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TL;DR The "build vs. buy" equation has flipped. Businesses used to buy SaaS because it was cheaper than building their own. AI has changed that—building your own is now more affordable than ever. The discovery problem. AI recommendations default to well-established solutions. Think SEO is a long game? Try LLM SEO. Everyone worries about AI taking developer jobs, but what if AI wipes out the entire off-the-shelf software industry? The "Why Buy?" Problem Six months ago, we needed an AI-powered code review tool. We explored several options and ultimately "vibe-coded" our own GitHub Action—a simple Bash script that takes a git log, sends it to Claude via curl, and posts the results to Slack. Done. The best part? AI wrote the entire thing faster than it would take to sign up for a SaaS. How long until every company realizes they can do this? Need a simple "CRUD" CRM with JIRA-style tasks? Done. Need a mobile time-tracking app for remote employees? AI will spit out a React Native iOS build in minutes. Why pay for yet another SaaS when you can "vibe-code" something in a week? And mark my words, LLM providers are one step away from actually hosting the code they generate. Who needs to spawn an AWS server if you can just ask OpenAI to host the code it just wrote? - "Hey Siri! build me a Basecamp, but with green buttons, also register a domain, spawn a server and host it all there, charge this credit card when you're done" - "Absolutely, that'd be $1.17 per hour" The Discovery Problem AI doesn’t just make it easier to build software—it makes it harder for new SaaS products to get discovered. When you ask AI for recommendations, it defaults to the biggest names. And not just in SaaS, by the way, in open source too. Imagine launching a killer new JS framework today. AI coding assistants and tools like Cursor will just default to React anyway. And not even the latest version of it! In a recent tweet Adam Wathan, the creator of Tailwind, asked: "Has anyone migrated to Tailwind 4.0 yet?" The most popular response was "Nah! we're still waiting for LLMs to learn it." AI isn’t just "the next internet moment." It’s more like "the social network moment." Echo chambers get louder, big names get bigger, and smaller ones disappear into the noise. What Can SaaS Companies Do? 1. Become an Industry Standard Or at least a "go-to" product in a niche. If your app becomes something people mention on their CVs or job descriptions, you win. Examples: Slack. HubSpot. Salesforce etc. A salesperson moving to a new company simply expects Salesforce to be there. That kind of lock-in ensures survival. 2. Build Moats: Infrastructure & Vendor Lock-In SaaS products that are just CRUD apps will die. The ones that survive will own infrastructure or at least some part of it. Instead of building another AI voice assistant, create one with built-in VoIP and provide landline numbers to customers. Examples: Transistor.fm – Not just a SaaS, but also a podcast hosting and publishing pipeline. Postmark (or any transactional email service really) – yes, AI can code an email-sending app, but it can't get you a 10-year old high-reputation sender IP address trusted by Gmail and Outlook. SignWell, SavvyCal and similar "inter-business" file-sharing, communication & escrow apps that own the communication part (and frankly, are literally easier to use than vibe-code your own). But prepare for tthousands of clones. Which SaaS Will Die First? Side-project-scale, "one simple tool" SaaS products that used to be easy wins—form builders, schedulers, basic dashboards, simple workflow apps—those days are over. If AI can generate it in an afternoon, no one is paying a subscription for it. Oh, and "no code" is toasted too. The SaaS graveyard is about to get a lot more crowded. I give it 4 years. Software consulting is making a comeback though. Someone has to clean up the vibe-coded chaos.
TL;DR The "build vs. buy" equation has flipped. Businesses used to buy SaaS because it was cheaper than building their own. AI has changed that—building your own is now more affordable than ever. The discovery problem. AI recommendations default to well-established solutions. Think SEO is a long game? Try LLM SEO. Everyone worries about AI taking developer jobs, but what if AI wipes out the entire off-the-shelf software industry? The "Why Buy?" Problem Six months ago, we needed an AI-powered code review tool. We explored several options, tested them all, and ultimately "vibe-coded" our own GitHub Action—a simple Bash script that takes a git log, sends it to Claude via curl, and posts the results to Slack. Done. The best part? AI wrote the entire thing—faster than it took to sign up for another SaaS. How long until every company realizes they can do this? Need a simple CRM with JIRA-style tasks? Done. Need a mobile time-tracking app for remote employees? AI will spit out a React Native iOS build in minutes. Why pay for yet another SaaS when you can "vibe-code" something in a week? The Discovery Problem AI doesn’t just make it easier to build software—it makes it harder for new SaaS products to get discovered. When you ask AI for recommendations, it defaults to the biggest names. Here’s an open-source analogy: imagine launching a game-changing JS framework today. AI coding assistants and tools like Cursor will still default to React. And not even the latest version! Adam Wathan recently asked on Twitter, "Has anyone migrated to Tailwind 4.0 yet?" The most popular response was "Nah! we're still waiting for LLMs to learn it." AI isn’t just "the next internet moment." It’s more like "the social network moment." Echo chambers get louder, big names get bigger, and smaller ones disappear into the noise. What Can SaaS Companies Do? 1. Become an Industry Standard Or at least a "go-to" product in a niche. If your app becomes something people mention on their CVs or job descriptions, you win. Examples: Slack. HubSpot. Salesforce etc. A salesperson moving to a new company simply expects Salesforce to be there. That kind of lock-in ensures survival. 2. Build Moats: Infrastructure & Vendor Lock-In SaaS products that are just CRUD apps will die. The ones that survive will own infrastructure. Examples: Transistor.fm – Not just a SaaS, but also a podcast hosting and distribution pipeline. Postmark (or any transactional email service really) – AI can code an email-sending app, but it can't get you a 10-year old high-reputation sender IP address trusted by Gmail and Outlook. SignWell and similar B2B file-sharing apps (literally easier to use then code your own). Don't just build another CRUD sales CRM, build a CRM with an inbound VoIP number – because AI can’t replace telco infrastructure (yet). Which SaaS Will Die First? Side-project-scale, "one simple tool" SaaS products that used to be easy wins—Calendly replacements, form builders, schedulers, basic dashboards, simple workflow apps—those days are over. If AI can generate it in an afternoon, no one is paying a subscription for it. Oh, and "no code" is toasted too. The SaaS graveyard is about to get a lot more crowded. I give it 4 years. Software consulting is making a comeback though. Someone has to clean up the vibe-coded chaos.
I mean, it is! But the whole story about the stock market reacting to the news about DeepSeek V3 and R1 is a fine example of the knee-jerk nature of mass consciousness in the era of clickbait economics. Briefly, by points: No, DeepSeek isn’t “head and shoulders above” every other model. The results vary across benchmarks, but on average, GPT-4o and Gemini-2 are better. You can see this on ChatBot Arena, for example (Reddit thread). Even in the results published by DeepSeek’s authors themselves (benchmark graph), you can see that in several tests, the model lags behind GPT-4o from May 2024—which, mind you, is currently ranked 16th on ChatBot Arena. No, training DeepSeek didn’t cost $6 million, “100 times less than GPT-4.” The $6 million figure refers only to the final training run of the published model. It doesn’t include any prior experiments, earlier versions, or R&D costs. This is just the raw computational cost of that final training run. And guess what? That figure is pretty much in line with models of the same class. No, Nvidia did not deserve this hit Not that we’re shedding tears for them — they could use a push to lower hardware prices. And let's not forget that DeepSeek was still trained on Nvidia’s own hardware. And no, their GPUs aren’t suddenly obsolete. DeepSeek’s computational budget is fairly standard for training, and inference for such a massive model (reminder: it’s an MoE with 671 billion parameters, 37 billion of which are active per token generation) requires a ton of hardware. Inference costs are roughly on par with a 70B dense model. Naturally, they’ll scale this success by throwing even more hardware at it and making the model bigger. Not to mention that Deepseek makes LLMs more accessible for the on-prem customers. Which means smaller businesses will buy more GPU's, which is still good for NVDA, am I right? Does this mean the model is bad? No, the model is very, VERY good. It outperforms the vast majority of open-source models, which is fantastic. DeepSeek used 8-bit floating point numbers (FP8) throughout the entire training process. This sacrifices some of that precision to save memory and boost performance. Additionally, they employed a multi-token prediction system and innovative GPU clustering/connectivity techniques. These are clever and practical engineering choices that undoubtedly contributed to their success. In the end, though, stocks will recover, ideas will spread, models will get better, and progress will march on (hopefully).
After years of working with the "big" Visual Studio, I've had enough. It's buggy, slow, and frustrating, and I've decided to make the switch to Visual Studio Code. While as a C# developer I'm still unsure if I can replicate every aspect of my workflow in VS Code, I'm willing to give it a shot—and so far, I'm really impressed. 1. Performance Visual Studio 2022 performance has been a constant issue. It's sluggish and feels increasingly bloated with every new update. It's like watching paint dry every time I open a project. In contrast, Visual Studio Code feels lightweight and incredibly fast. The first time I opened my large project in VS Code, I was shocked — it loaded in lees than a second, literally, even with extensions like "C#" and "C# Dev Kit" installed. 2. Better Developer Experience Running dotnet watch run in VS Code's terminal has been a revelation. It's fast, responsive, and actually works consistently. Visual Studio's "hot reload" feature, on the other hand, has been a constant source of frustration for me. Half the time it doesn't work, and I'm left restarting debugging sessions over and over again. I can't tell you how many hours I've lost to that unreliable feature. 3. Fewer Bugs, Less Frustration The minor editor bugs in Visual Studio have been endless and exhausting. I remember one particularly infuriating bug where syntax highlighting would break in Razor and .cshtml files whenever I used certain HTML tags or even just adjusted the indentation. It drove me up the wall! Not to mention the bizarre issues with JavaScript formatting that never seemed to get fixed. Since switching to VS Code, I've encountered far fewer bugs. It just feels like an environment that respects my time and sanity. 4. A Thriving Ecosystem The VS Code extension ecosystem is alive and thriving. Need Tailwind CSS IntelliSense? There's an extension for that, and it works beautifully. Want to visualize your Git history for a particular line (better version of git-blame)? The Git History extension has got you covered. In "big" Visual Studio, I'd report issues through the "feedback hub" and wait months — or even years — for a response. With VS Code, the community is constantly contributing new tools and improvements. It's energizing (and sometimes exhausting) to be part of such an active ecosystem. 5. Cross-Platform Flexibility One of the biggest advantages I've found with Visual Studio Code is its true cross-platform support. Whether I'm on my Windows PC gaming rig at home or my MacBook while traveling, VS Code runs smoothly and keeps my workflow consistent. Visual Studio's limited macOS version just doesn't cut it for me. Being able to switch between machines without missing a beat has been a game-changer. I have to admit, I was skeptical at first. I've always had a bit of a grudge against Electron-based apps — they've often felt sluggish and bloated. But VS Code has completely changed my perspective. It's fast, responsive, and flexible enough to let me build the development environment that works best for me. Switching to VS Code has rekindled my passion for coding; it reminds me why I fell in love with development in the first place. While Visual Studio will always have its strengths, I need a tool that evolves with me—not one that holds me back.
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In my previous post, I advocate turning against the unproductive. Whenever you decide to turn against a group, it’s very important to prevent purity spirals. There needs to be a bright line that doesn’t move. Here is that line. You should be, on net, producing more than you are consuming. You shouldn’t feel bad if you are producing less than you could be. But at the end of your life, total it all up. You should have produced more than you consumed. We used to make shit in this country, build shit. It needs to stop. I have to believe that the average person is net positive, because if they aren’t, we’re already too far gone, and any prospect of a democracy is over. But if we aren’t too far gone, we have to stop the hemorrhaging. The unproductive rich are in cahoots with the unproductive poor to take from you. And it’s really the unproductive rich that are the problem. They loudly frame helping the unproductive as a moral issue for helping the poor because they know deep down they are unproductive losers. But they aren’t beyond saving. They just need to make different choices. This cultural change starts with you. Private equity, market manipulators, real estate, lawyers, lobbyists. This is no longer okay. You know the type of person I’m talking about. Let’s elevate farmers, engineers, manufacturing, miners, construction, food prep, delivery, operations. Jobs that produce value that you can point to. There’s a role for everyone in society. From productive billionaires to the fry cook at McDonalds. They are both good people. But negative sum jobs need to no longer be socially okay. The days of living off the work of everyone else are over. We live in a society. You have to produce more than you consume.
<![CDATA[I'm exploring another corner of the Interlisp ecosystem and history: the Interlisp-10 implementation for DEC PDP-10 mainframes, a 1970s character based environment that predated the graphical Interlisp-D system. I approached this corner when I set out to learn and experiment with a tool I initially checked out only superficially, the TTY editor. This command line structure editor for Lisp code and expressions was the only one of Interlisp-10. The oldest of the Interlisp editors, it came before graphical interfaces and SEdit. On Medley Interlisp the TTY editor is still useful for specialized tasks. For example, its extensive set of commands with macro support is effectively a little language for batch editing and list structure manipulation. Think Unix sed for s-exps. The language even provides the variable EDITMACROS (wink wink). Evaluating (PRINTDEF EDITMACROS) gives a flavor for the language. For an experience closer to 1970s Interlisp I'm using the editor in its original environment, Interlisp-10 on TWENEX. SDF provides a publicly accessible TWENEX system running on a PDP-10 setup. With the product name TOPS-20, TWENEX was a DEC operating system for DECSYSTEM-20/PDP-10 mainframes derived from TENEX originally developed by BBN. SDF's TWENEX system comes with Interlisp-10 and other languages. This is Interlisp-10 in a TWENEX session accessed from my Linux box: A screenshot of a Linux terminal showing Interlisp-10 running under TWENEX in a SSH session. Creating a TWENEX account is straightforward but I didn't receive the initial password via email as expected. After reporting this to the twenex-l mailing list I was soon emailed the password which I changed with the TWENEX command CHANGE DIRECTORY PASSWORD. Interacting with TWENEX is less alien or arcane than I thought. I recognize the influence of TENEX and TWENEX on Interlisp terminology and notation. For example, the Interlisp REPL is called Exec after the Exec command processor of the TENEX operating system. And, like TENEX, Interlisp uses angle brackets as part of directory names. It's clear the influence of these operating systems also on the design of CP/M and hence MS-DOS, for example the commands DIR and TYPE. SDF's TWENEX system provides a complete Interlisp-10 implementation with only one notable omission: HELPSYS, the interactive facility for consulting the online documentation of Interlisp. The SDF wiki describes the basics of using Interlisp-10 and editing Lisp code with the TTY editor. After a couple of years of experience with Medley Interlisp the Interlisp-10 environment feels familiar. Most of the same functions and commands control the development tools and facilities. My first impression of the TTY editor is it's reasonably efficient and intuitive to edit Lisp code, at least using the basic commands. One thing that's not immediately apparent is that EDITF, the entry point for editing a function, works only with existing functions and can't create new ones. The workaround is to define a stub from the Exec like this: (DEFINEQ (NEW.FUNCTION () T)) and then call (EDITF NEW.FUNCTION) to flesh it out. Transferring files between TWENEX and the external world, such as my Linux box, involves two steps because the TWENEX system is not accessible outside of SDF. First, I log into Unix on sdf.org with my SDF account and from there ftp to kankan.twenex.org (172.16.36.36) with my TWENEX account. Once the TWENEX files are on Unix I access them from Linux with scp or sftp to sdf.org. This may require the ARPA tier of SDF membership. Everything is ready for a small Interlisp-10 programming project. #Interlisp #Lisp a href="https://remark.as/p/journal.paoloamoroso.com/exploring-interlisp-10-and-twenex"Discuss.../a Email | Reply @amoroso@oldbytes.space !--emailsub--]]>
Billionaires, am I right? Immigrants, am I right? It’s going to be so painful to watch. Billionaires will go away. Immigrants will go away. The problems will continue to get worse. The problem is the unproductive. The rich unproductive and the poor unproductive. The finance middle-man and welfare recipient. The real estate agent and the person on disability. The person with a fake job. Anyone who purposefully creates complexity for others. The obstructionists. Rent seekers. Anyone who lobbies against others getting so they can have relatively more. Broken systems that elevate zero sum losers. Why can’t we all turn against them? The first step is recognizing this is the problem. I don’t know why most people don’t see it.
