So... it's like a golfer who hits thousands of balls into an open field without ever once aiming for a hole. The relentless repetition flawlessly locks in their foundational muscle memory and basic swing mechanics, so when they finally step up to a real course, they don't have to waste a single thought on how to hold the club. Their basic swing is completely automatic - they can confidently take the creative, high-risk shot required to actually sink a hole-in-one.
I built this partly because i wanted a cleaner side-by-side comparison of the big “2026 outlook” reports (banks + asset managers), and partly as an experiment in whether codex / claude code / cursor together can be pushed to handle citations accurately rather than hallucinating summaries. Quite pleased with the result.
The workflow was roughly: ingest publicly available outlook reports, extract claims, numbers, and framing (& force every synthesized statement to be tied back to a specific source/page), anchor on key themes (ai capex, policy path, power/energy, credit, etc.) rather than by institution.
I agree - it is surprising how many are looking at doing in house.
I think what they miss (and I say this as someone who spent the early part of his career outside of tech) is an understanding of what goes into maintaining software products - and this ignorance will be short lived. I was honestly shocked how complex it was to build and maintain my first web app. So business types (like I was) who are used to 'maintaining' an excel spreadsheet and powerpoint deck they update every quarter may think of SaaS like a software license they can build once and use forever. They have no appreciation of the depth of challenges that come with maintaining anything in production.
My working model is that of no-code - many non-tech types experimented with bubble etc, but quickly realize that tech products are far deeper than the (heavily curated) surface level experience that the user has. It is not like an excel model where the UI is codebase. I expect vibe-coders will find the same thing.
I have on several occasions built my own versions of tools, only to cave and buy a $99 a year off the shelf version because the maintenance time isn't worth it. Non-tech folks have no idea of the depth of pain of maintaining any system.
They will learn. Will be interesting to see how it plays out.
Quite honestly, this is exactly what I am currently doing - identified a market with probably $50mm global TAM. Bootstrapping with first design partners currently.
One thing I didn't mention is that there are often a few sleepy legacy SaaS players (often public) in these niche markets who don't have the chops to add AI to their product and may be a good takeout / exit down the line. Won't be for billions, but if you bootstrap, that doesn't really matter.
I agree about boutique software, but see the development still being external -
To attempt to summarize the debate, there seems to be three prevailing schools of thought:
1. Status Quo + AI. SaaS companies will adopt AI and not lose share. Everyone keeps paying for the same SaaS plus a few bells and whistles. This seems unlikely given AI makes it dramatically cheaper to build and maintain SaaS. Incumbents will save on COGS, but have to cut their pricing (which is a hard sell to investors in the short term).
2. SaaS gets eaten by internal development (per OP). Unlikely in short/medium term (as most commenters highlight). See: complete cloud adoption will take 30+ years (shows that even obviously positive ROI development often does not happen). This view reminds me a bit of the (in)famous DropBox HN comment(1) - the average HN commenter is 100x more minded to hack and maintain their own tool than the market.
benzible (commenter) elsewhere said this well -
"The bottleneck is still knowing what to build, not building. A lot of the value in our product is in decisions users don't even know we made for them. Domain expertise + tight feedback loop with users can't be replicated by an internal developer in an afternoon."
This same logic explains why external boutique beats internal builds --
3. AI helps boutique-software flourish because it changes vendor economics (not buyer economics). Whereas previously an ERP for a specific niche industry (e.g. wealth managers who only work with Canadian / US cross-border clients) would have had to make do with a non-specific ERP, there will now be a custom solution for them. Before AI, the $20MM TAM for this product would have made it a non-starter for VC backed startups. But now, a two person team can build and maintain a product that previously took ten devs. Distribution becomes the bottleneck.
This trend has been ongoing for a while -- Toast, Procore, Veeva -- AI just accelerates it.
If I had to guess, I expect some combination of all three - some incumbents will adapt well, cut pricing, and expand their offering. Some customers will move development in house (e.g. I have already seen several large private equity firms creating their own internal AI tooling teams rather than pay for expensive external vendors). And there will be a major flourishing of boutique tools.
Strava is the closest thing to effective social media that I use, because it is 'slow'.
You create 'content' by doing something orthogonal.
You pay for access vs selling attention for ads.
You only look at Strava when you are working out, so engagement is authentic vs contrived/performative. I care about my friend completing a run because I know they did it.
One of the best thing they did was allow the chance to add photos.
Juice not worth the squeeze I imagine. 4.5 is chonky, and having to reserve GPU space for it must not have been worth it.
Makes sense to me - I hadn't founding anything it was so much better at that it was worth the incremental cost over Sonnet 3.7 or o3-mini.