Underrated interpretability result from our work with @EngramLab on @harvey law firm knowledge that makes a difference for the UX of long-horizon agents. The reasoning traces you get from parametric memory + study notes are much more intuitive than the interleaved bash commands you get from coding agents. When you read them (esp as a non-technical user), you can actually understand what’s going on. For example: "I remember two antitrust matters from earlier work, one that was terminated (client matter 1001-00004) and one that cleared after an HSR Second Request (client matter 1003-00003)" Compare this to the following from a coding agent (1 of 19 such bash commands btw): { "command": "cd /tmp/cache/1003-00003 && echo \"=== engagement letter head ===\" && sed -n '1,25p' Engagement/engagement-letter-hpe-fund-iv.docx.txt | cut -c1-500 && echo && echo \"=== practice group / partner mentions ===\" && grep -rhoi \"[^.]*\\(practice group\\|M&A partner\\|antitrust partner\\|responsible partner\\|lead partner\\)[^.]*\\.\" . | sort -u | head -12 | cut -c1-300 && echo && echo \"=== HSR outcome ===\" && grep -rhoi \"[^.]*\\(waiting period expired\\|expiration of the \\(extended \\)\\?waiting period\\|early termination\\|closed the investigation\\|closing letter\\|consent decree\\|no further action\\|without taking\\)[^.]*\\.\" . | sort -u | head -15 | cut -c1-400" } Interpretability like this becoming increasingly important for enterprise agent deployments. s/o to @dan_biderman @realJessyLin & team for innovating on multiple dimensions here.