jlcummings

Being effective with llm agents requires not just the ability to code or to appreciate nuance with libraries or business rules but to have the ability and proclivity of pedantry. Dad-splain everything always.

And to have boundless contextual awareness… dig a rabbit hole, but beware that you are in your own hole. At this point you can escape the hole but you have to be purposefully aware of what guardrails and ladders you give the agent to evoke action.

The better, more explicit guardrails you provide the more likely the agent is able to do what is expected and honor the scope and context you establish. If you tell it to use silverware to eat, be assured it doesn’t mean to use it appropriately or idiomatically and it will try eating soup with a fork.

Lastly don’t be afraid of commits and checkpoints, or to reject/rollback proposed changes and restate or reset the context. The agent might be the leading actor, but you are the director. When a scene doesn’t play out, try it again after clarification or changing camera perspective or lighting or lines, or cut/replace the scene entirely.

Skopeo lets you work with remote registries and local images without a docker/podman/etc daemon.

We use to ‘clone’ across deployment environments and across providers outside of the build pipeline as an adhoc job.

It’s weird how normalized over cap billing became acceptable simply because chargeable metrics were not collected/resolved until after the fact. Seems like an obvious gap in the process or a little bit shady.

Exactly. Why the fixation on one strategy for handling this not so uncommon scenario. It is so common that handling it should be defacto.

This isn’t a pre-paid gas pump use, but that could be one way to present it. We all want to fill as fast as possible. And if your fill spout can handle top rates, you get top fill rates, until you close in on the hard limit. Then it trickles down to the metered drop. Then stops precisely where it needs to.

By accepting/requesting a hard cap, the provider can make clear that in order to be precise, soft caps will go into affect earlier and induce progressive throttling where applicable. If the throttle doesn’t catch the final milliliter or two of gasoline, before the pump shuts off, the provider can and should just let it go. It’s a loss, but comparatively a figurative drop in the bucket.

The other obvious route is predictive where prior usage guide the guardrails. Ordering two eggs is typical for a single meal. Ordering twelve is not. Ordering three or four is unusual for most but if you are a regular diner your habits will be observable.

Any of this predicated on the provider to want to do something. They seem to lack incentives at this point for making it easy. It is stories like op that I avoid well known problematic providers like Firebase who don’t respect and foster long term relationships.

Better wouldn’t necessarily be the right qualifier, but faster, typically more repeatable, and greatly more economical with scale/workload would certainly fit as better from different vantages.

With high novelty? Probably not until machine learning and compilers are deeply entangled.

Likewise, the trivial or novel that you borrow for free isn’t really free when you need to use it suddenly in ways that the license doesn’t permit or it is just technically inconvenient. It is sort of like leasing vs buying, but not really a good analogy.

So far I haven’t seen a comment point this out or suggest similar, so let’s say that instead of trying to maintain an application level list of email addresses that is used in a breach (or for other reasons), rely on the exercising service (email) which by formerly sending a verification email, has a record of the destination at least in a log, and maybe during registration placed in a “verified member” list, all more or less managed within the mail service.

The advertisers (?) are different, but more than 35 (!) years ago, I remember the same format, just different sponsors for different programming.

If all you have is a hammer, hit something.

Use the tools you have to identify problems and turn them into opportunities that present high value returns. Be specific and address problems that can be observed to be clearly within measurable bounds of satisfaction. Employ YAGNI.

Today’s biggest concern is specifically about police treatment of the public it serves. The part that is maddening is the poor treatment and poor handling of people they interact with. Equally concerning but less articulated is the polar opposite, where the shining standouts are part of the training set for tuning the model of law enforcement appropriateness and effectiveness.

Agricultural efficiency, and food handling and storage are big cornerstones in this past century too. We were a world of frequent famine and hunger and now one of abject abundance.

Everyone loves a winner, on some level. But are sports stars generally popular with the public or among their peers, or teammates?

Michael Jordan, was/is endured to the public for his talent and work ethic, but I don’t believe he was adored quite the same by teammates or opponents.