> An engineer with AI tool can now outbuild a 100-person engineering team.
What an insane statement. If the tooling improves that much the team of 100 will also improve. A worker with a shovel only outperforms the other workers if they’re still digging with sticks.
That sets aside the assumption that a few years from now we’ll see any material improvement at all. More likely we’ll see more wasted hype on some new revolution.
Yeah I really don’t get why people keep hyping AI like this. It really doesn’t make things go that much faster. At best you’re able to generate prototypes more quickly + get better autocomplete. Nothing particularly revolutionary there.
Anyone claiming a generalized 100x, 10x, or even 2x productivity gain is either delusional or trying to sell you something. Possibly both.
The companies saying they are reducing the size of their workforce because of gains they’re getting from AI are probably just telling investors what they want to hear while cutting costs for the same reason they always have.
I felt this way until Claude Code. It works much, much better in large codebases than anything else I've tried. It implements smaller features, including ones with FE + API changes and tests for each, pretty well. I'm going to try cloning our main repo multiple times to get it working on multiple branches at once.
>Anyone claiming a generalized 100x, 10x, or even 2x productivity gain is either delusional or trying to sell you something
I don't understand how anyone who spends a couple hours or more per day coding new functionality couldn't at least double their productivity with LLMs, unless their organisation prohibits LLM usage. Even just limiting the LLM to writing unit tests would still save that much time.
The thing is, tab complete using LLMs is really great. But I still read it, then press tab, then press enter, then type a few chars, then wait.
Sometimes I get 1 good line from that. Sometimes I get 30. Usually I get 10 bad lines and have to type a bit more to coax out 8 good ones.
It just looks faster but typing was NEVER the bottleneck for coding.
Where it really flies, though, is building tooling around a well known API. FML if I ever have to write AWS CDK or AWS API calls without an LLM again. You're looking at ages of reading through really bad docs to get it going.
For that, which is a 1% task of convenience for most jobs, I can use most LLM output verbatim. But that's like I said less than 1% of the job, and only then when the core software is done.
Did you notice how much better things are today (eg Claude Sonnet 3.7) than they were 1 year ago? Don’t you expect things will not improve in the next year? Even R1, a public weights model, can add huge value when left to code in a loop.
Hm, I’m a CDK pro (4y of full time experience). I used all LLMs, except latest Claude model. All were bad in my estimation and just got in the way. I don’t use them for CDK code anymore.
Yeah! That's exactly the thing. It's passable for novices and bad for experts. But I don't need expert level CDK I need an instance to start up. Hate it or love it that's all I need.
The bottleneck is not putting code on the hard drive, or turning my thoughts into code — the productivity bottleneck is thinking and frankly no LLM is thinking better than an average developer.
Author of the post here. We’re a 4-member team running 4 products with 4,500+ paying customers. No sales team, no infrastructure team - just freemium and serverless computing (Firebase) doing the heavy lifting. I’ve been a developer and founder for 20+ years, and I know that 15 years ago, each product would’ve required at least a 30-member team to build, maintain, and sell. This isn’t hypothetical, it already happened to us.
Most of this leverage comes from internet distribution (freemium) and cloud computing (serverless), not AI. (Though we do use AI to answer support questions—since my cofounder is the only one handling them.) Now with AI, I argue that a solo engineer could outbuild a 100-member team in a couple of years. Given how much productivity has already increased, why is that an insane claim?
> How do you determine what features to build or the next product to develop?
My co-founder handles support, so he decides what to build next based on customer discussions. If a problem is big enough for a specific segment, we turn it into a separate product.
> What tools are you displacing (e.g., Excel)?
Most SMBs prefer to stay with Google Forms/Sheets rather than switching to a full-fledged CRM like HubSpot. But embedding Google Forms in their website affects their branding. We beautify and enhance Forms into a CRM, so they don’t have to migrate. I wrote about it here: https://manidoraisamy.com/developer-forever/post/can-you-use...
They clearly don't mean one person with AI now vs. 100 people with AI now. They're comparing one person with AI now to 100 people without AI before.
Regardless, one person still costs 1/100 as much as 100 people. Let's say each of the 100 adopts AI and multiplies their productivity by 100. Does their company need its total engineering productivity multiplied by 100? They might settle for let's say 3X and save 97% of the costs by firing 97 people.
(I tend to ignore most of the hype and I'm dubious about that 100X figure, but I'm taking it at face value here for illustrative purposes.)
OP here. While this logic holds, large companies don’t move fast.
In 2018, I wrote about scaling big while staying small using serverless computing (https://cloud.google.com/blog/products/gcp/scale-big-while-s...). But by 2020, instead of leaner teams, we saw more hiring and even bigger orgs—ironically, even at companies selling serverless services.
Why? Because incentives at large companies favor empire-building (prestige from managing big teams) over efficiency. I expect the same inertia with AI: solo devs will fully embrace AI, serverless, and freemium to race ahead, while big teams will adopt AI at a crawl.
Even if that’s what they mean (and I agree, that’s plausible, though not obvious) it’s still an asinine statement in the context of their broader thesis: advancements in generative AI are going to power the rise of the solopreneur. In absolute terms, an individual developer may be more productive in 3 years than they are today, but in relative terms, they will still be underpowered when compared to large teams building complex software. It only makes sense if we also assume the consumer and quality bar of today as well — and I don’t think LLMs are expected to crack time travel.
There will still be successful solopreneurs, just as there are today, but the idea that tooling-based productivity gains for individual developers are going to drive a power shift towards solo development and away from team-based companies is stupid.
That's a good point, and there's probably a sweet spot somewhere between "a few" and Dunbar's number, that represents the typically-most-efficient team size going forward.
Great. So a team of 100 with LLMs is still faster than a team of 100 without even if they spend the same amount of time on synchronization? Or did I miss something here?
well if they have more slop to get through, they'll spend even more time going over the more slop to find the useful bits. imagine 97 of them believe the machine upfront and you have to convince them that the code is shit. shudders
If 1 person can use an excavator/AI, then a 100 person crew can use 100 excavators/AIs. Capabilities have increased for everyone, not just for 1 man operations.
Have you seen how big excavators are physically? There are functional limits to certain tools. I can see how software could become a hot mess if AI tools aren’t calibrated or the human element makes a mess of combining disparate parts.
In this scenario, it's like the excavators are pocket sized, and cheap. As cheap as the shovel. So there is no reason for the entire digging crew not to have one each
In this analogy, how many ditches do you think need to be dug? Each company only has a limited number of ditches they need done. The unnecessary human diggers will be let go.
I didn't make the original analogy. I was just explaining part of the point.
I disagree with the number 100. It is not a reasonable number with respect to current AI capabilities.
If the cost of digging ditches goes down, companies will be apt to dig more ditches. I've seen many projects worth $100k-$500k but they weren't pursued because the cost in salaries was higher.
I don't think companies are generally well run to let go of unnecessary people efficiently. At least one place I've worked at had, by my estimates, $100m salary of unnecessary people employed. It didn't matter, the business has revenues of $100b yearly, so it's a drop in the bucket.
In my experience, team efficiency does not improve linearly with head count. A 100-person team may be 2 or 3 times more productive than a 10-person team. Collaboration efforts (process, bureaucracy, calls, meetings, mails, chats) increase exponentially with larger teams. AI can help with coding but not much with this collaboration process, at least not yet. Now, AI can make a small team much more productive because their collaboration overhead stays the same. But AI cannot help with a 100 person team because their collective collaboration overhead cannot be solved by AI. I guess the trend will move towards smaller sized teams that can effectively use AI.
Depends on if you think AI is more like a shovel or an excavator. The article to me implies a shovel: a tool used by one person to increase individual productivity. An excavator is not run by a single worker — it’s run by a team. If AI assisted coding is an excavator, a solo developer won’t outperform a 100 person dev team, because they won’t be able to operate the AI tooling efficiently or effectively.
but it takes months for a team of 100 to o do anything, let alone make the decision to do so. Right now there is a sort of time arbitrage opportunity for single developers
You need to retool the corporation, the way the company is organized, and retrain the workforce for the new way building.
In addition you have to pull that of, while still keep the light on, for what you already have.
It will be much easier for someone starting from scratch.
I do think many corporations will fail for this reason. But some will successfully adapt, and others will start fresh and have no baggage.
I do think it will be easier for very small organizations to compete than it was previously - which is great - but let's not fool ourselves that big companies won't maintain some competitive advantages.
>First, the internet killed the need for sales teams (distribution moved online).
Sales and marketing is still 90% of the game. The solopreneur still doesn’t have an easy way to get paying customers. Either you sell SaaS into a network of business contacts, or else you try to play the influencer / reddit / SEO game to get early traction.
To add to this, while this approach may work for long tail, transactional sales with low ACVs, and work very well, it will not work for larger strategic/enterprise deals.
Sales teams are alive and well in this area. I’ve been in GTM for nearly my entire career. I have yet to see a company closing 6+ figure deals on a credit card and without a relationship.
As a career proposal specialist, I’m in complete agreement with you. Large deals take significant pursuit and documentation…at the Fortune level enterprise or for regional / state-level agreements in the US, it’s a highly competitive process. I’ve seen this first hand in SaaS sales for municipal clients and it’s simply a cost of doing business for certain markets. AI can’t be trusted with proposal responses that may be catastrophic in the contract phase.
Relationship may be secondary in a large SaaS company (you may see new key account once a year or two), but 6 figures mean paying by invoice, custom discounts and there will be inevitably some KYC process. CEO or CCO can do it and in boutique business they do it, but you probably cannot have lots of customers AND such deals at the same time.
A lot of bold statements unsupported by data or even sufficiently deep understanding of the mentioned things.
Like for example this:
> Formfacade is a CRM that competes with HubSpot
It is not a CRM system and it is far from addressing the needs of users of real CRMs. Of course, an early stage startup or a business with less than 1000 customers can handle leads in Google Forms. But that is a lot to handle.
AI does not replace software engineering. It can enhance productivity on certain types of tasks, but AI is doing terrible job on something that mildly deviates from SO answers. It cannot build something like CRM or anything with rich domain.
It is absolutely possible to go solo today, but it’s not because of AI. Tech founder can just write a lot of good code. Business founder won’t get past outsourced no-code solution.
Author of the post here. This is a misunderstanding of CRM given how customer relationships have evolved over the last 20 years. Salesforce didn’t copy Siebel - it moved sales tracking to the cloud. HubSpot didn’t copy Salesforce - it focused on inbound leads.
We’re not trying to build every feature of a traditional CRM. We’re focusing on Google Forms as CRM for SMBs because they already use Forms + Sheets to manage leads. Wrote another post explaining how we use it as a CRM - https://manidoraisamy.com/developer-forever/post/can-you-use...
I'm not sure how I feel about the take on "disappearing pillars". I think that knowledge and expertise in the different "pillars" the author describes has become easier to access, reducing the moat around the individual pillars and allowing greater overlap between professions. So while you might not need a "sales team", you do need "sales knowledge". Cloud solutions are amazing until they are not and you need "infra knowledge" to understand where you are going wrong and to evaluate potential solutions.
I would argue that at a given size, scale, and growth you would find yourself looping back to the "original pillars".
The example of Neartail[1] competing with Shopify is a prime example of this. Shopify has a large market cap, shareholders demanding profits, a large quantity of paying customers. Neartail has none of these, it may have paying customers and it may have some potential in the future but it is currently all within the sphere of control of a few individuals.
Obviously a lot of what I'm saying is self-inflicted, you don't _have_ to grow endlessly but if you _do_ you need many decision makers and domain knowledge simply starts to reach limits for individuals (even when using AI).
I've been validating this sentiment almost every day.
I left my job last year, after over a decade leading design and UX for iOS at Google, to pursue building a bootstrapped solopreneur startup, and the speed at which I've been able to build things out has been wild.
There are entire domains that would have taken weeks or months for me to learn the ins-and-outs of the tech, that Claude has been able to knock out in a matter of minutes. It's like I have two full time junior engineers working with me at all times (with a similar amount of coaching + guidance required), and for $20/month. These are gains of easily 2x-10x productivity and I already consider myself to be fairly productive as a design engineer.
Keep in mind, switching from Google to startup without AI should get you a 2-10x productivity gain just from lack of bureaucracy alone. But I do agree LLMs are at their best when teaching you subjects you have adjacent knowledge in.
I can buy it for the low end of your range. I was able to learn Angular during my time at Google super quickly thanks to GPT4 (before they banned it). I recall feeling it doubled my productivity in those early months.
"For example, the future of CRM isn’t just software—it’s software + sales team. Startups that don’t want to hire salespeople will eagerly adopt AI-driven CRMs that automate outreach, and follow-ups."
I'm not involved in either side of this part of the business. Doesn't this read as "smarter spam"? Does that result in long-term customers?
Perhaps I'm just not aware of just how down-and-dirty the top of the funnel is?
My emotional response is: If you don't value _my_ time (as the customer), why should I consider your product?
As software engineer jobs get culled (citing the excuse of AI), I strongly urge experienced senior software engineers to flip the game, becoming AI-assisted solopreneurs instead. If you're sufficiently intelligent, you don't even need VC money to bootstrap it. Here are some income models:
Service:
1. pay-by-use
2. subscription
Software:
1. open-source with paid new feature development
2. sales (on app stores)
Physical products:
1: Resell from China in West
2. Develop new from China/anywhere and sell globally. Let big sites like Amazon and Walmart do the marketing and fulfillment.
Payment or funding models have never been the problem. Those are menus you choose from, not tricky parts you have to come up with from scratch. Thinking of a single product idea I feel has enough chance to succeed to be worth working on, is the entire problem.
After 25 years of never once thinking of one, I doubt that's going to change.
Seriously? Payment and funding are what matter when you are self-bootstrapped, wanting to make an income, and not intending to sell your company (to someone who will likely just destroy it). If instead you want VCs to own you, or intend to not turn a profit, then payment and funding don't matter.
This is crazy how fast you can build things today. But you need to understand what AI is spitting out and make decisions what to include, what to reject and how to ask it to create things. Ironically, this is almost like you would talk to your employees to make things for you.
Yes, you must be able to recognize the right answers and separate them from the hallucinations and crappy engineering.
Maybe it’ll get to a point where even people who don’t have a clue can click Apply and never have to worry, but it’s not quite there yet.
If it does get there, I’ll find another occupation; it’s not like my job ever defined me as a person.
The main problem with this is that presumably a 100-person team with AI will still outperform the individual with AI. The benefits will be adopted by organizations at every level.
However I actually think the argument works for things that aren’t actually businesses and don’t really have competition.
If for example you want to build an online encyclopedia about an obscure niche topic, or dialogue for an indie game, or do any number of other otherwise tedious and resource -heavy tasks, you can now do that with AI tools. This is what excites me the most about AI - not the prospect of outcompeting another business, but of making giant creative projects dramatically more feasible.
>While the giants are trapped in their own complexity, nimble teams can build and launch AI-native solutions that directly challenge established players. Target a bloated SaaS vertical, rebuild it from the ground up with AI at its core, and position it as the next-generation alternative.
Is there _anyone_ that would jump ship to yet another SaaS just because it's "AI enabled"? Obviously it's all the rage for VCs right now, but I can't imagine switching to some other product simply because it has AI and mine doesn't.
Just want I want: a SaaS vendor with even less customer service and that’s literally dependent on one single guy staying alive and motivated to work, or the entire service just gradually shuts down.
There’s a product our marketing and copy writing teams use to write content and manage content and they were using the same tool successfully for years and recently switched to a different one because it had really good copy re-write AI and also caught grammatical errors really well.
I forgot the name of the product in question but this is one example I can think of
Completely anecdotal I realize, but my experience so far has been that people who aren't in some way involved with AI/tech in general are mostly indifferent, with a vocal portion that is actively against it. Not a single one of my non-tech friends care beyond using ChatGPT to be lazy writing emails or whatever. If it all went away tomorrow I doubt any of them would care in the slightest either.
I have however been getting some friends asking me how to disable all the AI crap in Windows and Google. It could very well just be my specific circle, but I think people are slowly starting to push back against all the AI enshittification to the great chagrin of all the VCs hyping it up
If anything, I know people contemplated the opposite (i.e., finding a less hype-driven job)
I think it's anyway not a strong reason to leave or stay, at this point. It's still "yet another technology", and I'd be surprised if it turned out to influence any decision in this regard.
Mentioning AI as a feature is a turnoff for customers: https://news.ycombinator.com/item?id=41126685 Annectodally, everyone I know who is not in the industry is somewhere on the spectrum of indifference to revulsion, literally no one who is not a technologist or an investor has a positive opinion of AI.
A sales team is even more important! Actual humans to talk to you—this is the future! The demand for non-automated, human tasks will skyrocket. Our society will shift back to being human-centric, just like before any automation.
I think they presented it wrong for impact. If instead of "killed" and "eliminated" they were saying that the internet made it possible to proceed without a sales team and that cloud computing made it possible to not need a bare metal IT team, it makes a little more sense. That is to say, it's not going to be the most effective way, but it went from impossible to at least viable. Similar to music recording. It used to be you needed competent instrumentalists and access to a commercial recording studio. Now you can do it all at home on a laptop and it is viable, people are successfully doing it. But in large part the most successful music is still done using the same professionals that existed before.
It's like someone took the most extreme hype for a bunch of past shifts, all of which have already played out so we know they definitely did not work out that way, as if all the hype described what had actually happened, then also took the same hype for "AI" and assumed all that's going to be, or is, true, too.
There is technology that can greatly benefit solopreneurs, but it isn’t AI. It’s just an evolution of the same tech that has been a huge benefit to early stage projects for awhile now. Knowing what you’re doing with highly productive tools like Rails or Laravel or whatever your preference is going to have a far greater impact than some LLM will.
The article starts out interesting:
> But DeepSeek didn’t just build another AI model. They wrote their own parallel file system (3FS) to optimize costs—something that would have been unthinkable for a company of their size. This was possible because AI helped write the file system.
I thought, hmm, now that’s interesting. But then the breathless leaps of faith comes quickly
> Now, imagine what will happen in a couple of years—AI will be writing code, optimizing infrastructure, and even debugging itself. An engineer with AI tool can now outbuild a 100-person engineering team.
> This kind of disruption was previously limited to narrow consumer products like WhatsApp, where a 20-member team built a product that led to a $19 billion exit. But now, the same thing is happening in business applications that requires breadth
Umm, not so fast, AI will not enable a couple of guys to write a robust production grade kernel in a couple of weeks or months, unless that kernel is simply a fork of Linux with some cosmetic tweaks. I always wonder, do the people making these sorts of pronouncements actually understand software? Have they built software of any significant size and depth?
And then:
> First, the internet killed the need for sales teams (distribution moved online).
Sales teams have not been killed simply because distribution has moved online, although kind of sales people you need, and what they do, has certainly changed.
The reason why VCs don't like solo founders is because VCs want the freedom and power to be able to kick out a founder. It is all the more reason for solopreneurs to detest VCs, to bootstrap their own thing instead.
There is institutional prejudice against "Solopreneurs". The notion is that if you are doing the business alone, then it must be something wrong with you. Like, why didn't you attract any co-founders? Why you don't have a team behind you that supports you etc. etc.
Basically they want to shoehorn outdated economic models onto emerging businesses and they way they operate.
This is fuelled by the rich, who inherited their wealth and have no talents on their own, just want to get shares in "cool" things and appear in circle jerk magazines how they spotted this little company and took them to the next level etc.
As solopreneur you are unlikely to get any grants and other government support too. There is always one question that shuts the conversation down: "What if you get hit by a bus?"
All of that mattered only for those that need much VC funding. With AI, the need for VC funding is minimized because you don't need employees anymore except for physical work. The key is in bootstrapping the solopreneurship by oneself.
I read it as “The DeepSeek team, though very small, accomplished what would have taken a much larger team before the introduction and adoption of genAI tools”
This just reads like a fluff piece to advertise their own products, and the conclusions in the summary are the kind of vague handwavey promises AI bros have been making for the past 3 years
> Take our own experience: Neartail competes with Shopify and Square, and it’s built by one person. Formfacade is a CRM that competes with HubSpot—built by one person.
Would like it better if claims like this were backed up by numbers.
I remember when social media was the hype at the start of web2, and a bunch of people came in saying everything would be social.
Then the same thing with cloud.
Big data.
Bitcoin.
VR.
Ethereum.
Web3.
NFTs.
I mean AI is cool and it helps with some stuff. And it's also not going to be this epic panacea where rogue coders turn into the best entrepreneur they can be. To throw out such takes is just short sighted hype.
AI does assist with developing an automated deployment pipeline.
AI also assists with the use of CPU-efficient programming languages, e.g. Rust, Zig, etc. where one doesn't need a cluster of workers for a trivial service, where a single instance can be sufficient.
The word "assists" is wonderfully vague there. And lol at the "cluster of workers for a trivial service", you seem to enjoy erecting men of straw to knock down.
What an insane statement. If the tooling improves that much the team of 100 will also improve. A worker with a shovel only outperforms the other workers if they’re still digging with sticks.
That sets aside the assumption that a few years from now we’ll see any material improvement at all. More likely we’ll see more wasted hype on some new revolution.