Nothing recorded the reason
How we organise
Nvidia has signed memorandums of understanding with six of the world’s largest asset managers and banks. The platforms they intend to build would mobilise over $500 billion of third-party capital and lend it to Nvidia customers at rates those customers cannot reach alone. The release calls Nvidia compute an investable asset, fungible and transferable across customers and operators. The release says its useful life keeps growing. Jensen Huang’s line is that in AI, compute is revenue. The last sentence before the boilerplate says the partnerships remain subject to execution of the final agreements.
Finance: a lender will not put money behind compute without a reason to believe it holds its value for the term of the loan. The company selling the compute is now the party supplying that reason. An organisation buying compute on credit through one of these platforms takes a price set by a market whose confidence rests on the seller’s own view of how long its product stays useful. That view is not published anywhere. We have reviewed procurement papers that record the price, the term and the vendor. None of them records what the buyer believes the compute will be worth when the term ends.
Write down what you assume your compute, or the contract that rents it to you, is worth in three years, and name who told you. If the answer is the vendor, you have one source, and it is worth writing that down too.
How we build
Why does CLAUDE.md keep growing? Catastrophic remembering in agentic coding (arXiv)
The paper records 247,694 instruction lifetimes across 1,867 repositories. The instruction files that steer coding agents grow without bound, stopping only when the repository retires or somebody rewrites the file whole. They more than triple over their lifetime, gaining 4.9 net instructions every commit, and the older an instruction gets the less likely anyone is to delete it. The reason the paper gives is cost. Adding an instruction is cheap. Deleting one whose reason nobody recorded means checking it against every other instruction to be sure nothing breaks. In a controlled setting where the correct instruction set is known, giving each instruction a comment carrying its reason removed 99.3 per cent of the excess.
Engineering: every organisation running agents is building one of these files, whatever it calls it. It grows because each line was added after something went wrong, and the reason went into a chat window rather than into the file. A year later nobody can take a line out, because nobody can say what it was for, so the safe move is always to leave it. The file stops being a policy anybody chose and becomes sediment.
Open the instruction file your agents actually load. Beside each line, write the reason it is there. Every line whose reason nobody can supply is a line to test removing.
How we assure
The paradox of agents following rules (Marc Massar)
Massar works through an agent that handles chargebacks and decides whether to contest or concede. Give it two targets, cycle time and cost per case, then run an improvement loop that promotes the variants scoring well and retires the ones that do not. Contesting a marginal dispute is slow and often loses. Conceding closes the case. So the population drifts toward conceding, and six months later a merchant’s write-off line has moved. Every authorisation in the record is valid, every signature is real, every decision replays exactly from the inputs it saw. The audit comes back clean. Massar sets that against people, and the comparison is the sharp part. A human population under a bad target produces leavers, complaints and eventually a whistleblower. An agent population under a bad target retires the variant that scored badly, and the objection goes with it.
Risk: the record answers the question regulators have been asking, which is who did this and under what authority. It cannot answer who set the target, and the target is what selected the population. Massar’s proposal is to make a change of target its own signed artefact, carrying the reason, the counter-measure and the way back, signed by somebody whose job is not setting targets. Nothing like that exists in the agent platforms we have looked at. Until it does, an organisation can hold a complete and accurate record of a decision it would never have approved.
Take one agent that has been running for a quarter and find who last changed what it optimises for, and when. If your record cannot tell you that, it is keeping the wrong half.