alt Hacker NewsI am the founder of a niche SaaS (https://partsbox.com/ — software for managing electronic parts inventory and production). While I am somewhat worried about AI capabilities, I'm not losing too much sleep over it.
The worry is that customers who do not realize the full depth of the problem will implement their own app using AI. But that happens today, too: people use spreadsheets to manage their electronic parts (please don't) and BOMs (bills of materials). The spreadsheet is my biggest competitor.
I've been designing and building the software for 10 years now and most of the difficulty and complexity is not in the code. Coding is the last part, and the easiest one. The real value is in understanding the world (the processes involved) and modeling it in a way that cuts a good compromise between ease of use and complexity.
Sadly, as I found out, once you spend a lot of time thinking and come up with a model, copycats will clone that (as well as they can, but superficially it will look similar).
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Not specific to PartsBox, but we use Inventree (open source similar to PartsBox) and self host it. Over the past few months we noticed certain pain points in our workflow. Rather than looking for a new tool, we used Claude Code to write some backend services and some frontend modifications. Took 2 days of tinkering. Has easily saved that much time since we implemented it.
While rolling the whole solution with an AI agent is not practical, taking a open source starting point and using AI to overcome specific workflow pain points as well as add features allows me to have a lower cost, specifically tailored solution to our needs.
> Coding is the last part, and the easiest one. The real value is in understanding the world (the processes involved) and modeling it in a way that cuts a good compromise between ease of use and complexity.
Coding and modeling are interleaved. Prototyping is basically thinking through the models you are considering. If you split the two, you'll end up with a bad model, bad software or both.
Coding agents like Claude are just one line of AI making inroads. There are lot of nearly tasks that can be almost, but not quite, implemented effectivly with existing tools like Excel and Word. As they seek a return on their investments, are MS likely to target those nearly cases with AI in their Access, Excel, Word etc product lines?
I have two tech q about partsbox. Why Clojure? Why not CL (lack of saas related-features)?
The problem IMO is simpler.
You have a product, which sits between your users and what your users want. That product has an UI for users to operate. Many (most, I imagine) users would prefer to hire an assistant to operate that UI for them, since UI is not the actual value your service provides. Now, s/assistant/AI agent/ and you can see that your product turns into a tool call.
So the simpler problem is that your product now becomes merely a tool call for AI agents. That's what users want. Many SaaS companies won't like that, because it removes their advertising channel and commoditizes their product.
It's the same reason why API access to SaaS is usually restricted or not available for the users except biggest customers. LLMs defeat that by turning the entire human experience into an API, without explicit coding.
> The real value is in understanding the world (the processes involved) and modeling it in a way that cuts a good compromise between ease of use and complexity.
Which I don't think can be replaced by AI in a lot of cases. I think in the software world we are used to things being shared, open and easily knowable, but a great deal of industry and enterprise domain knowledge is locked up inside in companies and will not be in the training data.
That's why it's such a big deal for an enterprise to have on prem tools, to avoid leaking industry processes and "secrets" (the secrets are boring, but still secrets).
A little career advice in there too I guess. At least for now, you're a bit more secure as a developer in industries that aren't themselves software, is my guess.