Programmer aesthetics: “your engineering taste is composed of the set of engineering values you find most important.” // And: “most bad taste comes from inflexibility. I will always distrust engineers who justify decisions by saying ‘it’s best practice.’ No engineering decision is ‘best practice’ in all contexts! You have to make the right decision for the specific problem you’re facing.”
They advocate for using JSON (with comments) over YAML: “Generating json as a better yaml Often the choice of format is not ours to make, and an application only accepts yaml. Not all is lost though, because yaml is a superset of json, so any tool that can produce json can be used to generate a yaml document.”
🤖 Technical writers are shifting from writers to content directors, steering and editing AI output. To thrive: build deep subject matter expertise and tool expertise–with editorial judgment and workflow skills as supporting habits. // How many managers does the world need, though?
🔗 Two strategies to succeed when AI seems to be eroding jobs around you
“Doughnut Economics is based around an important insight: Diagrams are powerful marketing tools.”
And, from the book reviewed:
Visual frames, it gradually dawned on me, matter just as much as verbal ones…[N]ow is the time to uncover the economic graffiti that lingers in all of our minds and, if you don’t like what you find, scrub it out; or better still, paint it over with new images that far better serve our needs and times
Once you fix the bottleneck of coding, you face the all the other bottlenecks down the line. So, you have to think of how to apply AI, or whatever, to the rest of the SDLC processes. Some real theory of constraints stuff there.
Manton reviews ChatGPT Pulse: it might drive traffic to more websites, going around Google:
There’s something else about how this works that is fundamentally different than current chat-based AI where people are looking for answers. Instead of replacing a Google search, it’s adding opportunities to point to other websites and blogs. Because it’s proactively pushing stories to you that you may never think to look for, it should increase referrers to websites instead of subtracting them. Not enough to offset the lost Google searches, but still notable.
Enterprise AI not legible. If you can’t measure it, you can’t ROI it: “It’s easy for an employee to say, ‘Yes, this will help me,’ but hard to quantify how. And if they can’t quantify how it’ll help them … it’s not going to be a long discussion” over whether the software is worth paying for, Thompson said. // And: it’s a “challenge for businesses is that there’s this leap of faith moment where you try to justify it with the return-on-investment calculation, which is hard to figure out.”
🔗 Microsoft Hopes Hastened AI Rollout, Price Discounts Can Fuel Office 365 Growth
“But after nine months on the market, fewer than 5% of Salesforce’s more than 150,000 customers are paying for Agentforce, according to the company’s disclosures. And more than half of customers that are using Agentforce are still testing it without paying.”
🔗 Marc Benioff Said AI Was Easy. A ‘Crazy’ Team at Salesforce Proved Him Wrong
‘I think the level of quality that everything has these days, every image, every website, every song, every video also has downsides. It defining the “norm”, the expectation we have from one another has two main issues that keep irritating me.’
nine out of the top 10 AI labs use Google’s infrastructure. He also says that nearly all generative AI unicorns run on Google Cloud, that 60% of all GenAI startups worldwide have chosen Google as their cloud provider, and that the company has lined up $58 billion in new revenue commitments over the next two years, which represents more than double its current annual run rate.
(1) Clearly, some comms work in action here, to, (2) get the message out there that Google is kind of a big deal. Unlike with Kubernetes, Google hasn’t been able to (effortlessly?) translate it’s brand-appeal to AI. Maybe that’s because much of AI-frenzy is consumer-focused, not nerd-focused (as was the case with Kubernetes).
🔗 It isn’t your imagination: Google Cloud is flooding the zone