’s not deducted from your salary). You can use the Comparis website to compare the options. You have 3 months to choose both the company and your franchise.

      Choosing health insurance in Switzerland

    6. Other important things - if you plan to use public transport, we recommend you to buy the Half Fare card. It gives you a 50% discount on most public transport in Switzerland (it costs 185 CHF per year).

      Recommendation to buy a Half Fare Card for a public transport discount

    7. There are also some general expat groups like Zurich Together

      Zurich Together <--- expat group for Zurich

    1. If you delegate all your IT security to the InfoSec, they will come up with draconian rules

      Try to do some of your own security before delegating everything to InfoSec that will come with draconian restrictions

    2. you should always advocate for having a dedicated SRE if there’s any real risk of after-hours pages that are out of your control.

      Site Reliability Engineers (ideally from different time zones) should've been settled when we might expect after-hours errors

    3. Consuming media (books, blogs, whatever) is not inherently a compounding thing. Only if you have some kind of method to reflect, to digest, to incorporate your knowledge into your thoughts. If there is anything valuable in this post, you, reader, will probably not benefit from it unless you do something active to “process” it immediately.

      Consuming books/blogs is not as compounding as we think

    1. if you have an amazing manager at a shit company you’ll still have a shit time. In some ways, it’ll actually be worse. If they’re good at their job (including retaining you), they’ll keep you at a bad company for too long. And then they’ll leave, because they’re smart and competent. Maybe they’ll take you with them.

      Danger of working with a great manager at a shit company

    2. Some of the people in the company are your friends in the current context. It’s like your dorm in college.

      "Company is like a college dorm"... interesting comparison

    3. It’s also okay to take risks. Staying at a company that’s slowly dying has its costs too. Stick around too long and you’ll lose your belief that you can build, that change is possible. Try not to learn the wrong habits.

      Cons of staying too long in the same company

    1. I do think when a lot of managers realized they’ve hit their peak or comfort level, they then start to focus on playing politics instead of delivering results to hold onto their position. These are also the kind of managers who would only hire people less capable than them, for fear of being replaced.

      The way corporate world works

    2. “In practice people gravitate to, hire and promote individuals they like to be around, not people who demand accountability.”

      Everybody likes having an agreeable and flattering person around them

    3. Dr. Peter advises creative incompetence — pretending to be incompetent but doing it in an area or manner where it doesn’t actually impair your work.

      Creative incompetence

    4. Dr. Peter also surmised that “super competent” people tend to “disrupt the hierarchy.” I suppose that’s a nice way of saying you’ve made your boss look bad by being more capable.In such situations, you’ll probably find yourself deliberately suppressed or edged out sooner or later — for some stupid reason or blame pushing.

      Being overly competent may get you fired

    5. So if you’re a highly competent and aggressive individual, it’s best you find yourself a job in a startup, be an entrepreneur, or work in a company that needs turning around.

      Advice to competitive workers

    6. Dr. Peter also had another interesting theory about getting promoted. He considered working hard and improving your skill sets not as effective as something called pull promotion. That’s when you get promoted — faster than usual — when a mentor or patron pulls you up.No wonder there’s so much butt kissing in the corporate world. They must have read Dr. Peter’s research from the ‘60s.

      Pull promotion

    7. competency doesn’t factor as much as likability in most corporate promotions, especially when the ship is smooth sailing.

      Another truth of the corporate world

    8. Find a results-oriented job if you’re fiercely independent and opinionated. Climb the ladder in a big corporation if you’re highly diplomatic or a crowd-pleaser.

      Advice for two different working profiles

    1. managers fail to see and address this problem is that they are used to looking at communication and assume it's a good thing. Because they see activity

      Managers in general perceive meetings as a good thing

    2. A study conducted by Gloria Marks, a Professor of Informatics at the University of California, revealed that it takes us an average of 23 minutes and 15 seconds to refocus on a task after an interruption, and even when we do, we experience a decrease in productivity

      23 minutes and 15 seconds - average time to refocus on task after an interruption

    3. It doesn't mean that we ignore all messages and only look up from our work when something is on fire – but the general expectation is that it's okay to not be immediately available to your teammates when you are focusing on your work

      One of the rules of "Office time"

    4. Working in an open office renders us even more vulnerable

      Like single standup meeting, open office doesn't improve the productivity of makers

    5. Office hours are chunks of time that makers set aside for meetings, while the rest of the time they are free to go into a Do Not Disturb mode

      "Office hours" - technique to improve makers schedule

    6. People think it’s efficient to distribute information all at the same time to a bunch of people around a room. But it’s actually a lot less efficient than distributing it asynchronously by writing it up and sending it out and letting people absorb it when they’re ready to so it doesn’t break their days into smaller bits.”

      Async > meetings

    7. it's a matter of culture. None of these rules would work if the management fails to see that makers need to follow a different schedule

      Change in the work environment needs acknowledgement of managers

    8. context switching between communication and creative work only kills the quality of both

      Context switching lowers the quality

    9. since most powerful people operate on the manager schedule, they're in a position to force everyone to adapt to their schedule

      Managers highly affect makers schedule

    10. The most straightforward way to address this is to build a team knowledge base. Not only does that minimize the number of repetitive questions bounced around the office, it allows new team members to basically onboard themselves.

      Building a team knowledge base

    11. almost no organizations today support maker schedules

      Unfortunate truth

    12. For managers, interruptions in the form of meetings, phone calls, and Slack notifications are normal. For someone on the maker schedule, however, even the slightest distraction can have a disruptive effect

      How ideal schedule should look like:

    13. Immediate response becomes the implicit expectation, with barely any barriers or restrictions in place

      Why Slack is a great distraction:

      in the absence of barriers convenience always wins

    14. In our experience, the best way to prevent a useless meeting is to write up our goals and thoughts first. Despite working in the same office, our team at Nuclino has converted nearly all of our meetings into asynchronously written reports.

      Weekly status report (example):

    1. For many data scientists, the finished product of a work session is a business analysis. They need to show team members—who oftentimes aren’t technical—how their data became a specific recommendation or insight.

      Usual final product in Data Science is the business analysis which is perfectly explained with notebooks

    1. Work never ends. No matter how much you get done there will always be more. I see a lot of colleagues burn out because they think their extra effort will be noticed. Most managers appriciate it but do not promote their employees.

      Common reality of overworking

    1. Don't focus too much on the salary. It's just one tiny part of the whole package.Your dev job pays your rent, food and savings. I assume that most dev jobs do this quite well.Beyond this, the main goal of a job is to increase your future market value, your professional network and to have fun. So. basically it's about how much you are worth in your next job and that you enjoy your time.A high salary doesn't help you if you do stuff which doesn't matter in a few years.

      Don't focus on the salary in your dev job.

    1. COVID-19 has spurred a shift to analyze things like supply chain disruptions, speech analytics, and filtering out pandemic-related behavior, such as binge shopping, Burtch Works says. Data teams are being asked to create new simulations for the coming recession, to create scorecards to track pandemic-related behavior, and add COVID-19 control variables to marketing attribution models, the company says.

      How COVID-19 impacts activities of data positions

    2. Data scientists and data engineers have built-in job security relative to other positions as businesses transition their operations to rely more heavily on data, data science, and AI. That’s a long-term trend that is not likely to change due to COVID-19, although momentum had started to slow in 2019 as venture capital investments ebbed.
    3. According to a Dice Tech Jobs report released in February, demand for data engineers was up 50% and demand for data scientists was up 32% in 2019 compared to the prior year.

      Need for Data Scientist / Engineers in 2019 vs 2018

    1. 70% async using Twist, Github, Paper25% sync using something like Zoom, Appear.in, or Google Meet5% physical meetings, e.g., annual company or team retreats

      Currently applied work structure at Doist

    2. According to the Harvard Business Review article “Collaborative Overload”, the time employees spend on collaboration has increased by 50% over the past two decades. Researchers found it was not uncommon for workers to spend a full 80% of their workdays communicating with colleagues in the form of email (on which workers’ spend an average of six hours a day); meetings (which fill up 15 percent of a company’s time, on average); and more recently instant messaging apps (the average Slack user sends an average of 200 messages a day, though 1,000-message power users are “not the exception”)

      Time spent in the office

    3. we think the async culture is one of the core reasons why most of the people we’ve hired at Doist the past 5 years have stayed with us. Our employee retention is 90%+ — much higher than the overall tech industry. For example, even a company like Google — with its legendary campuses full of perks from free meals to free haircuts — has a median tenure of just 1.1 years. Freedom to work from anywhere at any time beats fun vanity perks any day, and it costs our company $0 to provide

      Employee retention rate at Doist vs Google

    1. I also recently took about 10 months off of work, specifically to focus on learning. It was incredible, and I don’t regret it financially. I would often get up at 6 in the morning or even earlier (which I never do) just from excitement about what I was going to learn about and accomplish in the day. Spending my time focused Only on what I was most interested in was incredibly rewarding.

      Approach of taking 10 months off from work just to learn something new

    1. I'm working for myself right now, but if one day I needed to go get a full-time job again, I would almost certainly not go to big tech again. I'd rather get paid a fifth of what I was doing, but do something that leaves me with some energy after I put in a day's work

      Reflections after working for FAANG

    2. more money comes at the cost of very high expectations and brutal deadlines
    3. Second, in my experience working with ex-FAANG - these engineers, while they all tend to be very smart, tend to be borderline junior engineers in the real world. They simply don't know how to build or operate something without the luxury of the mature tooling that exists at FAANG. You may be in for a reality shock when you leave the FAANG bubble

      Working with engineers out of FAANG can be surprising

    1. Truth be told, we found that most companies we worked with preferred to own the analytical backend.

      From the experience of Plotly Team

    1. Talented people flock to employers that promise to invest in their development whether they will stay at the company or not.

      Cannot agree more on that

    2. We want to learn, but we worry that we might not like what we learn. Or that learning will cost us too much. Or that we will have to give up cherished ideas.

      I believe it is normal to worry about the usage of a new domain-based knowledge

    1. The two things I really like about working for smaller places or starting a company is you get very direct access to users and customers and their problems, which means you can actually have empathy for what's actually going on with them, and then you can directly solve it. That cycle is so powerful, the sooner you learn how to make that cycle happen in your career, the better off you'll be. If you can make software and make software for other people, the outcome truly is hundreds of millions of dollars worth of value if you get it right. That's where I'm here to try and encourage you to do. I'm not really saying that you shouldn't go work at a big tech company. I am saying you should probably leave before it makes you soft. 

      What are the benefits of working at the smaller companies/startups over the tech giants

    1. afternoons are spent reading/researching/online classes.This has really helped me avoid burn out. I go into the weekend less exhausted and more motivated to return on Monday and implement new stuff. It has also helped generate some inspiration for weekend/personal projects.

      Learning at work as solution to burn out and inspiration for personal projects

    1. Praca w Facebooku - doskonała znajomość JSa, React, zarządzanie projektem OSS na GitHubie, prowadzenie społeczności, pisanie dokumentacji i wpisów na blogu.Szkolenia - dobra znajomość JSa, React, tworzenie szkoleń (struktura, zadania, itd), uczenie i swobodne przekazywanie wiedzy, marketing, sprzedaż.Startupy - dobra znajomość JSa, React, praca w zespole, rozmawianie z klientami, analiza biznesowa, szybkie dowożenie MVP, praca w stresie i dziwnych strefach czasowych.

      Examples of restructuring tasks into more precise actions:

      • Working at Facebook - great JS, React, managing OS project on GitHub, managing a social group, writing documentation and blog
      • Workshops - good JS, React, delivering workshops (structure, tasks), learning and teaching, marketing, sale
      • Startups - good JS, React, work in a team, talking to clients, business analytics, quick MVP delivery, work under stress and in strange timezones
  11. Jan 2020
    1. Majority of the times, the only way to break into a circle is for someone within that circle to speak positively on your behalf.

      Who speaks on your behalf?!

    2. I have observed something else under the sun. The fastest runner doesn’t always win the race, and the strongest warrior doesn’t always win the battle. The wise sometimes go hungry, and the skillful are not necessarily wealthy. And those who are educated don’t always lead successful lives. It is all decided by chance, by being in the right place at the right time. — Ecclesiastes 9:11
    3. They simply possess the willpower and drive to observe people, get to know people, appear in gatherings that involve people that are aligned with their goals, and connect people with one another.

      Skill that puts sometimes the smartest minds below you

    1. ericb 12 days ago | unvote [-] * Better googling. Time-restricted, url restricted, site restricted searches. Search with the variant parts of error messages removed.* Read the source of upstream dependencies. Fix or fork them if needed.* They're better at finding forks with solutions and gleaning hints from semi-related issues.* Formulate more creative hypothesis when obvious lines of investigation run out. The best don't give up.* Dig in to problems with more angles of investigation.* Have more tools in their toolbelt for debugging like adding logging, monkey-patching, swapping parts out, crippling areas to rule things out, binary search of affected code areas.* Consider the business.* Consider user-behavior.* Assume hostile users (security-wise).* Understand that the UI is not a security layer. Anything you can do with PostMan your backend should handle.* Whitelist style-security over blacklist style.* See eventual problems implied by various solutions.* "The Math."

      What do top engineers do that others don't?

      • Better googling. Time-restricted, url restricted, site restricted searches. Search with the variant parts of error messages removed.
      • Read the source of upstream dependencies. Fix or fork them if needed.
      • They're better at finding forks with solutions and gleaning hints from semi-related issues.
      • Formulate more creative hypothesis when obvious lines of investigation run out. The best don't give up.
      • Dig in to problems with more angles of investigation.
      • Have more tools in their toolbelt for debugging like adding logging, monkey-patching, swapping parts out, crippling areas to rule things out, binary search of affected code areas.
      • Consider the business.
      • Consider user-behavior.
      • Assume hostile users (security-wise).
      • Understand that the UI is not a security layer. Anything you can do with PostMan your backend should handle.
      • Whitelist style-security over blacklist style.
      • See eventual problems implied by various solutions.
      • "The Math."
  12. Nov 2019
  13. Oct 2019
  14. Sep 2019
    1. Pretty much the same things as the engineering blog, but make sure to skim through the “Issues” section to see if you can find anything else interesting.

      Things to look for in open source projects

    2. What projects/products have they developed recently? And more importantly, what led them to build these things? What business challenges or goals drove the project? What technical challenges drove it?

      Things to look for in the developer's blogs

    3. The list of product(s). Is there anything similar you’ve worked on that you can show you understand the business problems and domain? Anything similar you’ve worked on where you helped make UX and/or feature decisions (where you stepped outside your developer-world bubble?). Anything similar that you had to develop a unique technical solution for? You want to show you can understand the business/product side of things and translate that into technical solutions. List of customers (company’s love to list customer logos!). While on the surface this might not seem that helpful, it can actually provide helpful information. Is there a particular type of customer they have that you have developed solutions for before? (i.e. – government, insurance, etc). Any specific customer you have built products for before? News section. Companies will often talk about new customers, recent acquisitions, and new product developments here. This will give you a sense of where the company is headed and is really useful to bring up in interviews as it shows you have an understanding of the current state of the company.

      Things to look for on company websites

    4. Things to look for are: What are recent things they’ve worked on or tools they’ve built? What are things they’re working on now? Projects/products/etc What projects/products do they mention that you would be working on? Do they mention any specific technologies you have experience with (not Node/React etc, but for example, performance testing tools -> this suggest they have a lot of traffic and they need to profile their services, something that you would be a good fit for if you have this experience) Anything they explicitly mention they need help with? Sometimes job posting will say things like “We just had a huge increase in users and need to hire another developer to help us re-architect some of our core services”.

      Things to look for in job postings

    5. At a very high level, it is:

      Better approach to look for jobs:

      Step 1: figure out what companies’ problems are: – Research company website, engineering blog, etc. to find out what these problems are

      Step 2, show how you can help solve those problems: – create your “pitch” (whether this is a resume and quick paragraph email, or something in person, approach is the same) by showing how your skills and experience will help solve their problems

    6. The job search process is a sales process – one in which you are selling your skills and experience
  15. Aug 2019
    1. Passion, character, and initiative are a requirement. A long resumé is not — as long as you care about the right things, we can help build your skillset. This is true for those we hire, and it is equally true for our apprentices.
    1. “There comes a time when you ought to start doing what you want. Take a job that you love. You will jump out of bed in the morning. I think you are out of your mind if you keep taking jobs that you don’t like because you think it will look good on your resume. Isn’t that a little like saving up sex for your old age?” — Warren Buffett
  16. Apr 2019
    1. Important skillset that can be used for direct work in a wide range of causesWeb design is a skill that’s in-demand in many types of organisations, from charities to startups, giving you great flexibility and the opportunity to work on high impact projects.Organisations that are especially high-impact to work at or volunteer for include:Government departments, such as Obama’s US Digital Service and 18F or the UK’s Government Digital Service.Effective non-profits, such as those recommended by GiveWell, Giving What We Can and The Life you Can Save.Innovative for-profits, such as Google, which now has seven products with over one billion monthly active users (Search, Gmail, Android, Chrome, Google Play, Maps and Youtube)1, or AirBnB.For-profits focused on the global poor, such as Sendwave.Effective Altruist organisations.
    1. Part-time advocacy journalismDue to the rise of online publications it is becoming easier to get published, which opens up the opportunity to pursue advocacy journalism part-time, as a freelancer alongside another job that pays the bills. We know of several people who are successfully pursuing this option.
    1. Documentary film-making seems like a form of art with a good chance of direct and advocacy impact, in that it resembles investigative journalism. It also appears stronger in terms of network and transferability of skills. As a result, we would expect a career profile on documentary film-making to be more positive than this one.
    1. Sean Cavanagh, Associate Editor for Education Week, writes about the use of technology to benefit the career development of students. This article focuses on the K-12 sector, but this implementation at this level is important because it will influence these students when they pursue their career choices, often in Higher Education. This article outlines specific technologies and partnerships that schools are utilizing and shows the investment that students show when given these career opportunities to guide themselves toward.

      Rating: 8/10

    1. Author Melissa A. Venable, Ph.D. has spent her career working in career development, technology and instructional design. The article outlines technology options for career professionals to use with distance learners and how to conduct an assessment to ensure needs are being met.

      Rating: 5/10

    1. This article is authored by Farouk Dey, formerly of Stanford University and currently the Vice Provost for Integrative Learning and Life Design at Johns Hopkins. Dey offers an overview of the transformation that college career services have gone through over the past 100 years and showcases 10 areas where career services will continue to change in the future, including the scope of how technology will allow for a wider reach.

      Rating: 8/10

  17. Jan 2019
    1. Finally, after 11 years of lukewarm comfort and mediocre job security, I decided to take a chance in trying out in art, which I had always loved. From one point of view, I’ve succeeded, because I am making a living doing this. But even if I didn’t, the bottom line is that at least I have tried. If we try really hard and things don’t work out the way we want them to, we can move on.  I moved with two suitcases to New York from Tokyo and started over with my life. I enrolled myself as a freshman in my 30s, among my 17 and 18-year-old classmates, at School of Visual Arts, started studying art for the first time. Four years later, I received an MFA in Illustration, then started slowly working as a freelance illustrator
  18. Dec 2018
    1. SIGGRAPH: Share your top three technology tools. CC: I hate technology! But if you’re trying to make something pretty in this medium, there’s no avoiding it
    2. SIGGRAPH: What is the best advice you would give someone starting out in animation? CC: Draw. Carry a sketchbook (or a tablet) and draw (or paint!) every chance you get. Make observations from the world around you, from photo or video reference, from artists you admire. Most importantly, don’t just observe, but put those observations down on paper in visual form. Make a habit of it. The things you learn that way will stay with you forever. And that knowledge will be useful no matter what medium you end up working in.
    1. A: Anything else you’d like to say or tell the new comers and/or the community? L: Mmh, I know how it feels to be limited by your own lack of skills and today’s tools are taking away a little bit of that barrier. And the more the software helps you to get rid of the technical problems of representation, the more creative you can be. While the tool is the same, it’s very fun to see that everybody has its own take to how to use Quill. It wasn’t at first, but now I see more and more people having their own style. It’s so refreshing. I follow the group and what is going on with a lot of attention.
    2. A: Hello Lip, please tell us a bit more about you. What is your background? Did you study visual arts?   L: Not really [laughs]. My parents forced me to have a very classical education. I studied Latin and ancient Greek in high school. But when I was 18, I realized that I enjoy to visualize my ideas and thoughts. So I went to the University and studied advertising. I was heading toward more of a copywriting agency type of occupation until I felt the need to carry my ideas until completion. I was tired of giving them away too soon because I found my stories never really turned out the way they should be. Since the softwares got easier and more accessible, I managed to find the right moment to jump in and learn the technical skills to do it on my own.