Frannky
I do use Anthropic and OpenAI mostly because it costs me 1/40 and 1/50 of the api prices, which is way cheaper than Chinese subscriptions, but I’m ready to jump ship when they pull the plug. Fortunately they have nothing that forces me to keep paying them, and I don’t pay the crazy enterprise subscription costs, just the personal account prices.
I also die to be able to run the OSS setup locally to stop being spied on all the time.
For context, I averaged 10 hours a day prompting LLMs from when ChatGPT came out. At the start it was just function generation, then single file modules, then modules, and now I reason, design, implement and test with them.
An interesting thing is that with omp you can plan with a smart model and then implement with a dumber one. So for example, plan with Kimi 3.1 via OpenRouter and then implement with DSFV4 with zero data retention active, sorted by cheapest, and minimal tps accepted.
I get the people who are pissed about their cushy jobs evaporating, but if you know how to use these technologies it’s very freeing because it’s like having a company of people working for you, except they are not human so they’re not wasting their life working for you instead of using it for themselves.
You can make them do pretty much everything that is fuzzy-verifiable, you don’t have to worry about their feelings or that they won’t do what you asked them to do or stop, and you can activate them when you want at scale in parallel or not use them at all for days.
For me it’s a dream honestly. I never felt so much empowered in my life while being enabled to unlock my creativity with almost no boundaries.
For now, I think everyone is still using Anthropic and OpenAI because if you use a subscription you pay 1/40–1/50 of the API prices, and the models are good when they don’t nerf them, and they are also way cheaper than open models’ API prices.
The interesting thing will happen when they pull the plug and become economically smarter to stop using them. I regularly try alternatives to avoid being locked in and found GLM-5.3 as an orchestrator and GLM5.3 Flash + OMP and DeepSeek Flash as advisor to be able to get jobs done just fine. Space Bunny too was pretty great, which was probably MiniMax’s new model.
I think they are using an Uber like strategy but without the network effects that justify losing money for so long
Oh-my-py unlocks max capabilities at the smartest token usage, and you can change AI company and providers while still getting things done. Roles, advisor, and the ability to use Chinese models on international providers with no training and ZDR behind OpenRouter are very powerful. You can have providers and model companies competing on price, intelligence, and speed for something that's useful but with less and less moat as model progress plateaus.
I now use GLM 5.3 for slow/planning, GLM 5.3 Flash as the default task-vision model, and DeepSeek Flash 4.1 as the advisor. Providers are ordered by cheapest at the minimum TPS I want for that model. I use it not only for coding but also as a personal assistant. I can ask it things and it gets them done automatically, like opening an issue on a repo, then having another agent ship the code, run the tests, and update master after having changed the app to autoupdate on cut release.
I can also ask it to do groceries. I use Bitwarden machine secrets and a limited virtual card connected to my phone.Something else that's very powerful is asking it to launch parallel agents to do things you know don't overlap too much.
The amount of agency we're gifted with is crazy, you can now move hundreds of hours of work with one hour of input using an open-source harness and open-weight models. I can't wait for more competitors in the chip space, and to be able to buy models etched on silicon for even higher agency, speed, and independence.
They have a new shiny data center with Chinese GPUs, so hopefully they will be able to handle the demand. Their subscriptions are meh, in particular the Flash model has not that much usage. The other thing I wanted to try is Groq Qwen 3.8-27B at 450 tps to see if it's able to get work done faster.
I feel it's very important to play outside of the walled gardens, I feel they will pull the rug very soon, and I need to get job done while waiting hardware prices to go down...
No need to go from audio to text to reasoning, just from audio to output json for running a command via adb automatically and it's working crazy good.
Pretty cool model, especially since it's not a nanny, if you want to unlock your own devices, like rooting an Android, it will happily help instead of flagging you.
Available for free via OpenRouter and Nous free tier. Also via OpenCode Go, but you have to pay a $5–$10 subscription. APIs are hammered now, so service is bumpy.
I can save ideas and ask a CLI terminal to work on them. If I want to do something advanced, I can use Zed, but even from my phone via remote control, I can talk to agents. I always approve the plan before handing off the task.
It's crazy, it's like having a personal assistant and an army of junior engineers. And you can just use a ZDR provider and an open-source harness to stay private and not share your data.
And the models keep getting better and better!!
I'm currently using omp with Kimi K3 as the planner and DeepSeek v4 Flash 0731 as the implementer, or CC + Fable for planning and Opus 4.8 for implementation. For API(not coding), I just use DeepSeek v4 flash 0731 and MiMo.
I'm pretty happy where I am, but I'm wondering if these new models provide some new kind of advantage
Who are the users? What are the problems? And why would people pay for Lovable instead of Claude/OpenAI/Grok, etc.? Do they have something those companies don't,something that lets them get chosen vs the competition?
I'm very confused. I'm not saying the valuation doesn't make sense, but I have a hard time explaining it. The best answer I can come up with is that they're betting on people building apps without knowing how to code—that this alone will be enough to leverage LLMs and turn a profit, capturing a market that's scared away from tools like Claude Code.
And I assume they're not betting on the thing actually working. They're betting on people wanting to build an app and pouring money into it, hoping it'll eventually work—and on Lovable not getting eaten by CC-like tools, thanks to distribution and brand.
I used it in the past and it was terrible. Claude Code from scratch, or even a template tweaked via CC, was way better.
So the assumptions seem to be: - Lovable has data that delivers results people want and can't get otherwise. - Marketing, brand, and distribution are enough to keep users on Lovable, which under the hood just leverages normal LLMs guided in some smart way. - LLMs will get good enough to deliver fully working, enterprise-level products—and Lovable will be the frontend delivering that result
And one can say LLMs are not as smart as a human, but a lot of the reasoning humans do for product and service generation isn't smart at all—it's just a bit of fuzzy input/output plus some reasoning rules. And then if you hook a robot up to the LLM, you can get results in atoms instead of bits.
I'm very excited about the future. I also hope it will stop money from flowing to bureaucrats who are incentived to keep the problems open to keep the money flowing, and instead facilitate sharing directly with the people (for example, no money to the state to solve homelessness—instead, spay instead with intelligence output to build a house and provide food as part of taxes.)
It's similar to the situation where you ask whether you should walk or take the car to go refill the car with gas. I feel LLMs have a linearity embedded in them that prevents them from finding non-linear, smart solutions, especially when data is scarce. They can probably get it done, but with far more complex solutions, which increases the risk of ending up with a crazy complex codebase when it could have been much simpler and more elegant.
The other situation is when I spot a problem or a feature change that's needed after experiencing the product, and I ask how to change the codebase, it suggests something, I say "why not this other thing," and then we do the other thing.
Any suggestions for a better configuration? I mostly need Opus 4.6 + Claude Code alternative. I don't need Fable level capabilities, I add one new feature at a time and approve the code before shipping it. Then test and open a PR.
Usually both Fable and Opus suggest dumb ideas but are good implementers once I tweak the idea, approve the code, and add unit and production tests.
I'm OK spending max $100/month on APIs, ideally with Zero data retention. I only need a few hours a day of coding. I don't want agents running all the time; I figure I can stay on top to each feature and wrap my head around the product and new suggestions as long as I don't build too much at once.
I'm still on a Claude Max $100 plan, but it's barely usable anymore—one call and I hit 20–30% of the 5h window on Opus 4.8. Opus 5 seems tuned to make messes, and Fable burns tokens for a level of capability I don't actually need.
Why work there when you can start a company? You get to choose the problem you care about most, the people you work with, and your own pace—and if it works, you own the success.
Why accept all the rules Google will force on you, are those rules optimized for you or for them?
The rule-makers don't stop anyone, and often the end state is worse than before the rule existed. This happens constantly with tech and the laws that try to contain it.
Tech is like reality: there are endless routes to roughly the same destination, and rules are slow. The asymmetry is the whole problem — you only need to find one new route; they have to block every possible one.
One does not have to use social media or be exposed to that crap. The nice info is easier than ever to reach.
If you start to think of information as code you run through your brain, you may want to select and sanitize what you run. Because in the end, what you read triggers what you think/feel, which influence what you do.