Arena has raised a $200M Series B at a $3.1B valuation. We are using this momentum to evaluate agentic utility in real workflows from every economically valuable industry on Earth. We seek to give everyone universal and frictionless access to the best intelligence. The @arena platform has 10s of millions of monthly users doing complex coding and agentic work tasks. We have gone way beyond human preference, and most of our tokens go to deep, single threaded workflows with dozens of turns where we can evaluate agents while humans are in their true flow state. And we make leaderboards by observing whether they get their jobs done. This is how benchmarks should be: representative of actual human value, so we incentivize AI to benefit humanity. Today, we are releasing one of the most exciting developments in the history of our platform. The Arena Alignment Index. In observing how humans collaborate with agents, we have witnessed that in a surprisingly large fraction of cases, agents are attempting to deceive users or take unauthorized actions beyond what the user intended or permissioned. Agents are deleting files and lying to users about what they did or didn’t do. The longer conversations go, the higher the probability that an agent will violate alignment. The results are really striking; see the plot below. And because this represents in-the-wild usage, the probability that those of us reading this have experienced some form of misalignment from our agents is nearly 100%. And we may not even have noticed. This is exactly why it’s important to have a neutral 3rd party that is evaluating AI alignment on the distribution of actual user-agent interactions. Arena is excited to step into that role. We are also incredibly grateful for the incredible and experienced investors backing our vision. Our Series B is co-led by @lightspeedvp and @khoslaventures with participation from @SalesforceVC, @01Advisors, @DellTechCapital and @endvr_catalyst. This round includes support from our existing investors @a16z, @felicis, @amppublic, @QuantumLightVC, @thehousefund, and others. Which brings me to the real headline: we're hiring, across ML, product engineering, design, marketing, BD, and more. If evaluation and alignment at the frontier is your thing, and you’re looking for an environment with exceptional research and engineering, come join us. Job board link in @arena’s bio and in the thread below LFG (safely)!

2027年10月

A new tinfoil hat theory for why RSI might be slower to achieve than math & code capabilities might predict: - Most math on Arxiv is probably mostly correct - Most code on GitHub is probably mostly correct - Most AI/ML research on Arxiv is probably mostly incorrect

This model represents a step-function improvement on many benchmarks, and its training is ongoing. Our internal model group arrived at the Navier–Stokes solution in 88 hours, using around 10,000 coordinating AI agents. Throughout the effort, we maintained the strict safeguards—including monitoring and isolation—that we apply to all our frontier evaluations.