Yet another essay completely missing the point, and an audience that misses it as well. All these organizations fly blind because nowhere in any technology or science education is there any emphasis on effective communications, conveying understanding, solving disagreements with analysis and the best of both perspectives... none of these critical communication skills are taught to the very people that most need them. It's a wonder our civilization functions at all.
The economics of software teams: Why most engineering orgs are flying blind
101–110 of 299 posts
Re: The economics of software teams: Why most engineering orgs are flying blind
#102I thought it was a good article, till I saw the Slack example. The copy doesn’t even remotely grasp the scale of what the actual Slack sofware does in terms of scale, relaiability, observability, monitorability, maintability and pretty sure also functionality. Author only writes about the non-dev work as difference, which seems like he doesn’t know what he’s talking about in all, and what running an application at th…
Yeah, I can build a Slack "clone" in a couple of weeks with my own two hands, no AI required. But it's not going to actually be competitive with Slack. Just to pick an incredibly, unbelievably basic enterprise feature, my two-week Slack clone is not going to properly support legal holds. This requires having a hard override for all deletion and expiration options anywhere in the product, that must work reliably, in o…
> It was a cliche for many years that Microsoft Word had "too many features." So people would start companies to sell "lightweight word processors" that only implemented "the most used 20% of features." And most of these companies sank without a trace (with a couple of admirable exceptions that hyperfocused on specific niches). Google finally made progress against the monopoly, but to it, they actually invested in a huge number of features.
The other issue is that yes, perhaps most users only use 20% of the features, but each user uses a different 20% of the features in products like Word. Trust me, it's super hard to get it right even at the end-user level, let alone the enterprise level like you say.
Re: The economics of software teams: Why most engineering orgs are flying blind
#103Measuring a platform team's productivity in pure "hours saved" is missing a huge point: reliability. If your platform prevents even one outage every month, how much business value and capital are saved? That analysis is utterly absent from this article.
It also seems to focus on "LLMs make code cheap" which is a half truth: LLMs make (so far) easy or messy code cheap. I'd bet that there too the analysis on reliability/stability is missing from the author's perspective.
Re: The economics of software teams: Why most engineering orgs are flying blind
#104> A messy codebase is still cheaper to send ten agents through than to staff a team around. And even if the agents need ten days to reason through an unfamiliar system, that is still faster and cheaper than most development teams operating today. I’ve been on 2 failed projects that have been entirely AI generated and it’s not that agents slow down and you can just send more agents to work on projects for longer, it’s…
The more I work with AIs (I build AI harnessing tools), the more I see similarities between the common attention failures that humans make. I forgot this one thing and it fucks everything up, or you just told me but I have too much in my mind as context that I forget that piece, or even in the case of Claude last night attesting to me while I am ordering it around that it cannot SSH into another server but I find it SSHing into said server about the 5th time I come back with traceback and it just fixes it!
All of these things human do, and i don't think we can attribute it directly to language itself, its attention and context and we both have the same issues.
Re: The economics of software teams: Why most engineering orgs are flying blind
#105> Software development is one of the most capital-intensive activities a modern company undertakes
The article is definitely written from a "high tech" industry lens. A mid-sized utility might spend $80-$150 million USD on IT capital projects in a year, but $2b on power pole maintenance. Utilities are a strong example, but any large enterprise manufacturing company is spending more on factory upgrades that programming.
> [...] built a functional replica of approximately 95% of Slack’s core product in fourteen days using LLM agents.
IT and Finance leadership and asset heavy companies are currently trying to wrap their head around the current economics of their 100+ SaaS contracts, and if it still makes sense with LLM powered developers. Can they hire developers in house to build the fraction of the tool they use from many of these companies, save on total cost and Opex?
I work with these companies a lot, and won't weigh in on the right decision. Bottom line "it depends" on many factors, some of which are not immediately obvious. The article still holds weight regardless of industries, but there is some nuance (talent availability, internal change cost, etc.) that also have to be considered.
Re: The economics of software teams: Why most engineering orgs are flying blind
#106> The obvious objection is that code produced at that speed becomes unmanageable, a liability in itself. That is a reasonable concern, but it largely applies when agents produce code that humans then maintain. Agentic platforms are being iterated upon quickly, and for established patterns and non-business-critical code, which is the majority of what most engineering organizations actually maintain, detailed human fam…
Ceding the premise that the AGI is gonna eat my job, my job involves reading the spec to be able verify the code and output so the there’s a human to fire and sue. There are five layers of fluffy management and corporate BS before we get to that part, and the AGI is more competent at those fungible skills. With the annoying process people out of the picture, even reviewing vibeslop full time sounds kinda nice… Feet u…
I think you missed the key capitalist part:
There needs to be someone to benefit from all your labor. No, no, it can't be you. You have conflicts of interest!
Re: The economics of software teams: Why most engineering orgs are flying blind
#107> A messy codebase is still cheaper to send ten agents through than to staff a team around People who say that haven't used today's agents enough or haven't looked closely at what they produce. The code they write isn't messy at all. It's more like asking the agent to build a building from floorplans and spec, and it produces everything in the right measurements and right colours and passes all tests. Except then you…
A lot of that can be overcome by including the need to be able to put more floors on top as part of the spec. Whether it be humans or agents, people rarely specify that one explicitly but treat it as an assumed bit of knowledge.
It goes the other way quite often with people. How often do you see K8s for small projects?
Re: The economics of software teams: Why most engineering orgs are flying blind
#108> A messy codebase is still cheaper to send ten agents through than to staff a team around. And even if the agents need ten days to reason through an unfamiliar system, that is still faster and cheaper than most development teams operating today. I’ve been on 2 failed projects that have been entirely AI generated and it’s not that agents slow down and you can just send more agents to work on projects for longer, it’s…
Is there a case for having more encapsulation? So a class and tests are defined and the LLM only works on that.
Re: The economics of software teams: Why most engineering orgs are flying blind
#109> A messy codebase is still cheaper to send ten agents through than to staff a team around People who say that haven't used today's agents enough or haven't looked closely at what they produce. The code they write isn't messy at all. It's more like asking the agent to build a building from floorplans and spec, and it produces everything in the right measurements and right colours and passes all tests. Except then you…
The problem is, the MBAs running the ship are convinced AI will solve all that with more datacenters. The fact that they talk about gigawatts of compute tells you how delusional they are. Further, the collateral damage this delusion will occur as these models sigmoid their way into agents, and harnesses and expert models and fine tuned derivatives, and cascading manifold intelligent word salad excercises shouldn't be under concerned.
Re: The economics of software teams: Why most engineering orgs are flying blind
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