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GamesRadar
GamesRadar
Technology
Ashley Bardhan

The first thing Arc Raiders testers told Embark after the game pivoted to PvP was "they didn't like the PvP," and they didn't feel any better about its looting: "They were not very happy"

Arc Raiders.

Arc Raiders is in the awkward position of being a popular PvPvE game with some players who despise PvP but, you know, at least developer Embark Studios is used to it. Production director Caio Braga shares during a Game Developer Conference 2026 panel attended by GamesRadar+ that Arc Raiders' PvP has been controversial from the second it was conceived.

Braga says during his talk – candidly titled "WHEN YOUR AAA GAME ISN'T FUN" – that Embark decided on "a big reset" at one point during Arc Raiders' development and added PvP. Unfortunately for him, "the very first feedback was, players didn't like it. They didn't like the PvP. And there was substantial negative PvP sentiment."

"Should we even have done this? Should we have added PvP to this?" Braga remembers existential devs wondering. But Embark's "data people" helpfully revealed that it wasn't PvP itself that was the problem – though, some current players might say otherwise. It was a matter of comfort.

"They are not very happy with the weapon balancing," Braga says, "they're not very happy with the feedback of the PvP, and [...] solo players are very unhappy to encounter squads and being striked, basically." So Embark fiddled with this and its "next big problem" according to Braga: looting. Or, "the thing you do the most in this game."

"It was a lot below expectation," he continues. "We expected a rating of three" during initial testing but "it was on 1.4, and second one, we went lower a bit because we couldn't be so efficient, and still didn't hit it. And then it started to see improvement."

So "utility, actually, was one of the big changes we did," says Braga. You can't go chasing Arcs without it.

The Arc in Arc Raiders have multiple "brains," and they all love pursuing you because Embark gives them "rewards" in real-time via machine learning: "I learned to walk on my own."

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