I'm a non-tech worker in a non-tech industry, let me state two things:
- Software today is written to cover as many use cases with as many features to target as many users a possible.
- End users very often only use a tiny slice of the program's capabilities, but still pay for the entire program.
This creates a situation where the people writing software see it as a monumental undertaking to get good functional programs (it is), and end users see programs as having annoying learning curves with lots of bloat and "unnecessary" features.
LLMs do an excellent job of fixing this for end users because it allows them to easily create a program that does the handful of tasks that they normally need to use MegaSoftware for. And it's tailor made exactly for the use case. And the LLM can tell you exactly how to use it.
I can give a brief example where I used gemini to create a CAD file transposition tool that utilized a simple GUI tailor made for the files my company works with. This allowed us to forgo a (very) expensive CAD software package to work through converting our archive of files. A probably 2M LOC program could be skipped because we only needed 3k LOC functionality.
I really cannot stress enough how often this is the case, and why SWEs see LLMs as weak tools while end users see them as gods.
There will still be a need for huge software packages in the future, but I know I never again have to pay for a huge class of "here is a large solution space that covers your small scope problem" software.
To bring it home, loveable understands this, an sees that the futures has lots of non-tech people "writing" software. Standard IDEs are not the tools your mom will use to make a "Friends and family birthday reminder" app.
End users rarely pay for the program. Someone in their management chain OKs the purchase, or there's a larger purchase with a cross-charge to the department for the license cost. the problem comes when software needs to meet every whim of the decision maker, when really the users only will ever use 20% at best.
> I'm a non-tech worker in a non-tech industry…
Certainly you must have enough detailed knowledge of CAD files to validate the output of the transposition tool you had AI create for you. This might not be enough for you to think of yourself as ”technical” but I’d argue that it’s far above the level of “entry level employee using CAD”.
This does also seem to fit the paradigm of “AI is a productivity booster for people who already know how to do x”
I agree with you, and I think the Jevons paradox will eventually manifest itself once again. How many smaller companies are stuck with outdated workflows and tools because they can't afford to pay ten engineers for months on end for something better?
Now those companies may very well be able to afford one engineer and some AI subscription to do the equivalent work.
I don't deny that there's utility in what you are describing: if you can make it work for you that's fantastic. However:
- if you can ship software like that given the current state of the technology, you are probably not the average non-tech worker in a non-tech industry. There are people paying exorbitant consulting rates for dashboards in PowerBI. LLMs in mid 2025 are orders of magnitude more operationally complex than anything most people have seen.
- "citizen developers" doing something to scratch their own itches sounds very much like how a professional software project starts. Suddenly the scope grows and you need a nerd to handle it. Then two. Then four. You get the idea. Maybe that won't be the case for your specific needs, but that's how it generally goes.
Weak or strong is a matter of framing, but that's why I see them as tools and not gods.
I don't disagree with the thrust, but I've recently cleaned some of those up.
One example: LLMs aren't smart enough to do things like properly manage zip codes with leading zeros. It was round tripping strings through an integer representation and corrupting them. The users did notice, but did not have the vocabulary/concepts to explain. To them, sometimes zipcodes get corrupted because inscrutable reasons (tm).
chatgpt also authored a bash script that would have blown away a chunk of my drive if any paths had a space in them. :shrug:
You're absolutely right and one has to judge the HN consensus on AI tools through a lens of bias of the very demographic being challenged by AI tools.
Good point. "Build vs buy" is a perennial controversy
https://www.thoughtworks.com/content/dam/thoughtworks/docume...
i see one crazy real leverage: every prototype built here is a frozen snapshot of someone's product thinking in motion. like u can literally watch how ppl prioritize flows, kill features mid-wireframe, choose friction over flexibility. it’s raw cognitive output
if lovable ever starts versioning those moves, storing reasoning behind edits, even lightly, u got a time-series of product intuition across thousands of users. that’s applied decision memory.
there's a window here to become the place where product sense gets archived and replayed.
I think what current agent's are missing is taste or the ability to tune taste. So capturing taste across many users might be really valuable.
...and then PM's can have the same wonderful experiences as engineers: finding the exact commit where a major change was made 6+ months ago by a former employee, with a comment like 'updated behavior' that gives zero insight into what led to the change or why it was made.
I don't get how this company makes money. Everyone who uses these tools is just building prototypes. They get to 60-70% functionality, but when it comes to actually productionize and launch, 99% of these projects will get abandoned. The churn has to be absurdly high, maybe people are just forgetting to cancel their subscriptions. Or they're just marketing very hard and getting new sign ups/subscriptions, but will crash and burn soon enough.
I noticed in the example product the person was bragging they made "$1.6k in 5 weeks" but looking at the screenshot they were selling "lifetime access" built on this product they pay $25 a month for. I think there is going to be a reckoning for all these fly-by-night SaaSlings and the poor people who start to rely on them.
> Everyone who uses these tools is just building prototypes.
But also I think that's kinda the point. Like for example we have to do a UI redesign of an app my company is building and our "wireframes" are just v0 projects my PO created in one afternoon.
I think wireframing is where these tools really shine. It's gives you roughly the same ideas as building a wireframe in Figma but it's way less work and you end up with higher fidelity wireframes.Like sure if I were to peek at the code under the hood I'm certain it's close to dogshit but the code doesn't really matter at that stage.
> building the software that can build all other software
All other software?
I'm afraid I stopped believing the author at that point...
It’s a marketing piece written by copywriters. Probably with AI suggesting the main arguments.
I don't think the idea sticks with me. The final products of these services are never reliable.
Right now, except for some hyperscalers, any similar service has integrated their deployments to some hyperscaler which means any day 2 operations will happen in someone else's computer (supabase, azure/aws, etc). On top of that, you have third party services that you need to integrate and manage their pricing plus auth. That alone is another challenge. Let's not even start with stateful data and migrations which is almost non existent.
The main problem is these tools don't tackle day 2 operations so it will be handled to some developer to make it happen which means exporting your code to some VCS service which I think it's only github. Right there, it's a threat for lovable and others. On top of that, there's not a real feedback loop between manual integration (external dev making it prod ready) and keeping the MVP workflow. Also, there's no real way these services can say "you are free to touch these components without breaking incompatibility with our system, anything else here be dragons".
In other words, You need to own the ecosystem to make more money. Funnel the capabilities to your own ecosystem.
> manual integration (external dev making it prod ready) and keeping the MVP workflow.
Right, the codebase generated by these can get huge, but maintenance can also be aided by AI tools like GitIngest[1], GitPodcast[1] etc. all helping you understand any new codebase easily or someone can query their doubts.
So, I wouldn't strike these kinds of tools yet. AFAIK, v0 already lets you connect github.
I’m using Lovable heavily for PM prototyping and it’s great. I think, if anything, current subscription may be too cheap! They’re probably want to get a huge mass of users now, eg they recently had a free usage weekend.
The comments on the Add Ons are spot on, I think:
“Lovable is creating lots of new software founders who will eventually spend lots of money on vendors. That money will flow, but Lovable currently captures zero of it.”
Having a Lovable App Store sounds like an excellent tool.
I think you must be the killer use case. As a programmer this is not good enough yet to warrant my time using it for production code (nor are its competitors)
However if I need to prototype for throwaway it would be ok.
These things right now compete with Figma and wire frames. Hopefully they lead ultimately to better UX in software.
As a product designer, I'm seriously looking at using Lovable for quick ideation and prototyping. Showing users a series of Figma screens can be nice, but virtually everybody responds better to an interactive prototype.
what most people assume:
myth (a) - software engineers mostly work on software for consumers reality (a) - software engineers mostly work on software for enterprises
myth (a) - it's just crud reality (a) - it's crud but with a bunch of business rules behind it that ai can't grasp
every other shiny 'saas' that's not the reality of the majority of software out there.
This analysis is very much on point. I'm building a product in this space (https://getmocha.com), and can share a few more insider insights:
- The churn from companies like lovable is indeed very high, and user frustration is high also.
- There are sub-niches available. Building internal tools is not the same as landing pages is not the same as saas. In the previous website builder market, different players (webflow, squarespace, wix) found and dominated a sub-niche
- The market is way bigger than anyone realizes. Today hundreds of millions for basically early adopters and highly tech-savvy users. This tech can and will go mainstream
- A huge issue with lovable, solved by others like mocha and replit, is the app backend. Lovable took a shortcut and partnered with supabase but that deal will not last. Supabase is losing big on their free tier (had to raise 200M to support it) and both want to capture the margin from the customer. There will be a reckoning.
The marketing is good. Especially on LinkedIn, for non technical people. But I am not convinced. Lovable is a nice Website or App builder. Nothing for professionals, unless they want to build an prototype. Even building MVPs is nearly impossible. It's like v0 from Vercel or anything you can do with other Agents like Claude or Co-Pilot. Lovable is promising a bit to much for my taste.
Oh great, another article on this company. I swear I keep being bombarded left and right with content desperately telling me hyperbolic things like "Lovable is the last piece of software humanity will ever build".
What this article touches on is why I focused only on the serverless part with my project https://saasufy.com/ and why didn't implement any frontend UI for it (besides the control panel which is only concerned with backend concepts like schema definitions, auth, access control...). Now Claude is allowing generation and hosting of UI apps directly from their chat interface so it would be reinventing the wheel to build a UI.
AI companies are going to be working really hard to ensure that users do not bypass their chat interface because AI APIs don't provide much lock-in factor for them.
just have a question, for a young company like this, isn't mrr better than arr? or do they have that many yearly subscription? cuz u always subscribe and cancel different providers
I recently used lovable to create the scaffolding for an app. It did a great job, far better than I expected.
However, it also squishes everything into one JS file, making it unwieldy for anything moderately complex. After I fell off the happy path (integrating onnx was basically impossible), I had to spend a fair amount of time reworking it.
I’m probably not the target audience though. And I got the end result faster than I would’ve, and it’s better looking.
Cybersecurity will be booming in 2026, trust me bro :)
I fully support vibe-coding in corporate env., plese bring more :D
Bug bounty programs will blossom like hell!!
These apps will look dated in a few years, don’t waste your time. You’re just having fun playing around making old shit that could have made you a lot of money 10 years ago but is now just a weekend project. That’s the way things go in tech. Starry-eyed dreamers will let their imagination run wild, but they’re the laggards, the industry is already thinking ahead.
The next generation of apps isn’t going to look like the previous gen. No beautiful UIs and fancy CSS. No UI at all.
Instead, everyone will have some kind of platform like Cursor, but instead of just coding, it’s for everything.
Subscribing to new services for your AI to use will be the equivalent of downloading apps from an AppStore to your phone.
Then you can just say things like “fuck this person! AI, give me an OSINT profile of this Redditor!” and since your AI has the osint app it compiles the info instantly and says “here, damn”. No need to open an app, just straight info into your brain as quickly as possible.
AI has clearly made us tired of googling endlessly for info on random websites, so why are we still opening up apps to do various tasks? Because we want to see pretty interfaces? Get real. It’s time for the UNIX philosophy to go mainstream. Start thinking of how your product can minimize time to satisfaction, graphical interfaces get in the way of satisfaction.
The only problem is we currently don’t have a single unifying platform like an iPhone or something to consolidate a user base, but it will come. Start planning for that day so you can launch new services on day 1. It will be a gold rush.
And in the end, a lot of people will find they will struggle with coming up with good AI app ideas, because 80% of their idea was just putting a pretty interface in front of something complex. That’s how you know it was mostly a bad idea.
With that mindset you’d have skipped getting a PC in the 90s because the Internet in your pocket is gonna happen any day now.
For example let’s say the agent you describe can relieve people of manual data extraction from websites. Such an agent would be sheer utter magic for a friend of mine. Part of their role involves logging in to get data on employees from 4-5 different systems, compiling a spreadsheet of the data, turning the spreadsheet into a report, and sending it to internal folks. It’d be great to have an agentic tool that can drive the data extraction piece and automate their entire process with just a prompt - but today’s tech works just fine! A Playwright script, some carefully stored credentials, and a workflow automation are enough to get the job done - even if they require constant tweaking and monitoring.
Today’s tech is never the ideal version you can imagine, but it can still be used to solve important problems. Better to enjoy what is happening now even if you know it’s temporary.
I think it is a matter of scale.
I think you are right if we scale to a type of super intelligence in all domains.
Otherwise, I can't know everything so a human will be able to build a better tool with AI that I will use for domains I have no clue about. Just like it has always been without AI.
You probably should spend less time on Reddit though if that is the example that comes to mind.
Love this concept - LLMs as the new "API layer" to everything. Don't design a frontend because the user can generate one on the fly or use their own styling or pick a common "theme".
Would you need a new platform, or just a screen and a microphone?
Perhaps me just stupid and do prompts bad, but I can't make Lovable come up with anything really differentiated as a design. I'm curious if folks have tips on how to use it well as I really love the idea behind it.
The kind of things I see mostly produced by these tools are landing pages, example dashboards and simple utilities like calculators and other simple stuff. There is certainly a space for these but nothing ground breaking that was not possible before with other beginner-friendly tools. The only difference is now that there is more freedom because LLMs can do more with less constraints.
I wonder what will happen after the honeymoon is over - after people realise that software development is not about writing new exciting code but maintaining things that should have been replaced years ago that are now too important because other people depend on it.
> I remember we were building a micro-app like that and it took at least a month, now it takes 3 minutes.
...please, statements like this have the power to invalidate the rest of the commentary. in 3 minutes you can complete a few prompts not nearly enough to write a piece of software the allegedly takes 3 months to do.
Is there really a reason why should I pay for vibe coding apps like this when I can vibe code for free and unlimited with Google's Gemini?
Lovable should allow max flexibility to its users, allow them to monetize
Lovable should be in the money flow, allow their users to monetize
I work for a very small startup. Our CTO heavily uses lovable for our internal tools. Think dashboards, user management ... A somewhat standard UI over CRUD operations.
In previous roles, we either used some SaaS platform and would end up designing features based on the limitations of the tools, or we'd spin up a team to roll our own tailored solution. (or, God forbid, use Oracle and pay consultants a small fortune to do it for us).
With lovable, our CTO can validate assumptions and iterate on their own. Even if the code was absolutely garbage and we deleted all of it, this alone saves us a ton of man hours per feature. There's an entire lossy communication loop that's been removed.
Now, the code is only ok. We generate API clients from openapi definitions but it will struggle to properly orchestrate them. It will absolutely not have sane defaults anywhere, and will abuse the "any" type.
You still need a human in the loop, but my back of the napkin calculation is we'd have to hire two full time developers to do the work it's been doing for us.
Why does your CTO not use cursor or whatever other code IDE tools to build on your own standard internal stack?
At least that would allow them to handoff to other members of the team.
I'm pretty sure the person who wrote this has never run pricing research for a brand. Short answer, they can ignore Gabor-Granger because their cost base is so low compared to their revenue, so they'd be looking at Van Westendorp's Price Sensitivity Meter to set a benchmark for where the pricing probably lands, and a conjoint study to understand the value of different elements for segmenting different versions of the product at different price levels.
Obviously positioning, who they're positioning against, how they communicate that, the level to which they're known amongst the market etc all feed in to this, but that'd be a decent starter for ten.
This is an overly simplistic version of where to go with pricing for a brand like this, but that's where I'd begin with creating pricing for them.
Good product placement of Lago :)
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