# Coding agents may speed engineering by 20 to 40 percent

Markdown copy of https://realalpha.app/s/coding-agents-may-speed-engineering-by-20-to-40-percent/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Diogo Almeida](https://realalpha.app/builders/diogo-almeida/) · Diogo Almeida is creator of Jev and cofounder of TypeSafe AI. · Built Jev, a decision model returning typed probabilities; co-invented RLHF and InstructGPT at OpenAI.
- Host: [Jacob Effron](https://realalpha.app/people/jacob-effron/) · AI Investor, Redpoint Ventures · Growth investor in Abridge, Ramp and Physical Intelligence; ex-Flatiron Health.
- Show: Unsupervised Learning
- Episode: [Jev Creator on Decision Models, Benchmark Fatigue & Why the Labs Missed It](https://realalpha.app/v/ham8dROHCrc/), Nov 5, 2026
- Moment: 52:49 to 56:02 of the episode (3 min), playing on https://realalpha.app/s/coding-agents-may-speed-engineering-by-20-to-40-percent/; the episode from there: https://realalpha.app/v/ham8dROHCrc/?t=3169

## Quote

> “my estimates are in the **20 to 40% speed up** range. But again, it really depends on the use case.”
> — [Diogo Almeida](https://realalpha.app/builders/diogo-almeida/) at [55:07](https://realalpha.app/v/ham8dROHCrc/?t=3307) · Unsupervised Learning

## Takeaways

1. His average estimate is a 20–40% speedup.
2. Results vary by use case and user skill.
3. Containing side effects can make agents more valuable.

## About this segment

Diogo Almeida estimates a 20–40% average speedup, with results depending on the task and the engineer. He says managing side effects is key to capturing the benefit.

From “Jev Creator on Decision Models, Benchmark Fatigue & Why the Labs Missed It”, Nov 5, 2026. [Watch the full episode](https://realalpha.app/v/ham8dROHCrc/)

## Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[52:56](https://realalpha.app/v/ham8dROHCrc/?t=3176) right now is what decisions can you trust them with in terms of like stakes for the company and like can you like can you get like value without too much of the the downside and coding is like quite unique in this or like math is actually like like super duper unique where like there's no downside other than the compute you spend right like math models do not cost companies anything except if they're like paying people to validate their proofs which it's unclear if they even pay them for that um yeah to me maybe someone knows um but code also has like somewhat more kept downside because you have like a git right and you have humans in the loop and like there's ways to protect you from unwanted side effects which is the main downside of powerful tools and powerful tools are necessary to do knowledge work because knowledge work often

[53:43](https://realalpha.app/v/ham8dROHCrc/?t=3223) involves like side effects in the world i'm talking a lot like a computer scientist right now My sense is that for a lot of other fields, they don't have anywhere close to the same levels of like safeguards and ability to revert and like tracking and all of that. And that is why, to my knowledge, no one has automated like a drive-thru yet, even though people have tried really, really hard. And the stakes of a drive-thru are a lot lower than the stakes of many other forms of knowledge work.

[54:13](https://realalpha.app/v/ham8dROHCrc/?t=3253) So I think that the truth will be like, there'll be like, nuance and skill into it and the people who will be the big winners are not the ones who just yolo all in but like understand reality and like deploy them um you know in the in in line with the realities of technology so i am i and i'm not given my state of ai i feel like most people are very fomo driven and they do not have a great understanding of the state of ai and they will probably err on the over-optimistic which will get them burned with many side effects or like the over-pessimistic which is business as usual which is how most businesses have been for this ai boom when one thing you said there like you know you i'm curious you said you have an estimate for how much these coding agents actually improve uh engineering productivity what is that estimate

[55:03](https://realalpha.app/v/ham8dROHCrc/?t=3303) okay i will say i have like error bars on this because i think that there's like long term effects, like, you know, skill degradation, and tech debt and stuff like this. So my estimates are in the 20 to 40% speed up range. But again, it really depends on the use case. And it also depends on like the skill of the user. And if you can like, you know, because the side effects are the bad thing, if you can isolate the side effects in a way that those are very legible. So depending on the use case for some, it's kind of like an infinite percent speed up you know you would do things you would never you can do things you can never do otherwise for others they are like just so bad that they're as bad as like coding the thing by hand i would guess on average it's like a decent but small boost and i believe that is the consensus that

[55:51](https://realalpha.app/v/ham8dROHCrc/?t=3351) i've seen in the field right now yeah another question i'm not totally sure how you how you