reedlaw

Or go full acronym with Kit for the K as in "Developer Kit".

Same experience with Sonnet on low effort. It used be when I used a "table_name/id" format to reference a db record, it knew exactly how to find it using connected mcp tools. Today it failed 4/4 times (I tried the exact same prompt in 4 separate sessions and each time it replied "I don't have access to [...]"). On medium effort it got it right the first time.

> we shouldn’t anthropomorphize

Agreed, so why frame it as avoiding unpleasant people? My experience with Anthropic's latest models is that no amount of instruction can overcome their latent verbosity (nor can AGENTS.md overcome OpenAI models' reticence). I tried A/B testing several models and Opus was the clear winner, so I'm not likely to retire it just because it generates unpleasant prose. I do curate model-specific notes to mitigate some of the worst offenses.

Turns out Frigate uses visual classification only. Hard to trigger when birds are so small, unless they fly right up to the camera perhaps.

Expectations around software quality will rise in tandem with gains in productivity so that the same experience curve continues to apply.

Because agents lack human judgment. At the very least there's a need for a human-in-the-loop with agentic processes. Otherwise, it's like running a coding harness with --dangerously-skip-permissions all the time.

I have Bird Classification enabled in the settings, but so far haven't seen any labelled (it's only been a few days). Similarly with Face Recognition, I've only seen false positives. It does reliably detect people though (300 tracked so far). I'll have to experiment with settings such as confidence score.

Codex has the opposite problem. Instead of being overly proactive it's overly reticent. I have been preferring it lately, although my preference tend to switch every few months when a model or harness regresses horribly.

What do you mean? I'm Gen X but remember all those things. It seems like a reasonable mashup of nostalgia.