Of course that’s your contention.
You’re just getting into an RL data startup.
You just got finished reading some thread about how the harness is better and the scaffolding is what makes the difference.
You’re gonna be convinced of that til next month when you decide the model is what actually matters, and then you’re gonna be talking about pure capability and how harness doesn't mean much. That’s gonna last until you read more tweets and say the old model vs harness dichotomy is already obsolete and the RL-harness lifecycle with pure outcome rewards fail on long-horizon non-verifiable work because of credit assignment then talk about process supervision without knowing what it even means.
Then you're gonna read some technical blogpost explained to you by sol as ELI5 about how cheap reliable process-level signal+solving credit assignment at agent scale is what actually matters.
and in the end you'll realize that you've been following what everyone is coming up with no original thoughts while burning VC money because you can't even do B2B sales properly when you could've just done powerpoints made by LLMs and shilled it on linkedin
Congrats to the @WeAreLegora team on the release of the Legora BAR, a benchmark for agentic legal work built on 5,161 real law firm cases across 28 practice areas!
@AfterQuery helped QA the benchmark with Legora. Proud to work with their team on measuring the frontier of agentic legal work.
Link to the full blog post in the replies.
🔍 Introducing BackSearch.
LLMs are increasingly asked to predict the future, but a good backtest requires a snapshot of the internet at a point in time.
BackSearch allows LLMs to search the web as it was on a particular date. It’s great for:
🔮 Forecasting and prediction markets.
📈 Quantitative finance.
🌍 RL environments that simulate the world.
🥶 Freezing websearch for benchmark reproducibility
We’re releasing a narrow slice of our index to begin with, focused on the news domain for 2026. Based on feedback we’ll open up more of our index in subsequent releases.
👇 Try BackSearch out with the link below.
@AfterQuery is hiring SWEs!
In 14 months, AfterQuery has surpassed $100M in revenue run rate and works with all leading AI labs to build the data and systems that models train on.
Our founding eng team joined from firms like Citadel Securities, Palantir, and Meta, and we're hiring more.
Apply in the link below or drop your email.
Refer a successful hire and earn $10K.
@AfterQuery is hiring SWEs!
In 14 months, AfterQuery has surpassed $100M in revenue run rate and works with all leading AI labs to build the data and systems that models train on.
Our founding eng team joined from firms like Citadel Securities, Palantir, and Meta, and we're hiring more.
Apply in the link below or drop your email.
Refer a successful hire and earn $10K.