zlacker

>>peteth+(OP)
> The fear is that these [AI] tools are allowing companies to create much of the software they need themselves.

AI-generated code still requires software engineers to build, test, debug, deploy, secure, monitor, be on-call, support, handle incidents, and so on. That's very expensive. It is much cheaper to pay a small monthly fee to a SaaS company.

>>latefo+G02
Hmm, I wonder if it would be cheaper to hire a couple of software engineers to vibe-code custom SaaS apps on top of the company's existing data layer instead of paying for a hundred different SaaS subscriptions.

Financial considerations aside, one advantage of having in-house engineers is that you can get custom features built on-demand without having to be blocked on the roadmap of a SaaS company juggling feature requests from multiple customers...

>>keeda+G72
I'm at a large company that is building connections between all of its different financial systems. The primary problem being faced is NOT speed to code things, the primary problem at large companies is getting business aligned with tech (communication) and getting alignment across all the different orgs on data ownership, access, and security. AI currently doesn't solve any of this. Throw in needing to deal with regulation/SOX compliance and all the progress you think AI might make, just doesn't align with the problem domains.

>>Sleake+Uf2
This is also generally true for all mid to large businesses I've ever worked at.

The code they write is highly domain-specific, implementation speed is not the bottleneck, and their payroll for developers is nothing compared to the rest of the business.

AI would just increase risk for no reward.