Series · 2 parts
Procedural Memory
How we taught our AI systems to keep the code they already wrote: the registry, the first paired benchmark, and what each measurement changed about the method.
- Part 1AI Agent Memory: Why Our Systems Stopped Re-Solving the Same ProblemsMost AI automations re-derive the same work every run. Here is how procedural memory, storing the working code rather than a description of it, makes AI agent workflows faster, cheaper, and more predictable.Jim Deola · August 23, 2026
- Part 2The Benchmark Pointed at ItselfThe first paired benchmark of our procedural-memory registry measured a deterministic share under 0.5% on one workload and about 55% on another, caught its own row-append step failing silently, and ran under two conditions that rule out any arm-versus-arm verdict. Here is what held up, what did not, and the six variables the next cohort holds fixed.Jim Deola · August 26, 2026
See exactly where your business
runs through you.
The next step is a 30-minute call.
Book a 30-minute call and we'll map where the business depends on you — and what it looks like once a system you own runs the routine. You leave with a plan, whether you hire us or not.
No pitch — you leave with a plan. We'll tell you exactly what we'd do, whether you hire us or not.