articsputnik

> Third, we *give full responsibility* to a small integrated team of designers and programmers. They define their own tasks, make adjustments to the scope, and work together to build vertical slices of the product one at a time. This is completely different from other methodologies, where managers chop up the work and programmers act like ticket-takers.

Best guide on project management! Discover how fully responsible, integrated teams of designers and programmers can 10x your team's efficiency and innovation, leaving traditional management methods in the dust.

Awesome write-up. I'm on the Obsidian train, and these explain why Obsidian is the app for me (for now):

> But I've become somewhat maniacal about ensuring the longevity of my stuff. Servers break; products pivot; companies get acquired or go out of business or kill their less-loved stuff. No app is forever, and my journal entries and notes need to outlast Day One and Obsidian.

> I don't care what app or service you're using, if it doesn't come with a simple way to move your data — to another app, to a text file, to a PDF, whatever — you're at more risk than I'm comfortable with.

> The best ones start with private spaces and then add features from there, instead of starting with a mountain of collaborative features and integrations and then tacking on a privacy policy after the fact.

In that context, I love giving complete responsibility to a small, integrated team of designers and programmers. They define their tasks, adjust the scope, and work together to build vertical slices of the product one at a time. This completely differs from other methodologies, where managers chop up the work and programmers act like ticket-takers.

Instead of having 10x engineers, make the team 10x. Shape Up (https://basecamp.com/shapeup/0.3-chapter-01#making-teams-res...) by Basecamp is the best resource I've seen on that topic.

With Rust, you won't have to wait for runtime (in Production) to notice an obvious error like wrong types for example, nor do you have to set up 15 external tools to achieve the same toolchain reliability (pytest, mypy, tox, ...), these things are built-in Cargo (Rust package manager).

Of course, Python can be fast enough, and decisions like these are tradeoffs. Still, you'll have to invest a lot of DevOps time in Python to achieve a fraction of the reliability and safety guarantees Rust (and its tooling) provide—a high-level summary of the book's first chapter.

That is super exciting and frightening at the same time.

amazing

I just wrote about how it transformed my path and why I did them on "Finding My Pathless Path" at https://www.sspaeti.com/blog/finding-my-pathless-path/.

For my life journey, these sabbaticals were transformative. I had several. I love the definition by Paul Millerd, "mini-retirement." Instead of waiting for your retirement in the sixties, take more minor once along.

For my life journey, these sabbaticals were transformative. I had several tough. I love the definition by Paul Millerd, "mini-retirement." Instead of waiting for your retirement in the sixties, take more minor once along. I wrote more about how it shaped me in "Finding My Pathless Path" at https://www.sspaeti.com/blog/finding-my-pathless-path/.

I love DuckDB's simplicity and think it will solve many problems. Still, transitioning from a local single file DB to concurrent updates and serving it online will be different. I'm curious about what MotherDuck will come up with to solve DuckDB at scale.

I love use cases like the Rill Data (https://youtube.com/watch?v=XvP2-dJ4nVM), where you can suddenly run analytics with a single cmd line prompt and see your data just instantly visualized. Such use cases are only possible because of the "small" data approach that DuckDB tries.

Wow, this was super interesting as someone using a Second Brain daily. Thank you so much for digging into it, putting in the work, and sharing with us all! Much appreciated. I will follow you for more.

I am much excited to do more with my Second Brain, but one concern, as you point out, is to use chatGPT or similar; we'd need to upload all our private and sometimes sensitive notes, which is a no go for me. So happy that you do everything locally. I wonder what the equivalent would be to train the model to search and ask questions based on our second brain (plus the already trained information). That's also where Obisidan will win in the long run, as other tools do not have the data locally. Obviously, it's already in the cloud; they could train on them, but training on customer-sensitive data would be a big problem. Something I will follow closely.

I'm always intrigued by Simon, and I enjoy his open-minded way of working. Thanks, Simon!

I love learning new languages because of learning, not because it's cool. That's why learning Rust shows more about the person than being on a hype train. This is one of the best indications for hiring if I'd hire someone.

I am amazed by how Readwise improves my workflow thus far. But "Readwise Reader" seems to be their latest announcement that combines Instapaper, RSS, web highlights, tweets, YouTube videos, images, books, email, PDF, and more into one.

The best part, all highlights/notes are automatically synced into Obsidian or any note app of choice.

Live right now.

Check out the schedule:

* 8:15 AM MT - Ben Rogojan - Intro And Review Of State Of Data Survey

* 9 AM MT - Mehdi Ouazza - What's in Rust for data folks?

* 10 AM MT - Mei Tao - Building field-level lineage with ANTLR, Airflow, and dbt

* 11 AM MT - Sireesha Pulipati - Implementing Self-service analytics

* 12 PM MT - Stefan Krawczyk - Natively bringing software engineering best practices to python data transformations

* 1 PM MT - Kostas Pardalis - How Iceberg enables real-time ingestion for the data lake

* 2 PM MT - Mingsheng Hong - Data Cloud Optimization & FinOps: An Efficiency Multiplier.

* 2:45 PM MT - Zach Wilson - Data Engineering Challenges at Hyperscale

* 3:30 PM MT - Chen Chang - Building a Data Foundation: The Journey Towards a Single Source of Truth

* 4:15 PM MT - Chad Sanderson - Data Contracts - Accountable Data Quality

* 5:00 PM MT - Ananth Packkildurai - Functional Data Engineering

I mean, what happens if the models update and all API calls will not work any longer? That's going to be a challenge to integrate with such excellent technologies.

This is going to be interesting. I see significant improvements there, but keeping up with the model version will take a lot of work to integrate into all products.

Data Lakehouse to me is: > A Data Lakehouse open data management architecture that combines the flexibility, cost-efficiency, and scale of Data Lake with the data management and ACID transactions of Data Warehouse with Data Lake Table Formats (Delta Lake, Apache Iceberg & Apache Hudi) that enable Business Intelligence (BI) and Machine Learning (ML) on all data.

The initial concept was created by Databricks in the CIDR Paper (https://www.cidrdb.org/cidr2021/papers/cidr2021_paper17.pdf) in 2021.

This is so cool. It reminds me of Markdown and Mermaid (https://github.com/mermaid-js/mermaid), which can do a similar thing within a plain text file. Keep it up; looking forward to trying it out.