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The MAD Podcast · 3 min · Oct 15, 2026
Complex automation can be built from reliable decision blocks
CEO, TypeSafe
Built Jev, a decision model returning typed probabilities; co-invented RLHF and InstructGPT at OpenAI.

Matt TurckHost · General Partner, FirstMark Capital
Publishes the annual MAD landscape of data and AI; sold TripleHop to Oracle.
About this segment
Diogo argues that higher-level AI workflows should be composed from reliable System One decisions. Reusable, testable blocks can make complex automation trustworthy.
From “Jev: The AI That Makes Decisions, Not Text - and Why It Changes Everything (Diogo Almeida)”, Oct 15, 2026. Watch the full episode
Thanks. We'll look at and fix what's off.
“We just believe that system two tasks should be composed from simpler building blocks that are so reliable that they can be trusted to be built on top of”
Diogo Almeidaat 14:55 · The MAD Podcast14:55Takeaways
- Reliable decisions can serve as reusable software components.
- Composing those components can handle higher-level tasks.
- Test each block before stacking it into larger workflows.
In this episode
Full episode- 15:54Reliable email automation starts with legible decisions4:12
- 27:12RLHF made models pleasing, but raised automation expectations7:15
- 53:02Copying Jev’s interface does not reproduce its reliability5:39
12:19Complex automation can be built from reliable decision blocks3:07
- 19:57Probability scores let developers set their own risk thresholds3:49Up next
- 37:41RLCD required TypeSafe to build its own training data4:14
- 1:02:43Diminishing returns make recursive self-improvement unlikely3:35
Transcript
Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.
- 12:24
system two or bust okay great if uh there is a need for an ai that can do system one particularly well which is a jev world uh it means that there's a number of um decisions in the world of enterprise or otherwise that actually pretty simple decisions is that is that the right starting point that yes though i would go into like a big aside about software as well and machine nativeness and a little bit unclassifiers if i could right now does that sound like an okay aside to jump into sure i would talk about not that in business that there's specifically system one decisions that need to be made like yes i think that that's how it'll start but like i would talk about like how much software can do with its basic logic gates like software can do so many things in the world so many things like basically all of technology from like what 1980 to 2020
- 13:25
was driven by software maybe that's an exaggeration but it feels like that to me as a software engineer so maybe i'm biased um and you can do so many things with like these simple logic gates that just do like ands and ors on bits that's kind of crazy and software becomes big and powerful not by saying like there's an end here or an or here in a business it's by doing like a unit of work um so reliably that it can become like a bigger thing and then composing it together and my claim is where ai will get incredibly valuable is not people mapping out explicitly like here is work you know here's a job here's the system one decisions let's like do a workflow automation on that i think that's how it'll start but i think that ai will explode in usage once people start taking these you know these workflows putting them into like a box and then now people call
- 14:22
the higher level boxes and that is what software is all about because that box will be sold and safe and reliable exactly and you need so many that is what i describe as composability and and the beauty of software is like once you spend the effort up front to making these boxes you can infinitely replicate them, right? Like software is so unbelievably cool. Like imagine you have Lego sets where you can build up higher level things, but you can copy paste them as many times as you want.
- 14:50
That is what software kind of is for automation. And that I think is how you get more and more powerful properties. So system two tasks are not off the table for our models. We just believe that system two tasks should be composed from simpler building blocks that are so reliable that they can be trusted to be built on top of, which AI so far has been incredibly non-composable. Like it plays nicely with nothing except other AI.
- 15:19
And that's kind of tragic. Yeah. Amazing. All right.