+1 -1

Artificial Intelligence Models.md

reviewed

··· 78 78 79 79 ### Tools 80 80 81 81 - - [Curated GitHub Starts list](https://github.com/stars/davidgasquez/lists/robot-llms) 81 81 + - [Curated GitHub Starts list](https://web.archive.org/web/20260226130834/https://github.com/stars/davidgasquez/lists/robot-llms) 82 82 83 83 ### FrontEnds 84 84

+2 -2

Blogging.md

reviewed

··· 1 1 # Blogging 2 2 3 3 - Expect 80% of the [[ideas]] in a post to happen after you start [[Writing]] it, and 50% of those you start with to be wrong. 4 4 - - To decide if your idea is worth [[Writing]] about, [ask these questions](https://jvns.ca/blog/2016/05/22/how-do-you-write-blog-posts/): 4 4 + - To decide if your idea is worth [[Writing]] about, [ask these questions](https://web.archive.org/web/20260205031856/https://jvns.ca/blog/2016/05/22/how-do-you-write-blog-posts/): 5 5 - Would this have helped me a year ago? 6 6 - Would this have helped me last week? 7 7 - Do you think this would be interesting to at least like 2 other people? ··· 14 14 - Put a summary at the top if you're writing a long post. 15 15 - The more you create, the more ideas come to you to continue creating. That's the creativity [[Feedback Loops|feedback loop]]. 16 16 - [Expand your definition of completing a project (any project, no matter how small) to include writing a blog post that explains that project](https://twitter.com/simonw/status/1578018383127187461). 17 17 - - For long-form content, the [diamond model](http://web.archive.org/web/20250130021041/https://dropbox.design/article/mental-models-for-designers) works great for putting a structure around your main idea: 17 17 + - For long-form content, the [diamond model](https://web.archive.org/web/20250130021041/https://dropbox.design/article/mental-models-for-designers) works great for putting a structure around your main idea: 18 18 1. Attention: Start with a story, statistic, or something similar 19 19 2. Main topic: Briefly introduce the main topic you'll cover 20 20 3. Previews: Give quick previews of your subtopics

+1 -1

Data Practices.md

reviewed

··· 22 22 - How can we measure our progress/success for each step? 23 23 - What happens if we don't hit the target? 24 24 - What is the real problem you're trying to solve? 25 25 - - Frame the (initially vague) data questions this way: [How does _lever_ impact _KPI_?](https://www.narrator.ai/blog/how-i-frame-data-questions-to-make-analyses-more-useful/) 25 25 + - Frame the (initially vague) data questions this way: [How does _lever_ impact _KPI_?](https://web.archive.org/web/20220810142837/https://www.narrator.ai/blog/how-i-frame-data-questions-to-make-analyses-more-useful/) 26 26 - What is the business question you're trying to answer? 27 27 - What decision will you make or action will you take with this data? 28 28 - [What are we trying to improve](https://twitter.com/ergestx/status/1758538405695086829)?

+1 -1

Data Quality.md

reviewed

··· 4 4 - Log data quality issues so you can act on them. 5 5 - [We live in a messy world and as a result the data we collect and represent it are always going to be messy](https://twitter.com/KostasPardalis/status/1641122521775849497). 6 6 - Data quality [is a measurement of the value of data to the business, meaning it is dependent on the task trying to be accomplished](https://tayloramurphy.substack.com/p/data-quality). High quality data in one context can be low in another. 7 7 - - [Data issues are fractal](https://www.speedwins.tech/posts/some-words-with-nuria-ruiz#question-7). 7 7 + - [Data issues are fractal](https://web.archive.org/web/20241212162417/https://www.speedwins.tech/posts/some-words-with-nuria-ruiz). 8 8 - [There are many common data quality problems already figured out](https://b-greve.gitbook.io/beginners-guide-to-clean-data/). 9 9 - Incremental data quality improvements can lead to measurable value back to the business. That's what you should focus on and this is what's going to help you with convincing people to care about data quality. 10 10 - Data quality is a team sport. Data is not the concern of just the DEs, ML Engs, Analysts etc. Data quality starts from the front-end. Did you check the JSON you sent on Rudderstack before merging that instrumentation PR?

+8 -8

Decentralized Web.md

reviewed

··· 17 17 - [Kernel Community](https://kernel.community/). 18 18 - Decentralized friendly and open source alternatives: 19 19 - [Trello](https://dework.xyz/) 20 20 - - [Notion](http://web.archive.org/web/20241220080916/https://www.clarity.so/) 20 20 + - [Notion](https://web.archive.org/web/20241220080916/https://www.clarity.so/) 21 21 - [Medium](https://mirror.xyz/dashboard) 22 22 - [Imgur](https://www.pinata.cloud/) 23 23 - - [Netlify](https://fleek.co/) 23 23 + - [Netlify](https://web.archive.org/web/20250105132652/https://fleek.co/) 24 24 - [Firebase](https://textile.io) 25 25 - [Dropbox](https://www.sliksafe.com/). [Another](https://files.chainsafe.io/) 26 26 - [Publishing](https://docs.distributed.press/) ··· 29 29 ## Links 30 30 31 31 - [Kernel](https://kernel.community/). An 8 week program covering crypto and web3. 32 32 - - [Crypto Canon](https://a16z.com/2018/02/10/crypto-readings-resources/) - Great list of crypto readings and resources. 33 33 - - [Understanding Crypto](https://a16z.com/2020/04/30/explaining-crypto-from-a16z/)- Learn more about cryptocurrencies. 32 32 + - [Crypto Canon](https://web.archive.org/web/20230219013152/https://a16z.com/2018/02/10/crypto-readings-resources/) - Great list of crypto readings and resources. 33 33 + - [Understanding Crypto](https://web.archive.org/web/20230207021732/https://a16z.com/2020/04/30/explaining-crypto-from-a16z/)- Learn more about cryptocurrencies. 34 34 - [DAOs, A Canon](https://future.a16z.com/dao-canon/). Understand, build, and get involved with “decentralized autonomous organizations”. 35 35 - [Trading View](https://www.tradingview.com/markets/cryptocurrencies/) - Crypto charts. 36 36 - [Finematics](https://www.youtube.com/channel/UCh1ob28ceGdqohUnR7vBACA). Educational videos on DeFi (Decentralized Finance). ··· 45 45 46 46 ### Blockchain Indexing Projects 47 47 48 48 - There is an emerging landscape of [Data and Blockchain](https://www.primodata.org/blockchain-data). 48 48 + There is an emerging landscape of [Data and Blockchain](https://web.archive.org/web/20241013061702/https://www.primodata.org/blockchain-data). 49 49 50 50 #### Companies 51 51 52 52 - [Tokenflow](https://tokenflow.live/) 53 53 - [Indexed.xyz](https://github.com/indexed-xyz) 54 54 - [BitQuery](https://bitquery.io/) ([GitHub](https://github.com/bitquery/explorer)) 55 55 - - [Coherent](http://web.archive.org/web/20250312045544/https://coherent.xyz/) 55 55 + - [Coherent](https://web.archive.org/web/20250312045544/https://coherent.xyz/) 56 56 - [Covalent](https://www.covalenthq.com/) ([GitHub](https://github.com/covalenthq)) 57 57 - [Nansen](https://www.nansen.ai/) 58 58 - [Footprint](https://www.footprint.network/) ([GitHub](https://github.com/footprintanalytics)) 59 59 - - [Blockchair](http://web.archive.org/web/20240228210324/https://blockchair.com/dumps) 59 59 + - [Blockchair](https://web.archive.org/web/20240228210324/https://blockchair.com/dumps) 60 60 - [Sentio](https://www.sentio.xyz/) ([GitHub](https://github.com/sentioxyz)) 61 61 - [GeniiData](https://geniidata.com/) 62 62 - - [Transpose](https://www.transpose.io/) ([GitHub](https://github.com/TransposeData)) 62 62 + - [Transpose](https://web.archive.org/web/20250422042357/https://www.transpose.io/) ([GitHub](https://github.com/TransposeData)) 63 63 - [Allium](https://twitter.com/alliumlabs) 64 64 - [Kyve](https://www.kyve.network/) 65 65 - [Token Terminal](https://tokenterminal.com/)

+2 -2

Design Docs.md

reviewed

··· 45 45 46 46 - [Google Design Doc Template](https://docs.google.com/document/d/18hYAQCTsDgaFUo-VJGhT0UqyetL2LbAzkWNK1fYS8R0/edit#) 47 47 - [Rust RFCs](https://github.com/rust-lang/rfcs) 48 48 - - [Awesome Tech Specs](https://eng.lyft.com/awesome-tech-specs-86eea8e45bb9) 49 49 - - [On Writing Tech Specs](https://codeburst.io/on-writing-tech-specs-6404c9791159) 48 48 + - [Awesome Tech Specs](https://web.archive.org/web/20171029062931/https://eng.lyft.com/awesome-tech-specs-86eea8e45bb9) 49 49 + - [On Writing Tech Specs](https://web.archive.org/web/20221213144524/https://codeburst.io/on-writing-tech-specs-6404c9791159) 50 50 - [Rust RFCs Template](https://github.com/rust-lang/rfcs/blob/master/0000-template.md) 51 51 - [Scaling Engineering Teams via RFCs: Writing Things Down](https://blog.pragmaticengineer.com/scaling-engineering-teams-via-writing-things-down-rfcs)

+2 -2

Documentation.md

reviewed

··· 41 41 - [Microsoft Documentation Style Guide](https://docs.microsoft.com/en-us/style-guide/welcome/) 42 42 - [Google Documentation Style Guide](https://developers.google.com/style) 43 43 - [Mailchimp Content Style Guide](https://styleguide.mailchimp.com/voice-and-tone/) 44 44 - - [18F Content Guide](http://web.archive.org/web/20230327160033/https://content-guide.18f.gov/our-style/voice-and-tone/) 44 44 + - [18F Content Guide](https://web.archive.org/web/20230327160033/https://content-guide.18f.gov/our-style/voice-and-tone/) 45 45 46 46 ## READMEs 47 47 48 48 - - [Building a README](https://readme.so/). 48 48 + - [Building a README](https://web.archive.org/web/20251221211249/https://readme.so/). 49 49 - [How to Write a Great README](https://www.appsmith.com/blog/write-a-great-readme). 50 50 - [Template](https://www.makeareadme.com/). 51 51 - [Readme Driven Development](https://tom.preston-werner.com/2010/08/23/readme-driven-development).

+1 -1

Dogs.md

reviewed

··· 77 77 78 78 ### Stuffed Kongs 79 79 80 80 - [Stuffed Kongs](https://youtu.be/LwZI1isnvPQ) are meant to give your puppy or dog a chance to work out his brain and tongue while he gets a delicious treat or meal and you get some well-deserved downtime to relax. [Some stuffings](https://www.naturzoo.com/estimulacion-mental-alimentos-naturales/): 80 80 + [Stuffed Kongs](https://youtu.be/LwZI1isnvPQ) are meant to give your puppy or dog a chance to work out his brain and tongue while he gets a delicious treat or meal and you get some well-deserved downtime to relax. [Some stuffings](https://web.archive.org/web/20230929103825/https://www.naturzoo.com/estimulacion-mental-alimentos-naturales/): 81 81 82 82 - Puppy kibble or wet food. 83 83 - Proteins: Beef (non-fatty cut), chicken, turkey, salmon - all should be unseasoned and cooked.

+1 -1

Learning.md

reviewed

··· 70 70 71 71 [Follow this method](https://www.lesswrong.com/posts/ZGzDNfNCXzfx6hYAH/how-to-learn-soft-skills): 72 72 73 73 - - Pick a soft skill, X, that you'd like to get better at. Then, set a 5-minute timer. Spend those 5 minutes [explaining](https://jvns.ca/blog/confusing-explanations) to yourself, in [[Writing]], how to do X. Brainstorm on what the key tricky bits are, or strategies for navigating them. 73 73 + - Pick a soft skill, X, that you'd like to get better at. Then, set a 5-minute timer. Spend those 5 minutes [explaining](https://web.archive.org/web/20260213163031/https://jvns.ca/blog/confusing-explanations/) to yourself, in [[Writing]], how to do X. Brainstorm on what the key tricky bits are, or strategies for navigating them. 74 74 - Explore how is skill X really actually just the same as skill Y. In the sense that anyone who is fluent in skill Y already knows all they need to know to be good at X — they just need to apply their Y-skill to X. Your goal, as you do this, is to create a very short guide that enables anyone who already knows Y to hit the ground running with X. 75 75 76 76 ## Teaching

+2 -2

Machine Learning.md

reviewed

··· 57 57 58 58 - [Applied ML in Production](https://madewithml.com/#course) 59 59 - [Applied ML](https://github.com/eugeneyan/applied-ml) 60 60 - - Microsoft [ML Model Production Checklist](https://microsoft.github.io/code-with-engineering-playbook/machine-learning/ml-model-checklist/) and [Fundamental Checklist](http://web.archive.org/web/20240903115158/https://microsoft.github.io/code-with-engineering-playbook/machine-learning/ml-fundamentals-checklist) 60 60 + - Microsoft [ML Model Production Checklist](https://web.archive.org/web/20250808173855/https://microsoft.github.io/code-with-engineering-playbook/machine-learning/ml-model-checklist/) and [Fundamental Checklist](https://web.archive.org/web/20240903115158/https://microsoft.github.io/code-with-engineering-playbook/machine-learning/ml-fundamentals-checklist) 61 61 - [Engineering best practices for Machine Learning](https://se-ml.github.io/practices/) 62 62 - [Full Stack Deep Learning](https://course.fullstackdeeplearning.com/) 63 63 - [Awesome Production Machine Learning](https://github.com/EthicalML/awesome-production-machine-learning) ··· 82 82 - [The Open-Source Data Science Masters](https://github.com/datasciencemasters/go) 83 83 - [The Data Visualization Catalogue](https://datavizcatalogue.com/) and [Project](https://datavizproject.com/). 84 84 - [Visualization Curriculum](https://jjallaire.github.io/visualization-curriculum/) 85 85 - - [Chart Dos and Don'ts](http://web.archive.org/web/20211026152255/https://www.eea.europa.eu/data-and-maps/dashboards/industry-energy-ghg/) 85 85 + - [Chart Dos and Don'ts](https://web.archive.org/web/20211026152255/https://www.eea.europa.eu/data-and-maps/dashboards/industry-energy-ghg/) 86 86 - [Machine Learning Tutorials](https://ujjwalkarn.github.io/Machine-Learning-Tutorials/) 87 87 - [Data looks better naked](https://www.darkhorseanalytics.com/blog/data-looks-better-naked) 88 88 - [Guides for Visualizing Reality](https://flowingdata.com/2020/06/01/guides-for-visualizing-reality/)

+3 -3

Open Data.md

reviewed

··· 24 24 25 25 In the blockchain example, data is Open, Verifiable, and Useful. And yet, the main provider of data is Dune, a company that captured most of the data layer. Users can run `cryo` but there are no incentives for them to share the data. There isn't a matchmaking market for data and people are forced to repeat the same work. 26 26 27 27 - Open Source code has made a huge impact in the world. Let's make Open Data do the same! Open data is, essentially, public infrastructure (similar to roads, bridges, or the internet). Let's make it possible for [anyone to fork and re-publish fixed, cleaned, reformatted datasets as easily as we do the same things with code](http://web.archive.org/web/20240719190206/https://juan.benet.ai/blog/2014-02-21-data-management-problems/). 27 27 + Open Source code has made a huge impact in the world. Let's make Open Data do the same! Open data is, essentially, public infrastructure (similar to roads, bridges, or the internet). Let's make it possible for [anyone to fork and re-publish fixed, cleaned, reformatted datasets as easily as we do the same things with code](https://web.archive.org/web/20240719190206/https://juan.benet.ai/blog/2014-02-21-data-management-problems/). 28 28 29 29 This document is a collection of ideas and principles to make Open Data more accessible, maintainable, and useful. Also, recognizing that a lot of people are already working on this, there are some amazing datasets, tools, and organizations out there, and, that Open Data is a people problem at 80%. This document is biased towards the technical side of things, as I think that's where I can contribute the most. I believe we can do much more with the available data. 30 30 ··· 42 42 - Data watermarking, fingerprinting, and provenance tracking with blockchains. 43 43 - Better CPUs, compression algorithms, and storage technologies. 44 44 45 45 - These trends are already making their way towards movements like [DeSci](https://ethereum.org/en/desci/) or smaller projects like [Py-Code Datasets](https://py-code.org/datasets). But, we still need more tooling around data to improve interoperability as much as possible. Lots of companies have figured out how to make the most of their datasets. **We should use similar tooling and approaches companies are using to manage the open datasets that surrounds us**. A sort of [Data Operating system](http://web.archive.org/web/20250316031339/https://data-operating-system.com/). 45 45 + These trends are already making their way towards movements like [DeSci](https://ethereum.org/en/desci/) or smaller projects like [Py-Code Datasets](https://web.archive.org/web/20260224162429/https://py-code.org/datasets). But, we still need more tooling around data to improve interoperability as much as possible. Lots of companies have figured out how to make the most of their datasets. **We should use similar tooling and approaches companies are using to manage the open datasets that surrounds us**. A sort of [Data Operating system](https://web.archive.org/web/20250316031339/https://data-operating-system.com/). 46 46 47 47 One of the biggest problems in open data today is the fact that organizations treat data portals as graveyards where data goes to die. Keeping these datasets up to date is a core concern (data has marginal temporal value), alongside using the data for operational purposes and showcasing it to the public. 48 48 ··· 50 50 51 51 Organizations like [Our World in Data](https://ourworldindata.org/) or [538](https://fivethirtyeight.com/) provide useful analysis but have to deal with _dataset management_, spending most of their time building custom tools around their workflows. That works, but limits the potential of these datasets. Sadly, there is no `data get OWID/daily-covid-cases` or `data query "select * from 538/polls"` that could act as a quick and easy entry-point to explore datasets. 52 52 53 53 - We could have a better data ecosystem if we **collaborate on open standards**! So, let's move towards more [composable](https://voltrondata.com/codex), maintainable, and reproducible open data. 53 53 + We could have a better data ecosystem if we **collaborate on open standards**! So, let's move towards more [composable](https://web.archive.org/web/20260119102459/https://voltrondata.com/codex), maintainable, and reproducible open data.

+1 -1

Openness.md

reviewed

··· 12 12 - One of the hardest exercises is to receive [[feedback]]. Ask for it and be ready to change. Aim to improve once you've gathered feedback and reflected on it. 13 13 - Criticizing your in-group takes courage but is possible. 14 14 - Experience things again (books, movies, ...). They might be the same, but you change and are a different person now. The world changes, too. No one steps in the same river twice. 15 15 - - Look for new experiences. It is the most important factor for [memorable experiences](https://travelopment.com/how-to-create-memorable-experiences/). When all days follow the same routine, [there is no way to differentiate the memories](https://www.youtube.com/watch?v=zHL9GP_B30E). 15 15 + - Look for new experiences. It is the most important factor for [memorable experiences](https://web.archive.org/web/20240716123255/https://travelopment.com/how-to-create-memorable-experiences/). When all days follow the same routine, [there is no way to differentiate the memories](https://www.youtube.com/watch?v=zHL9GP_B30E). 16 16 - Monotony collapses time. Novelty unfolds it. You can exercise daily and eat healthily and live a long life, while experiencing a short one... Creating new memories stretches out psychological time, and lengthens our perception of our lives. 17 17 - Keep high experimental velocity. Try more things quickly! 18 18 - [When you learn an interesting idea, or read an article, it takes 0 effort to think through friends who might enjoy it, and pass it on](https://www.neelnanda.io/blog/mini-blog-post-10-seek-positive-externalities). This applies all the more so to bigger things - jobs worth applying to, other people they should talk to, etc. Receiving opportunities has (essentially) 0 downsides on their end.

+1 -1

Privacy.md

reviewed

··· 2 2 3 3 - [Privacy is about power](https://www.privacyguides.org/en/basics/why-privacy-matters/), and human information confers power over human beings. 4 4 - If we care about being authentic, fulfilled, and free humans, we have to care about the rules that apply to information about us. [Privacy gives you the freedom to live your life in a way that best suits your personal goals and needs](https://vitalik.eth.limo/general/2025/04/14/privacy.html). 5 5 - - [Doing privacy first tackles multiple online harms by addressing corporate surveillance.](https://www.eff.org/wp/privacy-first-better-way-address-online-harms) 5 5 + - [Doing privacy first tackles multiple online harms by addressing corporate surveillance.](https://web.archive.org/web/20260224191356/https://www.eff.org/wp/privacy-first-better-way-address-online-harms) 6 6 - [A society with no privacy is a severe disadvantage in any resistance against the oppressive tendencies of the state and other large corporate actors.](https://www.reddit.com/r/privacy/comments/188v2ao/why_is_privacy_important_to_you/) 7 7 - Think about how badly things can go if the wrong people end up in positions of power. 8 8 - What happens when someone is being stalked by an abusive ex-partner who works in law enforcement and has access to those databases?

+3 -3

Social Games.md

reviewed

··· 7 7 - [Diplomacy](https://play.google.com/store/apps/details?id=se.oort.diplicity). Also [Backstabbr](https://www.backstabbr.com/). 8 8 - [The Schelling Game](https://www.lesswrong.com/posts/kM3Xd2mJeWtsGkgSW/the-schelling-game-a-k-a-the-coordination-game). Discern Schelling points among the group. 9 9 - [Aumann Agreement Game](https://docs.google.com/document/d/1gCKURs0Xdnb8PQS54rckS4CJUp8kCklKs2KKi7xDZdA/edit#). Also possible to [play online](https://web.archive.org/web/20241226132325/https://aumann.io/). 10 10 - - [Calibration Questions](https://today.yougov.com/topics/politics/articles-reports/2022/03/15/americans-misestimate-small-subgroups-population). 10 10 + - [Calibration Questions](https://web.archive.org/web/20230828073617/https://today.yougov.com/topics/politics/articles-reports/2022/03/15/americans-misestimate-small-subgroups-population). 11 11 - [Black Stories](https://detective-stories.com/). 12 12 - [Stopots](https://stopots.com/es/). Choose a letter, think about things starting with it. 13 13 - [Two Rooms and a Boom](https://boardgamegeek.com/boardgame/134352/two-rooms-and-boom). [Print and Play version](https://drive.google.com/drive/folders/1_jbxtyH0V0xACK_crdIbf-QMFv0aw7pr). [Online Version](https://www.playkaboom.com/) ([alternative](http://tworooms.centralus.cloudapp.azure.com/)). ··· 39 39 - [Bartok](<https://en.wikipedia.org/wiki/Bartok_(card_game)>). 40 40 - Mao. 41 41 - [Egyptian Ratscrew](https://waste.org/~oliviax/cards/ratscrew.html). 42 42 - - [Dvorak](http://web.archive.org/web/20241219082825/https://en.wikipedia.org/wiki/Dvorak_(game)). 42 42 + - [Dvorak](https://web.archive.org/web/20241219082825/https://en.wikipedia.org/wiki/Dvorak_(game)). 43 43 - [Skull](https://boardgamegeek.com/boardgame/92415/skull). 44 44 - [Cheat / Bullshit](https://www.pagat.com/beating/cheat.html). 45 45 - [In Vino Morte](https://www.youtube.com/watch?v=ksy4mFBZmR0). ··· 75 75 - [Rocket Crab](https://rocketcrab.com/). Party games for phones. 76 76 - [Gartic Phone](https://garticphone.com/). The drawing telephone game. 77 77 - [Quicksplain](https://quicksplain.com/). Party trivia game for groups of 2 to 8 people that tests your knowledge on a variety of topics. 78 78 - - [Smart Cookie Trivia](https://www.smart-cookie-trivia.com/). Free, fun, challenging, multiplayer quizzes. 78 78 + - [Smart Cookie Trivia](https://web.archive.org/web/20251211062847/https://www.smart-cookie-trivia.com/). Free, fun, challenging, multiplayer quizzes. 79 79 - [Escape Team](https://www.escape-team.com/). A digital-physical escape room game. 80 80 81 81 ## Boardgames

+3 -3

Teamwork.md

reviewed

··· 6 6 - Stick to defining components and keep concepts generic (cache, [[databases]], algorithm, ...). Show how the components interact. 7 7 - Define boundaries and limitations of each component. 8 8 - Work in the open and [[Documentation|document]] everything. Transparency increases understanding and reduces synchronization challenges. **[Emulate Open Source projects](https://tomayko.com/blog/2012/adopt-an-open-source-process-constraints) and [[Remote Jobs|remote companies]]**. 9 9 - - [Write weekly updates](https://doingweeknotes.com/) and share them in a common place. 9 9 + - [Write weekly updates](https://web.archive.org/web/20250301174513/https://doingweeknotes.com/) and share them in a common place. 10 10 - What is shipping (e.g. what is on the near horizon). 11 11 - Why is it important / what is now possible as a result / why should people care? 12 12 - How are things progressing. Any blockers? ··· 16 16 - Automated code formatting. 17 17 - Templates for new projects and components. 18 18 - Mechanisms for creating test data. 19 19 - - Invest in [thoughtful logging](https://www.16elt.com/2023/01/06/logging-practices-I-follow/). 19 19 + - Invest in [thoughtful logging](https://web.archive.org/web/20250506184942/https://www.16elt.com/2023/01/06/logging-practices-I-follow/). 20 20 - Create a [[Company Handbooks|handbook]] to store your [[Company Knowledge Management|company knowledge]]. Document: 21 21 - [[Processes]]. Status updates, [[Design Docs]], [on-boarding docs/scripts](https://about.gitlab.com/blog/2020/02/10/lessons-learned-as-data-team-manager/), [[Checklist]], ... 22 22 - Decisions. Context and rationale can be documented in a durable location. ··· 79 79 - Being able to run small and compounding experiments (on the product or company [[processes]] and systems) is important. **Work smaller**. 80 80 - [Some experiments won't work](https://www.lesswrong.com/posts/97LgacucCxmyjYiNT/the-archipelago-model-of-community-standards). But oftentimes it _feels_ like it won't work when in fact you just haven't stuck with it long enough for it to bear fruit. This is hard enough for _solo_ experiments. For group experiments, where not just one but _many_ people must all try a thing at once and _get good at it_, all it takes is a little defection to spiral into a mass exodus. 81 81 - The group with the most power determine the system that reflect and reinforce their own way of thinking. Aim for inclusion. _Diversity is being invited to the party. Inclusion is being asked to dance and help organizing the party_. 82 82 - - [Brainstorm for questions first (explore). Then find the answers (exploit).](http://web.archive.org/web/20240522210302/https://getpocket.com/explore/item/better-brainstorming) 82 82 + - [Brainstorm for questions first (explore). Then find the answers (exploit).](https://web.archive.org/web/20240522210302/https://getpocket.com/explore/item/better-brainstorming) 83 83 - Strive for constructive conflict. Get people to [[Asking Questions|ask questions]]. Engage in passionate, unfiltered debate about what you need to do to succeed. 84 84 - Encourage to fail. Failing is good if the team [[Learning|learns]] from it! 85 85 - Encourage effectiveness. Find ways to free up your time.