what must've happened is greylock told them "hey GPT Cyber, Cyber cyber cyber... do something!!!" and here we are
Email security is a problem, sure, east coast boomers click dumb shit all the time
Software factories don't exist is an easily falsifiable statement https://github.com/topics/software-factory
I feel this is probably coming and perhaps inevitable, but I fear for the poor employees this sort of thing will be tried out on first.
Also https://web.archive.org/web/20260725174355/https://marshallb...
My current project is created by one-shot prompts. That’s not some kind of parlor trick. It is the framework for creating and evolving the product.
Many people laugh it off as “unserious”. But as I said, I see this happening in my place of work where people are paid lots of money.
https://jaisenmathai.com/articles/sojourn-for-ios-was-45-one...
In the longer term, the downstream impact is massive commoditization of software and invalidation of most existing moats. Data moats are gone if you can simulate the data with AI. Even platform effects can be sidestepped if AI replaces one side of the platform.
In addition, while right now agile startups have the advantage, at some point the balance will start tilting towards whoever has the most tokens (OR perhaps durable moats will trump even near-infinite tokens; we will have to see). Startups have a limited time window to have whatever impact in the world they are hoping to have, or to build a moat that won't be disrupted by AI, but there are few of them left in the world.
The upside is that when there is a lot of commoditization, then the consumer benefits.
This is a hilarious premise if you work in a domain where it matters even a little bit whether the data is correct or not.
1. He’s talking about training new models and at one point, having data was valuable. Now synthetic data is being used to train models
2. Companies like SalesForce who’s moat is having all your customer data so you’ll be locked in. You could extract it but you’d have to clean it and then change it to your new schema. With LLMs, you can do that in minutes and even use SalesForces MCP or API to get all your data and leave.
It’s exactly why companies like Figma are gate keeping their MCP. They know that swapping their MCP with Paper’s or any new one is easy.
The moats are evaporating as we speak. Distribution is one of the smaller ones left, but the personal software trend might eat that too.
But to pull something from the post:
> If this is the right mental model, you should expect to see:
> An unusual amount of in-house harness building on both the build side and the sell side
Yup.
> Org structures and individual roles being reshaped around their place in the business harness
Not yet, this is the one I am most skeptical about because it's still way too easy for the harness-driven processes I've seen to go off the rails, so it's still very much human SME-driven. However, the number of butts in seats required is going down.
> AI-native startups beating incumbents in domains where the “moat” can be easily harness-ified
In most cases I've seen the "moat" is not easily harness-ified, and increasingly the money and energy seems to be going into getting to the starting line.
> All software a software company uses (on or tied to the core build or sell paths) needing to be headless so the outer harness can run it
Tech companies are definitely doing it, but I don't think this is actually realistic yet for companies whose core competence isn't software. But this feels like a matter of when, not if.
Because someone was so sick of expensive Adobe Photoshop they created their own vibe coded PhotoShop for $2000 worth of tokens and then selling it on for way cheaper. [0]
Some YouTuber got so sick of Adobe Premier they literally vibe coded their own full fledge video editor exactly to their needs with everything else that they don't need stripped out. [1]
I know of a case where a totally non technical person sitting in an south asian city wrote his own financial management software for his business in just three weeks. Vibe coded and now his daily driver tracking accounts, payables, receivables, contracts, parses PDFs from his inbox, populates forms and full workflow that HE needs for his specific commission/resale/distribution business.
So what this company is going to sell with that Harness? Or would it be selling just that Harness to other companies like those Rails bootstrap SaaS boilerplate businesses that used to charge $300 for that junk with lifetime update promise?
EDIT: Formatting
[0]. https://www.reddit.com/r/vibecoding/comments/1wpaies/my_vibe...
There are 40,000 McDonald’s franchisees who basically just put money into a coinop machine and the machine returns with exactly the food, drinks, restaurant decor, prices, etc that it wants them to sell.
Toyota’s production system coordinates what gets made and when, detects abnormalities and directs human attention toward problems and improvement. They explicitly eliminate the need for people to continuously watch machines, while preserving human judgment
The harness controls the AI input and output into an outcome that requires judgement.
The human part is that judgement. Not the decisions - we can pass that off but what is a 'good' thing?
Tomatoes in your fruit salad? Tomatoes are fruit. Olive oil in your engine? Lubricants are lubricants.
AI slop creates software and documents and websites very quickly. It passes the tests. It does the thing but can it be trusted? Consistent positive judgement calls create a track record and that creates trust.
This explains the anticipation about Jev.
Trust is now what sells to the highest bidder.
Being a platform for personal software is gonna be valuable, but it needs a lot of trust. (I have a nonprofit idea around this right now)
Btw, I think distribution might temporarily become less important (because with better AI you can actually pull so far ahead of competitors quality-wise and therefore succeed despite a distribution drawback), but long run it actually becomes more important because of AI persuasion and commodification? If you are the super app then, well, you are the super app
Every company can now apply the latest and greatest analysis. Data generation is where the cost is. It's where the time was spent, time that can never ever be retrieved at any cost.
AI won't solve biology, make a pathogenic virus, etc, without tons and tons of data, of both types we know and types we have not yet figured out how to generate.
Perhaps the area where AI has the most to help bio is in figuring out novel measurement technology. But it's not going to be able to reason or deep-net its way to figuring out systems for which we can't even measure the parts.
I agree this is a kind of data moat, but it's also arguably distinct enough to be its own thing.
I think current incentives definitely go against any efforts to build this. It's very hard to build this and be rewarded for it by, say, investors or your boss, because you can't really prove that your system is non-sloppy while your competitor's is (even if being non-sloppy is all that matters), because by definition your novel results are not verifiable or else the model labs will have already trained it into their model.
But the same is true for high-quality AI systems in general. In general, I think AI model advancements will make the systems easier and easier to build until some small guy accountable to no one but themselvs can build it, and then it will actually be built.
- capital, as money is scarce
- network effects, as human attention is scarce
- relationships, as human attention is scarce
- research talent, assuming there exists some field(s) that AI is unable to surpass the best researchers
- proprietary data and sensors, as systems of record and action are scarce (training data, on the other hand, can maybe we simulated, but I'm pretty bearish in general on the idea of fully simulated data)
BinRoo•50m ago
I couldn't have said this better myself. If you're not owning your harness, and you're not owning your model, then that leaves very little moat for any AI native company.