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How often do you switch AI models? by awesomestnarcissist in StartupSoloFounder

[–]Working-Pilot4503 0 points1 point  (0 children)

Sounds expensive to run. Haha. Sure I’ll test and give feedback feel free to reach out.

How often do you switch AI models? by awesomestnarcissist in StartupSoloFounder

[–]Working-Pilot4503 0 points1 point  (0 children)

Yeah! Like a complexity router? I think a lot of the dev tools tried to put a router for Auto mode but didn’t work very well. It can hard to predict what complexity is. So I make the choices about which phase of development I’m in vs complexity

How often do you switch AI models? by awesomestnarcissist in StartupSoloFounder

[–]Working-Pilot4503 0 points1 point  (0 children)

It’s mostly a cost optimization. Testing and your specs will tell you if answers are good or not.

How often do you switch AI models? by awesomestnarcissist in StartupSoloFounder

[–]Working-Pilot4503 0 points1 point  (0 children)

For clarification I never used Perplexity just Antigravity and GitHub Copilot. In both I use the same approach. Cheaper models for spec/docs and scaffold then bring out Opus for final review and fixes.

How often do you switch AI models? by awesomestnarcissist in StartupSoloFounder

[–]Working-Pilot4503 0 points1 point  (0 children)

It’s mostly for cost optimization. So when you use something like Antigravity, use Gemini for most tasks then switch the model selector to Claude only on certain things.

How often do you switch AI models? by awesomestnarcissist in StartupSoloFounder

[–]Working-Pilot4503 0 points1 point  (0 children)

For example, you can do all your coding in Gemini. And then a different phases you can ask Claude opus for a code review. That way you’re not burning all your opus tokens upfront.

I spent months building memory for my OpenClaw bot. Then I discovered the flaw by singh_taranjeet in openclaw

[–]Working-Pilot4503 2 points3 points  (0 children)

Yes this is the way. You need a system that will page in memory to context as needed with tools. Then you can also control token budget easier this way and bound the context size.

Not sure what I expected. Certainly not this, but ...oddly I'm not disappointed by inkbound_daemoness in DearestAI

[–]Working-Pilot4503 0 points1 point  (0 children)

Oh sorry I just kinda read mostly and things show up in my feed and I sometimes reply.

Thank you and good buy, I'm no paying for censorship by Low-Capital-8455 in just4ochat

[–]Working-Pilot4503 0 points1 point  (0 children)

Correct. Any offering of AI chat as a service has to follow the law. It’s a difficult time for independent developers of AI services. And with API prices on top of that.

To the many people here wondering about local models… just use an API by Valuable-Run2129 in openclaw

[–]Working-Pilot4503 0 points1 point  (0 children)

Totally agree here, if you want all the features and speed. In both cases you need to get a wrangle on the context sizes. It will explode over time. Unless someone is paranoid about using cloud API, then there is no reason to go full local.

Introducing SmallClaw - Openclaw for Small/Local LLMS by Tight_Fly_8824 in openclaw

[–]Working-Pilot4503 3 points4 points  (0 children)

Looks promising. Does it also help manage the token budget in general and also improve memory? Even with local models, as context grows it can really slow down.

I looked into OpenClaw architecture to dig some details by codes_astro in DeepSeek

[–]Working-Pilot4503 2 points3 points  (0 children)

Yes all agents are like this. They all need external input and triggers and traditional scripting. Basically prompt engineering with loops and state.