I actually think this is directionally correct. Tech companies are starting to spend the same on tokens as they do on eng headcount. Other knowledge work industries will follow with some delay. Kirkland spends billions on lawyers so it’s not crazy to assume they will spend a similar amount on tokens in the future. Most companies are starting to realize they need to own their AI. As models get better law firms will need to better articulate their value to in-house teams using codex / claude for legal. Kirkland is sitting on one of the most valuable AI datasets in the world (all their associate and partner feedback and trajectories). The cost of replicating this dataset is essentially Kirkland’s yearly labor costs. I’m very bullish they can convert this into AI differentiation above the foundation models. There’s no need to build everything from scratch like a lot of the commentary assumes. The infrastructure for building / training / deploying agents has matured significantly. It’s very possible for a firm like Kirkland to use inference providers and rl-as-a-service companies to leverage their valuable data without needing to hire OpenAI level talent. We’ve already seen promising results doing this for similar firms and post training models on lawyer feedback. We think the best future for legal is one where every law firm is able to convert their unique expertise into their own AI and use that to provide their clients with exceptional service. We are starting to invest heavily in training our own models and helping firms do the same. Excited to see a top firm like Kirkland taking a big bet like this.