The perception of capability varies greatly between task. For my needs for example sol xhigh consistently outperforms fable xhigh.

I have 10+ of these workspaces in parallel, and I context switch between them as I get blocked on things. I manage the workspaces using `herder`, which is a terrific tmux-like tool that allows me to keep those workspaces on a nixOS machine I have at home that I SSH into via tailscale, so my agents don't stop working every time I close my laptop (it also lets me leverage that machine's computing resources instead of running dozens of servers and harnesses on my poor MacBook).

Having said that, in truth, I almost never read the unit tests. Before AI, we had almost none (see: several person game studio) so the tradeoff is not "AI-generated tests" vs "human written ones", it's whether we have tests at all. So, I take them for what they're worth - not much - but if it catches an extra regression before it ships every now and then, it was worth it for the price (~free).

Simple UI change? I do an AI review, but otherwise neither read nor write the code. The models are good enough they write better UI code than me, 9 out of 10 times. Not always the more idiomatic, but usually safer and more correct.

Change to our core data plane? I might spend 2-3 times more effort reviewing it than before AI. Yes, I go more slowly than pre-AI. Many more reviews, many more angles considered, including both human and (lots of) AI review cycles.

Most code is not that critical, and AI is also scarily good at writing tests. We also spend considerably more time paying down tech debt and testing thanks to AI, now that the cost is near-zero.

Net: I spend 10-25X less time on low-risk changes. I often direct (or at least approve) the implementation approach, but I rarely read this code. I spend 2-3X more time on high-risk changes. In both cases, I never write code "by hand". Since about November, I've had no reason to actually edit code in a code editor (perhaps maybe except .env files, which we don't allow agents to edit for obvious reasons).

AI is a tool. You can use it to go fast recklessly, or you can use it to go slow with confidence. Just like before AI... the skill and art of engineering is knowing when to do which.

After 6+ months of exclusive Claude Code usage, I was begrudgingly forced to try Codex once Anthropic rejiggered their limits such that I kept maxing out my $200/mo plan in just a few days. These days I pay both $200/mo plans, and it's just about enough to get me through a week's work (small game studio - infinite code to write!)

I had assumed they were primarily limiting it to entice people to upgrade, but I feel like these limits are so low and so temporary (especially over July 4th weekend in the US) that people will barely get a chance to get "used to it" and then think: "man, I can't live without this, I'll pay for API pricing".

There are numerous examples, such as Cloudflare claiming Workflows had reached "GA" status before offering a way to delete workflows... not via wrangler, not the dashboard, not the API. They eventually added this many months after declaring it "GA", with no upfront disclaimers, just the capability silently missing.

If they want to move fast and break things (and they do, as their numerous, "CEO declares an emergency" outages have evidenced) they can — but they need to be honest in their communication about the production readiness of their new products.

That is not "life and priorities": it is poor communication/judgement from an infra company, and misleading advertising at worst. I choose to believe it's the former.