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- Hacker News
- The strongest signal I have seen for whether AI actually reduces maintenance cost is whether the developer treats AI output as a first draft or a final artifact.
When I use AI tools on existing codebases - understanding unfamiliar modules, generating targeted refactors, writing migration scripts - the maintenance burden genuinely drops. The AI is working on code I already understand architecturally, so I can evaluate its output quickly.
The problem shows up when AI generates greenfield code that nobody deeply understands. That code still has to be maintained by humans who did not write it AND did not design it. At least with code another human wrote, you can reason about their intent from naming, structure, and commit history. AI-generated code often lacks that legibility because the "author" had no persistent intent across files.
The article is right that we need to measure maintenance cost, not just velocity. In practice that means tracking time-to-understand and change-failure-rate on AI-assisted code vs. human-written code over months, not days.
by lacymorrow - I really like this question:
If you could wish for a codebase, which codebase would you wish for?
If you think a second on that question, you’ll realize you probably not wishing for a super feature-rich one, but an easy to understand one, quite close to what you have now. One that is easily to maintain and extend, depending on the upcoming business challenges.
by jwpapi - Same with code reviews.
I wonder if AI could make code reviews more presentable.
for example, with human code reviews, developers learn quickly not to visually change code like reflowing code or comments, changing indent (where the tools can't suppress it), moving functions around or removing lines or other spurious changes.
And don't refactor code needlessly.
also, could break reviews up into two reviews - functional changes and cosmetic changes.
by m463 - My team has been using AI to add code, but also to aggressively remove old deprecated code. "Is anyone still using this? How does this get called" is easier to answer when you can toss your FE, BE, and entire codebase at an agent and let it create a map of your software project. IDEs can do this in a single language to some degree usually in a single project, but RPC, REST, etc... break some of these tools in a lot of IDEs.by Seattle3503
- Two things I'd add
1. software doesn't only have tech maintenance - there is also user support and it increases as software grows.
2. I'm not convinced maintenance costs scale linearly. And even if it scales linearly, you will eventually get to a point where maintenance takes up all your time.
by dirkc - In my Dconf'24 talk "Software as investment" I proposed a basic framework based upon a value function (compositional) for each piece of software. This framework doesn't really need an update due to AI, apart from the (unrelated!) cost model being updated depending on how good AI is at maintenance. Apparently it would do 1.7x the number of bugs, but perhaps it fixes them faster too? I don't know.
Seeing software as investment avoids speaking about "technical debt" by speaking about "value", a liability just being an asset with < 0 value. When software exits the high-margin world of yesterday it needs to develop a precise definition of what software deserves to exist, economically.
by p0nce - Insightful. Agree with this take.
Unfortunately, maintainability is simply bucketed as a "non-functional" requirement.
Maintainability (and similar NFRs) should actually be considered what preserves and enables the delivery of future functional requirements -- in contrast to framing non-functional requirements as simply "how" the software must do what it does vs. the "what"/functional requirements that "actually matter".
From that standpoint, if a steady flow of features/improvements is important for a project, maintainability isn't really a non-functional requirement at all, and amounts to being a functional requirement, in practice, over anything except the shortest of time horizons.
- In my experience AI reduces maintenance costs. Though, context might matter here, I'm working on a multi decade set of projects, while there is a lot of greenfield feature development, the old code / older projects have suddenly become a lot easier to work with, modernize, and in a bunch of cases, eliminated. Dependency on old libraries, build tools, in some cases updated, in other cases just eliminated, builds are faster, easier for developers, etc. End to end testing has become a lot easier to setup and automate. DevOps have been improved a lot, diagnosing production issues drastically improved, we have a ton of logs and information, and while we have various consolidated dashboards / monitoring to capture critical things, now we can do a lot more analysis on our deployed system (~50 ish projects)by keithnz