--- title: What Adobe v ArtCraft teaches us | daily.dev description: AI labs tried to replace software engineers but ended up destroying their own customer base, the author argues. Software companies used to run as 'toll... canonical: https://daily.dev/posts/what-adobe-v-artcraft-teaches-us-f9xjoziss twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: What Adobe v ArtCraft teaches us | daily.dev og:description: AI labs tried to replace software engineers but ended up destroying their own customer base, the author argues. Software companies used to run as 'toll... og:url: https://daily.dev/posts/what-adobe-v-artcraft-teaches-us-f9xjoziss og:image: https://api.daily.dev/og/posts/F9XjOZiSS.png og:image:alt: What Adobe v ArtCraft teaches us og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # What Adobe v ArtCraft teaches us **[Hacker News](https://daily.dev/sources/hn)** · 7 min read · 1 upvotes · 0 comments ## Summary AI labs tried to replace software engineers but ended up destroying their own customer base, the author argues. Software companies used to run as 'toll booths', charging recurring fees because building good software was hard. Cheap AI coding tools, priced at $20 a month, let hobbyists clone products like Photoshop over a weekend, so that money evaporates instead of flowing to the labs. A $200 'premium' plan works out to $2,400 a year, less than a single month of a senior engineer's salary at Google, while Amazon, Alphabet and Meta planned roughly half a trillion dollars of capital spending for 2026. Meta's 2023 release of Llama and Chinese labs following suit mean the labs can't raise prices without customers switching to free alternatives, leaving them with cheap plans that kill customers or expensive ones that kill demand. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### Why can't OpenAI and Anthropic just raise prices on their coding AI products to fix their business model Raising prices would push users toward free open-weight models instead. Since Meta open-sourced Llama in 2023 and Chinese labs followed, capable open-weight models can run on cheap rented servers, so pricing AI coding tools at engineer-level rates just drives customers to free alternatives rather than generating revenue. _Anyone weighing paid versus open-weight AI coding tools can track how this pricing standoff plays out on daily.dev._ ### How much do heavy users of premium AI coding subscriptions actually cost versus what they pay Heavy users of a $200 per month premium coding plan, working out to $2,400 a year, reportedly burn through compute worth many times that price, making the subscription a money-losing deal for the provider. By comparison, that annual cost is less than a single month of a senior engineer's salary at Google. _Developers budgeting for AI coding subscriptions can follow real cost breakdowns like this on daily.dev._ ### Why are AI coding tools hurting software companies that were supposed to become their customers AI coding tools make software cheap to build, so hobbyists can clone commercial products like Photoshop over a weekend and give the clone away for free, meaning the subscription revenue evaporates instead of shifting to the AI labs. This undercuts the software companies' 'toll booth' business model that was expected to eventually pay the AI labs instead of engineers. _Teams rethinking software pricing against free AI-built clones can follow this debate on daily.dev._ ## Community take How the wider developer community reacted, aggregated from 1 discussion and 146 comments across hackernews (as of 2026-10-25). **TL;DR:** Commenters are split between viewing cheap AI coding as a genuine wealth-transfer revolution that could flood the market with free software, and skeptics who doubt current AI clones can really replace mature professional tools or sustain themselves economically; many also suspect the post itself was AI-generated. **Sentiment:** 15% positive · 35% mixed · 50% skeptical **The case for** - Some argue free/cheap AI-built software is a genuine revolution that will make tools effectively free and benefit everyone, similar to past industrial/technological leaps. - A few people report daily, practical use of the Photoshop-alternative for simple edits like background removal and exposure adjustments. - Models can adapt to undocumented or proprietary APIs by reading docs and iterating, reducing the 'knowledge decay' concern raised in the post. **The pushback** - Many commenters say the AI-built Photoshop clone is buggy, incomplete, and can't reliably save files, calling it unusable for professional work. - Several argue toll booths persist mainly due to network effects, continuity, and organizational needs that a weekend clone can't replicate. - Multiple people believe the article itself was written by an AI (Claude), undermining trust in its argument. - Some dispute the economics, noting labs still get paid regardless of who uses tokens, and that CoreWeave/investor framing in the post doesn't hold up. - Concerns that commoditizing software work will also collapse the market for the engineers who buy AI subscriptions, hurting the labs' own customer base in a different way. - Doubts that models can stay useful without continuous costly retraining as APIs and frameworks evolve. **By community** - hackernews (mixed): Discussion splits between those who see freely replicated software as an inevitable, beneficial revolution and those who doubt AI clones' quality, question the post's economics, and suspect the article was itself AI-written. **Hottest debate:** Whether cheap AI-built clones represent a genuine, beneficial 'revolution' that democratizes software, or just hype around unreliable, unmaintainable slop that can't actually replace professional tools. **Open questions** - Will AI-built software clones ever reach feature parity and reliability with mature professional tools, or will they stay stuck as rough approximations? - If AI labs' cheap plans destroy their software-company customers, who ends up paying for continued model training and infrastructure costs? - Will open-weight models stay genuinely open and cheap once the current competitive 'price war' between labs ends? **Highlights** > Nobody uses it. It’s completely broken and was dead on arrival. It can’t even reliably save files. Maybe eventually it’ll get to a sort of working state, but I doubt it. I think that’s one of the things that’s jumped out at me in this latest slop wave from the last few weeks. Part of releasing meaningful software is the time investment by the creator is at least the barest of assurances that it’ll get some kind of support going forwards. Obviously not always, but the bigger the scope the more likely that is I think. If somebody spends 6 months on a project then it means it was worth at least 6 months to them and I believe there’s a higher chance they will continue to support it. With stuff like this, it’s unusable and unmaintainable, and it got crapped out so fast that the creator has absolutely no emotional or personal investment in it beyond the token costs. I’m not suggesting every project needs a minimum amount of time spent on it, but it’s certainly a factor in how I judge software now, and choose what I want to interact with. > — [roblh on hackernews · 2 comments](https://news.ycombinator.com/item?id=50234208) > Outside of specialized niches, toll booths exist due to network effects. Most of the revenue for Adobe is not due to individuals who need a competent standalone tool. It’s for organizations that need all of the usual qualities: 1) continuity with prior work (my old projects open properly, last year’s training is still relevant) 2) being able to hire/train employees on the tool 3) collaborating externally 4) interoperability across work products (eg vector, raster, video, etc) You are not getting any of that from someone’s vibe coded weekend project. > — [anon7725 on hackernews](https://news.ycombinator.com/item?id=50234191) > > that money doesn’t migrate to the AI lab. It evaporates. No, someone still has to pay the subscription. AI Labs don't care who uses the tokens and how. If Adobe goes under someone else is going to take their place. Suprise, surprise: they will also use tokens. > It’s a very expensive way of shooting yourself in the foot and sending the bill to your investors. I'm not sure how CoreWeave bond chart is even remotely relevant here. They are not even an investor. > They are just mining the asteroid, dumping the silver onto the market for $20, and watching the price of their own product plummet to zero. The lab's own product is the model. How is someone building a weekend project going to plummet the value of their model? It's the opposite! > — [RomanKornev on hackernews · 3 comments](https://news.ycombinator.com/item?id=50234025) > The author here is Claude (possibly something that distilled it). Dude was like “write me a diatribe about AI arguing why coding agents don’t make sense” > — [aabhay on hackernews · 2 comments](https://news.ycombinator.com/item?id=50233745) > The article is wrong. Adobe charged rent to create profit to send to shareholders. Paying engineers was not the major cost center other than that it needed to _seem_ like it was, to justify the subscription price. Ultimately Photoshop as an idea stopped creatively evolving and Adobe created a tenuous pricing scheme that disincentivized competition, locked in users, and made most customers resentful. What this taught many of us is that this is a cautionary tale. Mind you Adobe could have made CC free, built a healthy ecosystem around it, and created a lot of value in network effects, standards, plugins, etc. But they chose the dark path and they deserve to pay for it. > — [bentt on hackernews](https://news.ycombinator.com/item?id=50234117) **Source threads** - [hackernews](https://news.ycombinator.com/item?id=50232682) · 72 points · 146 comments ## Similar posts on daily.dev - [AI Is Too Expensive](https://daily.dev/posts/ai-is-too-expensive-snj1hxice) · Where's Your Ed At · 87 upvotes · 22 comments --- Tags: [#open-source](https://daily.dev/tags/open-source), [#openai](https://daily.dev/tags/openai), [#ai-coding](https://daily.dev/tags/ai-coding), [#anthropic](https://daily.dev/tags/anthropic) [View this post on daily.dev](https://daily.dev/posts/what-adobe-v-artcraft-teaches-us-f9xjoziss) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"What Adobe v ArtCraft teaches us","url":"https://daily.dev/posts/what-adobe-v-artcraft-teaches-us-f9xjoziss","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/what-adobe-v-artcraft-teaches-us-f9xjoziss"},"datePublished":"2026-10-25T18:07:25.378Z","dateModified":"2026-10-25T21:23:37.961Z","description":"AI labs tried to replace software engineers but ended up destroying their own customer base, the author argues. 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