Posts

Admonition to myself

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Most people quit before they reach their best work. Excellence lives in doing a bit more than others. From:  https://fs.blog/brain-food/february-16-2025/  

Altavista

From:  https://www.abortretry.fail/p/work-at-the-mill On the 15th of December in 1995, DEC made the AltaVista search engine publicly accessible on the World Wide Web. The search engine ran on two machines named Scooter and Turbo Vista. Scooter had a 20GB hard disk and 1GB of RAM and it did the page fetching/crawling while Turbo Vista had 250GB hard disk and 2GB of RAM and handled the index and web serving. Naturally, these were both Alpha machines. The company took advantage of its head count to test the system with 10,000 employees trying it out prior to launch. While the minicomputer and workstation company might seem out of place on the Web, Digital had registered dec.com in 1985 and digital.com in 1993. Let us not forget, DEC’s wonderful hardware had even powered many of the earliest networks that comprised the early internet. AltaVista was success. The site had approximately 300,000 hits on its first day of public availability; by the end of the year, the count had grown to 19...

Cheapest way to improve developer productivity

Dirt cheap and easy, just two things: give them the best IDE you can afford a large screen display (27" or above)

Reverse Improvement

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Via:  https://changelog.com/news/131 Bill Maher is new to me, and in a bit over 8 minutes he just became my favorite satirist. In a new segment called New Rule Bill Maher lamented the shitty status of technology driven forced improvement which I'm the first to admit, a lot of times, does not make our lives materially better. He makes the examples of streaming services which drive the user experience back to where we were 20 years ago (or worse), disappearing car handles and apps to do everything. As a European I can't really relate on the car valet experience, but I do find infuriating the growing number of restaurants forcing me to scan a QR code, register with my email, and then squint at my phone screen trying to decide what to order. Bring paper menus back 😠 It's a well worth watching 8 minutes. Especially if you work on the field. The lack of ethics in our field is really showing, and TBH I think we got away easily in this critique. It could have gotten much worse...

Playbook: turning around a software engineering team

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A note-to-self kind of post on a playbook to turning around a struggling sw engineering team. Core principles always behave trustworthily slow down and make time to address problems do you have the right people? if you can't get consensus, seek consent Foundational engineering best practices With regards to engineering best practices, the following are foundational and should be part of the execution somewhere between steps 4 and 8 of the playbook: trunk-based development continuous integration no separate tester or devops team (this can be relaxed after the team begins performing), seek out a stream-aligned team instead SCRUM with its process is useful to align the team and at last one main stakeholder automate as much as you can, especially the parts that come up often for discussion; one obvious but often overlooked example are customized coding styles (use the consent-over-consensus principle to reach a decision) If the team resists them or does not make progress, then see the...

Quasi-code with Apache Camel

Debating whether to go no-code but worried about unclear licensing, the dreadful we-need-to-rewrite-it dram down the road or django/rails/spring boot and its relatively higher upfront cost? There's a third way: quasi-code with Apache Camel . It still amazes me how few people know about the swiss-army knife of integrations.

LLMs (might) make it easier to port code away from CUDA

I was reading this interesting analysis on Nvidia competition (as usual, his blog should be on your feed) from Simon Willison and this bit caught my attention (emphasis mine): Technologies like MLX, Triton and JAX are undermining the CUDA advantage by making it easier for ML developers to target multiple backends - plus LLMs themselves are getting capable enough to help port things to alternative architectures . I found it curious that the very same thing that's been fueling Nvidia's success could also help reduce/eliminate their moat.