skolos

If you have free night charging plan you can recoup quite faster. My system paid off for itself in 3 years - although I designed and set it up myself, so it was about 3x cheaper than through contractors (and yes I'm in US and I pulled permits to do this).

You mean 2.25MW chargers: https://electrek.co/2026/09/30/chinas-2250kw-chargers-are-al...

Maybe civ 5 is more reactionary than strategic, so simple strategy that doesn't look too much into future works reasonably well. Or maybe civ is more mainstream and models absorbed more knowledge about strategies that work reasonably well.

I just started live streaming another game - now played by Muse Spark 1.3 (much cheaper than Opus 5.5):

https://www.youtube.com/live/jRi9cdo95As

Interesting that this is on front page. I thought HOMM is quite niche right now. I'm still spending some time on HOMM3 and recently created mcp for Claude Code (with opus 5.5) to play it - you can look at short playthrough here: https://www.youtube.com/live/uU-vvTOZFQY

It is not good at it! And very slow! I tried to improve, teach strategies, write some analysis scripts, etc. Did not help much.

My experience is that agents are decent in coding a feature, solving a bug - doing specific well defined task. They are very bad at judging UI/UX and user flows through app. Like really, really bad. They can quickly put together vibe coded app but make it usable takes a lot of extra manual work.

Did anyone solve this problem? Any good approaches?

By the way - Opus refuses to help you with setting this up - I used grok to drive this.

qwen3-asr-1.7b and parakeet both allow context/hotwords to bias transcription

Here's how to root echo show 8 1st gen: https://xdaforums.com/t/unlock-root-twrp-unbrick-amazon-echo...

responds within 1-2 seconds including 0.5 second waiting for silence as a trigger to start processing.

I confirm this as my experience as well. Parakeet did not perform well for me (English with heavy accent). Whisper large is much better. But once we get to model of this size look at qwen3-asr (1.7b parameters). I'm quite happy with how it performs (both transcription quality and speed on rtx5080). By the way the model is also available on openrouter and very/very cheap. Performance is reasonable (<1s response), but some requests are delayed (>10s)

Just ran some tests on my phrases:

- my whistle setup (tested can run on echo show with <1s response): 206 correct out of 208

These were not tested on echo show yet - on my pc for now:

- Vosk small, phrase grammar: 184/208

- Speech-to-Phrase 1.4.3 (Kaldi): 118/208

- suggested sphinx: 63/208 and on some examples took 13s on i7 14700k pc

looks like my customized whistle works better for me than these alternatives. But more testing wouldn't hurt.

It is all custom made and not very reproducible. I'm working on reproducible setup and once it is done will publish it here: https://blog.kvit.app

Interesting that this is here. I used whistle (and bunch of other things) to take ownership of my echo show. It now doesn't dial to Amazon at all - it does all processing locally with its own CPU and connects to my homeassistant for home automation. My initial setup involved qwen asr (1.7b model) running on rtx 5080. Compared to that, whistle was really bad (out of 170 messages, qwen recognized correctly 168, whistle - 70), but I adjusted whistle to work like jev - instead of free form transcription it recognizes only select set of templates (I trained tiny network with 10,000 generated utterances to translate whistle final state to probabilities within templates). The precision went up to 164/170 - almost matching qwen. By the way - I'm speaking with heavy accent.

This is discussion and not mechanical - surely I would understand this and suggest second favorite from not long ago.

I did lots of interview on both sides and know how often interviews are just luck - got asked trick question that I knew answer to, coding problem that involves algorithm I just recently used, etc.

There is so much randomness that I, as interviewer, decided on the following strategy - put candidate into best possible position and judge from that. I settle on one set of questions - "tell me about your most favorite project, why, and let's discuss in detail". If candidate knows his/her stuff - this is fun/informative discussion. Also easy filter if a candidate cannot say much or doesn't understand details of project they consider their favorite.

1 line in CLAUDE.md I tried (one line, 100 lines, many iterations) - it not always follows style instructions.

The value is very large for me - instead of reading page of Claude produced prose, I mostly just look at focused choices and continue with single button press - significantly less Claude deciphering and typing now. In addition, I do my sessions with /rc so I get nice form on mobile app where I can just select a button instead of typing to continue work.

PS: I think there is confusion in term - "every turn" - I don't mean every tool call, I mean after minutes or hours of agent work when agent decides that its done it gives a report. The report I see now has structure to it with options set to continue (or stop).