You can have a camera doorbell using your copper wire.

With a video doorbell you can get notifications when a person enters your property. You can notify police or neighbors if it’s a stranger

Don't developers configure their LLM tools to only be able to access things the user using the LLM should have access to?

Gotta love the LP4 mode. So much music on a single disk! Remember the cool rectangular batteries? Why aren't these gumstick batteries more used in modern devices!?

The only reason I know and use DuckDB is because my (internal, private-use-only, experimental) vibe coded projects use it a ton. I didn't pick it - LLMs did. Until this article, I wasn't aware of what it actually is capable of.

Most of these projects use JSON(L) files for storage, and duckdb to process them.

If you haven’t investigated storing in parquet format - and it doesn’t break other consumers that need your jsonl formatted files - it could be worth trialling for your use case. You’ll see vastly smaller file sizes (even more so if you use zstd compression), and querying time will shoot up.

Usual caveats apply, but as a general rule it’s held up well for me. Only downside is that inspecting the results moves from vi on the output file to duckdb and a select * from.

Yup, especially data backups (although I wouldn't store critical backups like this, only nice-to-have ones). One minor note is that parquet file sizes / compressed sizes can be sensitive to ordering, so you can try different sort orders to get optimal compression.

I found with using various tricks I can get the zstd parquet to be up to 10x (or more) smaller than an equivalent Postgres table - but obviously the exact compression ratios will depend on the kind of data you have and how well your Postgres table is normalized.

I'll 100% try DuckDB in more serious projects where I would normally use Sqlite.

Try the superpowers plugin, let it write a spec (what do you want?) and a plan (how is it implemented). Then let it implement the plan.

Review each step as much as you care. These things take time so you can just do other stuff while it’s cooking.

With proper isolation of projects you can easily have multiple sessions in parallel. I frequently have 4 to 8 parallel Claude Code sessions, each with whole trees of agents reproducing, speccing, planning, implementing and reviewing things.

For common mistakes, you can make it remember things or rely on reviews.

You know what’s worse (less efficient) at parsing and writing code than LLMs?

Humans.

“This is a significant rewrite that will take weeks”

Done after my potty break

Try it on RAM and CPU.

It’s slower but you can run them.

Good idea for evaluating the models, thanks.

Because the air is squished out I suppose

Min Release Age of 7-30 days covers the majority of potential issues with 0 effort.

All major Node package managers should support it by now.

Prom was the best IIRC, yarn second, but even npm is catching up

We’re using an internal package repository that acts as a gateway to the public package repositories, except it can have custom rules such as “min release age 30 days”, and can also give logs about which projects have actually downloaded a specific version.

It’s so much overhead and auditing to enforce compliance across the thousands of node microservices though.

That’s a great idea. Maybe use Claude Code with some owasp knowledge to sweep through them and see if there’s anything obvious?