Personally, with our company on Cursor, I can see why model makers are not the best people to go all the way down the stack. Using the right model for the situation will continue to be important, and model makers, by design, do not want to give you the choice to run different models.
Right now, we use:
- Kimi K2.5 for easy fixes, asking about the code, various agentic commands (e.g., summarizing Loom videos for Slack messages)
- Opus 4.8, Sonnet, or Kimi for planning (we find GPT-5.5 to have too terse outputs for plans)
- Kimi K2.5, Composer 2.5, GPT-5.4 mini, etc. for faster implementation (i.e. we don't have to wait around for the slower tokens-per-second generation on Sonnet, etc.)
If we had to only use Opus, Sonnet, and Haiku, I'd definitely be looking to switch harnesses
This is so neat! I really think AI turbocharges this kind of personal project way more than it speeds up programming for work:
> I was curious about the possibility of doing this myself, and I asked ChatGPT. Not surprisingly, it knew a lot of the various tapes, file formats, sizes, processing, storage, and after it asked some clarifying questions, it was quite optimistic about me being able to do this myself
Between this, it seems like it helped with so many different parts of the process:
1. Asking for how to do technical things, like transfer video from these old VHS to a newer computer.
2. Writing code for the web portal to host the videos.
3. Writing VLC plugins to help with data entry.
4. Transcribe audio into text.
Similarly, a coworker recently made a website that imitates what Alpha School does to incentivize his own kids to finish their homework all in the span of a weekend, and it's cool to think of the kinds of projects that less or minimally technical people can do with the help of ChatGPT to guide them.
Of course, the debugging techniques and the debugging and problem-solving techniques that you get from being a professional programmer helps a lot with taking what LLMs give you with a grain of salt, and knowing what they're good at and what they're not. But it is a superpower for sure.
Out of curiosity, what do you think contributed to this working better than even OpenAI agent or some of the other tools out there?
I'm not that familiar with how OpenAI and other agents like Browser Use currently work, but is this, in your opinion, the most important factor?
> An infrastructure provider that exposes OS-level controls, not just a browser layer with Playwright screenshots. This is important for performance as a number of common web elements are rendered at the system level, invisible to the browser page
Hey figmert -- this is Peter, one of the co-founders of Wanderlog. I'm actually on a trip to Italy right now and definitely feel your pain with some performance issues, and we've been working hard to improve this.
If you haven't tried the app in the last few months, can you try it again and let me know what parts are feeling slow for you by emailing me directly at [email protected]? I'd love to take a closer look, and especially if you've got specifics with screenshots/videos, I can try to fix some of these myself too.
We've had to go through this process for the app I have, and it definitely was cumbersome and makes the process a huge pain. Fortunately, after a while Google often lets you switch to a Tier 1 assessment, which involves using various tools to analyze your code and make improvements without shelling out a ton of money.
At the same time, Google is in a tough spot here. The files and documents in your Google Drive (or Gmail) are incredibly sensitive. One possible solution is using the https://www.googleapis.com/auth/drive.file OAuth scope, which only lets you access files a user has explicitly shared with the app. I'm curious if iA Writer has limitations that makes this a bad user experience, but from a user security point of view, I can see why I want the apps that get to see my whole Google Drive audited too.
This is a bit of an unusual choice, but I recently was trying to use Webflow, and its videos are both highly informative and funny! Engineers often thumb their noses at videos, but they really show how to do it well:
Right now, we use:
- Kimi K2.5 for easy fixes, asking about the code, various agentic commands (e.g., summarizing Loom videos for Slack messages)
- Opus 4.8, Sonnet, or Kimi for planning (we find GPT-5.5 to have too terse outputs for plans)
- Kimi K2.5, Composer 2.5, GPT-5.4 mini, etc. for faster implementation (i.e. we don't have to wait around for the slower tokens-per-second generation on Sonnet, etc.)
If we had to only use Opus, Sonnet, and Haiku, I'd definitely be looking to switch harnesses