Rui Carmo

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30 September

Rui CarmoKorrents 30 Sept

From one piece Sep 30th 2026 · 2 min read 3 beliefs, in the piece's order there

korrents.com
The idea of a Her-like assistant may neither fit how most people think about AI nor current sales and advertising business models.

Their words

I think there's a pretty decent chance that the idea of a Her-like assistant, however seductive, neither fits the way most people think about AI nor the sales and advertising business models that I can glimpse just underneath the surface.

Sep 30th 2026 · 2 min readtaoofmac.com
korrents.com
AI is unlikely to be much help with managing personal life processes beyond removing toil.

Their words

And I think AI is not going to be much help with that, other than remove toil (yes, it will sort out your inbox for you and research your travel itinerary).

Sep 30th 2026 · 2 min readtaoofmac.com
korrents.com
The current state of AI agents is at a plateau of decreasing returns where model intelligence increases but useful outcomes have not gelled.

AI agents

Their words

I feel we're coming to another plateau of decreasing returns, because even as models keep getting (arguably) smarter, what you can do with them beyond flashy demos hasn't really gelled into useful outcomes yet.

Sep 30th 2026 · 2 min readtaoofmac.com

22 September

Rui CarmoKorrents 22 Sept

From one piece Sep 22nd 2026 · 7 min read 3 beliefs, in the piece's order there

korrents.com
Apple's app-signing rules and hardware restrictions are increasingly difficult to defend given the power of their hardware.

Apple

Their words

And that is, at a personal level, the thing where I wish Ternus would make allowances, especially now that Apple has stupidly powerful personal hardware-more capable hardware makes those restrictions harder to defend, and app-signing rules need to change.

Sep 22nd 2026 · 7 min readtaoofmac.com
korrents.com
Apple's current approach to AI features fails to account for how regular people will perceive them.

Apple

Their words

Then there's the literal tone deafness about things like the Watch's newfound always-on transcription features, and the fact that Apple has pretty much failed to read the room regarding how regular people will think about these new AI features.

Sep 22nd 2026 · 7 min readtaoofmac.com
korrents.com
Apple's failure to build a competitive frontier model is due to a fundamental impedance mismatch.

Apple

Their words

And yet, I think there is a more fundamental issue that industry pundits keep harping on and circling around, which is that Apple really doesn't know what to do with AI-it's like some sort of fundamental impedance mismatch.

Sep 22nd 2026 · 7 min readtaoofmac.com

29 April

Rui CarmoKorrents 29 Apr

From one piece Apr 29th 2026 · 6 min read 3 beliefs, in the piece's order there

korrents.com
Individual tool tests are insufficient for determining if a model will use a chain of tools correctly.

MCP

Their words

Individual tools passing their tests tells you very little about whether a model will use them correctly together, and that is, I think, why chaining MCP calls has remained somewhat of a dark art.

Apr 29th 2026 · 6 min readtaoofmac.com
korrents.com
Smaller models require explicit breadcrumbs in responses to successfully follow tool chains.

Their words

The big ones will plan a chain from a tool list and a goal; the wee ones won't-they grab the first plausible tool and stop. The fix is stupid simple: every response ends with a breadcrumb dictionary of hints to follow.

Apr 29th 2026 · 6 min readtaoofmac.com
korrents.com
Models do not possess a hidden planner and instead react to the conversation and tool list.

JavaScript

Their words

Models don't plan They look at the conversation, scan the tool list, and grab whatever looks more probable. That's it. There is no hidden planner.

Apr 29th 2026 · 6 min readtaoofmac.com

8 March

Rui CarmoKorrents 8 Mar

From one piece Mar 8th 2026 · 5 min read 3 beliefs, in the piece's order there

korrents.com
Certain programming languages are better suited for agents because strong types and annotations help models understand intent.

Python

Their words

Some languages are inherently better for agents-not in terms of popularity (any agent can do decent Python), but because strong types and annotations help models understand intent and self-correct.

Mar 8th 2026 · 5 min readtaoofmac.com
korrents.com
There is an unwarranted hype cycle regarding the capabilities of local AI models.

Their words

And there is an almost weekly hype cycle around local models that I think is totally unwarranted in practice.

Mar 8th 2026 · 5 min readtaoofmac.com
korrents.com
The gap between local and cloud AI models is significant, and even high-end hardware cannot match frontier cloud capabilities.

Their words

None of these things are really "local" in any meaningful sense-the gap between local and cloud models is huge, and even tens of thousands of dollars in hardware won't get you close to frontier capabilities.

Mar 8th 2026 · 5 min readtaoofmac.com

23 July 2017

Rui CarmoKorrents 23 Jul 2017

From one piece Jul 23rd 2017 · 6 min read 3 beliefs, in the piece's order there

korrents.com
In practice, 80% of a data science team's time is spent wringing meaning out of the data.

Their words

In practice, what generally happens is that: 80% of your team's time will be spent wringing meaning out of the data: hunting down datasets, doing ETL and doing initial feature selection.

Jul 23rd 2017 · 6 min readtaoofmac.com
korrents.com
The first mistake organizations and managers make is thinking that the data scientists reporting to them are their whole team.

management

Their words

The first mistake organizations (and managers) make is thinking that the data scientists reporting to you are your whole team.

Jul 23rd 2017 · 6 min readtaoofmac.com
korrents.com
There is very little hard data on which factors are critical to making a data science team successful.

Their words

I am fascinated by the number of opinions out there on the kind of technology, skill sets and even the kind of data required to make a data science team successful, because there's actually very little hard data on which of those are the critical factors.

Jul 23rd 2017 · 6 min readtaoofmac.com

4 April 2016

Rui CarmoKorrents 4 Apr 2016

From one piece Apr 4th 2016 · 3 min read 3 beliefs, in the piece's order there

korrents.com
Docker will eventually play a role in micro-services, but it is still acquiring the necessary fine-grained control and self-healing.

Their words

Docker will be a part of that story in due time (it's already the gold standard for packaging and re-using "conventional" services, but it's still acquiring the degree of fine-grained control and self-healing that's required).

Apr 4th 2016 · 3 min readtaoofmac.com
korrents.com
Micro-services require scalable, resilient scaffolding that conventional SOA frameworks or ESBs do not usually provide.

Their words

Micro-services require scalable, resilient scaffolding (i.e., the ability to be automatically run on multiple machines, or having multiple instances on each machine to take advantage of multiple CPU cores), and that is not something you usually get out of a conventional SOA framework (or ESB) - although some are beginning to tackle that problem, even as they are bound by their own conventions.

Apr 4th 2016 · 3 min readtaoofmac.com
korrents.com
Micro-services are not inherently hard to design, deploy, or maintain.

design

Their words

None of these are actually true - although, of course, human ingenuity, knowing no bounds, is sure to provide critics with enough data points on any of these dimensions to provide for some healthy argument.

Apr 4th 2016 · 3 min readtaoofmac.com

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