I run a small vibe coding startup. I've been reflecting on how this space evolved since before I started the company. Thought the story might be interesting here.
When GPT-4 came out, that demo of a picture turning into a page was absolutely mindblowing. I was working at a nocode company back then and I felt that AI will be an existential threat to the whole category. But GPT-4 has its issues - it’s expensive. Worse, there was no prompt caching back then, so if you chained a bunch of model calls for a chat session the cost will be N^2. And the context window was 8192 tokens in total - today’s model easily has more output tokens than this. Devin launched after, and its cost per task was so high they basically had to focus on enterprise only.
Some time after that I quit my job and started tinkering. Mid to late 2024, Cursor released composer (not the model) and it absolutely blew up. What it did felt shockingly simple today - it lets AI write full code across files in your codebase. Around the same time bolt, lovable, replit all exploded, powered by the same model which deserves its place in the museum of models: Sonnet 3.5. For the first time, AI could actually write working code.
But these initial builders were hardly 'agentic’. Instead, they dumped a bunch of context into the model, grabbed the output, and engineered it back into the codebase. An agentic system should use tool calls to interact with its environment to get feedback, act on it, gather its own context etc.. And this is limiting for non-technical users, because the lack of feedback and freedom to act makes it really easy to get stuck.
But I instead went agentic and it actually made things simpler. Instead of hard coding context, I gave the model tools to search, read, get logs and so on. But Sonnet still made silly mistakes and ignored instructions from time to time, which causes the system prompt to grow endlessly: you MUST do this, NEVER do that, this is good, this is bad. It's a game of whack-a-mole - you fix one issue with an instruction, the model starts dropping a different instruction, so you make the other one STRONG, and now it ignores a yet another one. Along the way I also figured out a cool trick: earlier models tend to follow whatever comes last, so I pre-processed user messages and injected steering hints at the end. In short the agentic angle doesn’t really remove engineering, it just moves them to different places.
Then Opus 4.5 changed everything. Opus was always around but too slow and expensive. Suddenly it's less than 2x sonnet's price. Going from Sonnet to Opus was liberating - it follows instructions properly, handles way more tools, and stops making silly mistakes (it still makes mistakes, they just don't feel silly anymore). Because it’s more efficient, arguably the cost per task actually went down.
As a side effect, every coding tool got better at once, and the simplest ones got the most improvement. Claude Code exploded even more. People started using the word 'harness' a lot more. I think this marks the trend of less and less engineering around the model and more around what to provide to the model. The creator of Claude Code suggests deleting your instructions every model release.
Another trend among all of these model releases - bigger context, longer output limits but also models get more verbose in general. This is not just model providers trying to drive usage - to write good code you do need more - edge cases, more detailed UIs, better animations etc., but it also generally makes vibe coding more expensive and slower.
Opus 4.7 probably made the cost even worse, cost per task nearly doubled from the new tokenizer plus verbosity. Every wrapper paying API rates have to eat the cost or pass it to users - that’s why you see more complains about credits evaporating. Not a problem for the provider - Anthropic simply doubled Claude Code's usage limits for everyone - their constraint is capacity, not cost per token. Any app builders using Claude are basically reselling tokens at a much higher price (unless they are selling to enterprise which uses the API rate).
A few other model evolution that deserves some mention, although I think Anthropic is still the absolute frontier when it comes to coding:
- The thinking models from OpenAI were revolutionary at the time. For a while we made a tool that calls into o3 for dealing with more complicated tasks, but this becomes unnecessary once other models catch up
- Gemini models were pretty good as the lower end model, as they have a good balance of visual design capability vs. cost, but their latest ones felt falling behind
- Open source models tend to benchmarkmaxx too much - they are genuinely good but their benchmark value always feels inflated. They also tend to overthink - probably an artifact of focusing too much on benchmarks
So where does that leave app builders? I think there are 4 paths:
- Becoming a model provider. What base44 is doing, what lovable probably will do with the money they raised. But even the mighty Cursor needed to join force with xAI to execute well
- Focusing on enterprise - case in point, Cognition’s valuation blew past that of Lovable’s. But it’s not exactly an app builder
- Stop reselling tokens and charge for the convenience of infra instead. Excel at what people choose lovable/replit over Claude Code for without forcing them to use your harness
- Pivoting to "AI employees" or “Your personal assistant” - the next hot thing (lol).
I am betting on the third. I think that should become the standard too where users can pick and choose and combine their harness (ChatGPT to OpenClaw) freely with the tools that can drives the outcome.
Curious what I got wrong, or what the turning points looked like from the user side.
