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Eight Myths on Software Engineering and GenAI

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Re: Eight Myths on Software Engineering and GenAI

#51

I feel like all you need to know about how seriously to take this is that they cite that ancient early-2025 METR study, and describe it in the text as "recently one even found..."

Same thought - 80% through reading it occurred to me to check the citations. A few items from 2025 and most well before that. So much has changed since late 2025 one can’t really draw any conclusions from this. In fact, I’m guessing things will continue to move so fast that by the time one were to execute a survey of developers, many of the responses and findings are no longer relevant.

Exactly. I saw them using things from 2025... AI sorta sucked then and didn't really "take off" until that Opus drop in December or whatever it was.

Re: Eight Myths on Software Engineering and GenAI

#53
A lot of this rings true, but I think it's still too narrow. Sure, coding does not equal productivity, that is well debunked already. But I would argue that productivity is a product of engineering delivery + product decision making. Now where is the line between product and engineering? It varies by company, team and individual, but I don't think productivity can be measured for those functions independently, and in fact I see gains from AI on both the coding AND the product management side.

Basically as a senior tech lead in a large company engineering org, I don't have the bandwidth to individually validate every assertion from engineers on other teams OR from every product manager that comes with a half-baked ask. In the past I would be limited by the influence I could get through human relationships to strong SMEs with good judgment, and those folks always thin out as a company grows and calcifies. The number of creative and innovative thinkers dwindles, and the number of people protecting their turf and doing the minimum not to get fired increases. As a result many good ideas can get blocked by random gatekeeprs with poor imagination, poor expertise or both. However with AI I can follow up on gut instincts and fact check a lot more things, and ask incisive questions that can cut through a lot of organizational bullshit.

That's where I think most of the AI gains are today. Of course once AI plateaus and normalizes I think it will be baked into the org structures of tomorrow. But for now it offers real competitive advantage to those with the expertise to ask the right questions.

Re: Eight Myths on Software Engineering and GenAI

#54

I don't understand Myth 1 (Developers Spend Most of Their Time Writing Code). They quote a study in which developers report to spend 11-14% of their day coding. The rest is stuff like solution design and meetings. The insinuation is that AI can at most automate 14% of your day. The problem with this argument is that once you have code, some (not all) of the precursors to code go away.

Okay. Show me the evidence that AI has an impact on productivity when doing design work. Or reducing meeting load. My own experience is that AI doesn't tighten the design cycle, and in fact might extend it by encouraging gold plating.

> Or reducing meeting load.

Well, I expect when you've vibed too much and lost track of the code, and can't answer questions in meetings anymore, you'll stop getting invited to them.

Re: Eight Myths on Software Engineering and GenAI

#55

I feel like all you need to know about how seriously to take this is that they cite that ancient early-2025 METR study, and describe it in the text as "recently one even found..."

I felt the same and why didn’t the authors look over METR’s recent material? https://metr.org/blog/2026-05-11-ai-usage-survey/

The whole point of the 2025 one is that they found the self-reporting to be significantly inflated, which is why self-reported surveys like this one are hard to trust.

Re: Eight Myths on Software Engineering and GenAI

#56

I don't understand Myth 1 (Developers Spend Most of Their Time Writing Code). They quote a study in which developers report to spend 11-14% of their day coding. The rest is stuff like solution design and meetings. The insinuation is that AI can at most automate 14% of your day. The problem with this argument is that once you have code, some (not all) of the precursors to code go away.

Okay. Show me the evidence that AI has an impact on productivity when doing design work. Or reducing meeting load. My own experience is that AI doesn't tighten the design cycle, and in fact might extend it by encouraging gold plating.

It certainly helps as a research assistant for design work. But it can’t do it for you.

Re: Eight Myths on Software Engineering and GenAI

#57

Earlier quoted context omitted.

> That meeting that you spent an hour in to understand the requirements? You don't need that meeting if you're not writing the code. How are you going to prompt the LLM or validate its output if you don't understand the requirements?

In some number of cases, the business partner who would have passed you the requirements will just generate the code themselves.. I’m shocked shin some engineers don’t see a massive disruption coming..

[deleted]

Re: Eight Myths on Software Engineering and GenAI

#58
post #40

Earlier quoted context omitted.

Self-reported or observational data capturing time spent for categories of task ala every other similar study in this space? This isn't exactly novel territory, here, Simon. Let's not pretend I'm asking for something strange, unprecedented, or unreasonable.

How's this? https://simonwillison.net/2026/Jul/13/datasette-code-frequen... I have similar charts across my three main open source projects: https://github.com/simonw/datasette/graphs/code-frequency https://github.com/simonw/llm/graphs/code-frequency https://github.com/simonw/sqlite-utils/graphs/code-frequency

I don't think volume of code changed was the metric the other commenter was asking for.

Re: Eight Myths on Software Engineering and GenAI

#59

The 14% coding time figure is one of those stats that sounds surprising until you actually track your own time. When I started building a coding agent with persistent state, I realized how some days are spent with minimal actual typing, most of it is design, reading code, debugging, problem solving, and context-switching. But I'd push back on one thing the article implies that AI is automatically a productivity win.…

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Re: Eight Myths on Software Engineering and GenAI

#60

I don't understand Myth 1 (Developers Spend Most of Their Time Writing Code). They quote a study in which developers report to spend 11-14% of their day coding. The rest is stuff like solution design and meetings. The insinuation is that AI can at most automate 14% of your day. The problem with this argument is that once you have code, some (not all) of the precursors to code go away.

I don't know about others, but at work, the reason I only spend like 14% of my day coding is because I'm lazy, not because I'm actually doing other stuff.

Not lazy it is a taxing task like doing an exam.
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