Applied AI · John Collins
I investigate frontier AI by putting it to work, examining the results and following the consequences for systems, businesses and investment decisions.
Inspect the worked caseLatest worked case
A familiar number can be calculated correctly and still answer the wrong question. The useful work is showing which assumption makes the difference.
Work you can inspect
A worked case, a persistent-agent question and a systems teardown. Each gives you something concrete to examine.
A reproducible market calculation found seven historical matches. One relevant change to the comparison left none. This worked case shows how AI can help reproduce a result, challenge its assumptions and make the limits visible.
The extra trend condition is exploratory. Zero matches does not invalidate the broader sample or predict what happens next.
Download the five-page walkthroughA good answer can become expensive when the world changes and nobody reopens it. Continuing delegation requires evidence, durable state, permissions and the ability to recognise when an old conclusion has stopped being safe to use.
An AI deployment plan is also a memory deployment plan. Follow the connection from learned weights and persistent agents to the rack, the factory and the customer contract.
The practical question
The source, the calculation, the acceptance test and the assumption that could change the answer. Those are things another professional can inspect.
How I approach the workEngineering into economics
Meta and SpaceX show compute doing two jobs: helping teams create new products, then running what customers use. The relevant capex question changes when the business can create new capability as well as serve existing demand.
Disclosures from five banks show how a small group can build systems that benefit far more people than ever touch a frontier model. Some productivity gains improve the systems needed for the next round of adoption.
Jane Street and the emerging agent stack show how customers can buy less packaged software while becoming much larger infrastructure users. The application may survive; its old economics do not get the same guarantee.
Semtech connects lower-power optical engineering with higher supplier value and operating cash. Its turnaround shows why the funding discussion also needs to examine businesses already generating money from the build-out.
John Collins / Singapore
I build and examine AI-assisted work, then follow its consequences for the systems, organisations and investments around it.
About the work
