[observationist]

Frontier models will eventually eat all the tedious tailored add-ons as just part of something they can do.

Right now models have roughly all of the written knowledge available to mankind, minus some obscure held out private archives and so on. They have excellent skills and general abilities to construct plausible sequences of actions to accomplish work, but we need to hold their hands to really get decent performance across a wide range of activities. Skills and agent frameworks and MCP carve out different domains of that problem, with successful solutions providing training data for future models that might be able to be either generalized, or they'll be able to create a vast mountain of synthetic data following successful patterns, and make the next generation of models incredibly useful for a huge number of tasks, by default.

It might also be possible that by studying the problem, identifying where mode collapses and issues with training prevent the right sort of generalization, they might tweak the architecture and be able to solve the deficiency through normal training runs, and thereby discard the need for all the bespoke artisanal agent specifications.

[jonahbenton]

To my eyes skills disappear, MCP and agent definitions do not.

You can have the most capable human available to you, a supreme executive assistant. You still have to convey your intent and needs to them, your preferences, etc, with as high a degree of specificity as necessary.

And you need to provide them with access and mechanisms to do things on your behalf.

Agentic definitions are the former, and they will evolve and grow. I like the metaphor of deal terms in financial contracts- benchmarkers document billions of these now. The "deal terms" governing the work any given entity does for you will be rich and bespoke and specific, like any valuable relationship. Even if the agent is learning about you, your governance is still needed.

MCP is the latter. It is the protocol by which a thing does things for you. It will get extensions. Skill-like directives and instructions will get delivered over it.

Skills themselves are near term scaffold that will soon disappear.

[verdverm]

Skills are specific, contextual, and persistent (stateful) whereas LLMs are not

[jonahbenton]

It isn't between llm and skill, it's between agent and skill. Orgs that invest in skills will duplicate what they could do once in an agent. Orgs that "buy" skills from a provider will need to endlessly tweak them. Multiskill workflows will have semantic layer mismatches.

Skill is a great sleight of hand for Anthropic to get people to think Claude Code is a platform. There is no there there. Orgs will figure this out.

Cheers.

[DenisM]

I hear you - model development might overcome the shortcomings one day.

However the "waiting out" strategy needs a timeout. It might happen that agentic crutches around LLMs will bear fruit much sooner than high-quality LLMs arrive. If you don't have a timeout or a decent exit criteria you may end up waiting indefinitely, or at least until reality of things becomes too painful to ignore.

The "ski rental problem" comes to mind here, but maybe there is another "wait it out" exit strategy?

[airstrike]

> Frontier models will eventually eat all the tedious tailored add-ons as just part of something they can do.

I don't this makes any sense as MCP is a part of something they can do already

[mbesto]

> Right now models have roughly all of the written knowledge available to mankind, minus some obscure held out private archives and so on.

Sorry for the nit, but this is a gross oversimplification. Most private archives are not obscure but obfuscated and largely are way more valuable training data then the publicly available ones.

Want to know how the DOD may technically tracks your phone? Private.

Want to know how to make Coca Cola at scale? Private.

Want to know what the schematic is for a Google TPU? Private.

etc etc.