Board

A week of Nix hacking near the ocean

Now, these are financial concepts, typically not applied to talent. But some people do

Desktop environment in the browser

For over a year now I've been working on daedalOS, my desktop environment in the browser. At the...

Zero config PWA plugin for Next.js, with workbox 🧰 with appDir support

A blog by sunfishcode

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Customer obsession is the only winning strategy. Pretending to be customer obsessed is easy when the times are good. It’s easy to lose track of customer obsession when there’s plenty of funding, when you have decades-long network effects, or when you operate a monopoly. A few examples:

Suspend disbelief and assume there will be an “AI Engineer” in the future. Where does this role fit in? What organization does it become part of? R&D (Competition centers on training the best or biggest model.) Traditionally this is where AI has been in the organization. Labs experimenting with foundational model research. Examples are Google Brain/DeepMind and some of the earlier foundational model companies — OpenAI and Anthropic. Of course, the number of qualified PhDs in this position is small (but growing).

Object-relational mapping (ORM) libraries are scattered about millions of code repositories. They promise to bridge the gap between a relational database and an object-oriented programming language. Instead of writing a SQL query like `SELECT * from users where id = 1`, you would define a User type with some special annotations and then write something like `user = users.select().where(“id = ?”, id)`. Some other features they might provide: type safety, connection management, or a migration framework.

繁體中文版請按這裡This article is translated from the original Chinese edition. In the world of databases, Redis stands out as unique. Instead of the usual tables or documents that are the central focus of most databases, with Redis, you interact directly wi...

I remember reading an article years ago about a father in Yemen who lost a son to starvation, only to…

Developers face an onslaught of marketing and an unrelenting velocity of releases to keep up with. This is why we started Console.

Arcjet is a tier-1 VC backed startup hiring several founding engineers to help build the future of developer security in the age of the developer.

Reddit communities are still private in protest of new API rules. Twitter moved beyond a login wall and is rate-limiting users. Users are frustrated but still using these sites. But — what will happen to the Google Index? Millions of search results are effectively dead links. Users that refined Reddit search results via Google are now out of luck (Reddit’s search is inferior). Tweets in the search engine results page (SERP) now lead to a login wall for many users.

A sample of career ladders Sarah Drasner uses for her organization, open sourced for anyone.

Legacy British schools are learning to reconcile their illustrious legacy with fussy Indian parents and strict state laws

Enable Self-Service Operations: Give specific users access to your existing tools, services, and scripts - rundeck/rundeck: Enable Self-Service Operations: Give specific users access to your existi...

At the height of the dot com bubble, Yahoo was printing money from selling ads. Enticed by Yahoo’s success, more money was invested in startups. These startups, in turn, bought ads on Yahoo. Many of these startups failed when the bubble burst, and Yahoo’s market capitalization dropped dramatically.

News, tips, and tricks from the team at Fly.

Oil was found in Lima, Ohio, in 1885. It was one of the most productive oil regions by 1886. Except the oil was “heavy” — thick and sulfurous. It smelled so bad that not only did people refuse to use it to light kerosene lamps, but some cities outlawed its transportation. It was practically unusable. John D. Rockefeller started to buy up the sulfurous Lima oilfields. He bought so many barrels that the board of directors protested until Rockefeller agreed to put up millions of his own capital to finance it.

The brain metaphor for neural networks has always been a fun simplification but not a useful one under closer inspection. How we train and inference deep networks doesn’t have much to do with how the human brain works. But what if LLMs could teach us more about ways that we approach general reasoning and languages? Some personal lessons I’ve learned (or have been reinforced) from working with LLMs.

There aren’t many agreed-upon definitions, but I’ll attempt a simple distinction: IT covers physical provisioning and maintenance. Data center management, on-premise appliances, and technical support. DevOps covers virtual provisioning and maintenance.

It's always been true that speed is the #1 advantage of an early-stage startup. But now that generative AI here, you need to go 10x faster.