Real results for
real businesses

The problem

Two AI agents on the same desk, comparable models. One had the richer memory and a standing instruction to act first and stop asking. In a single week it rewrote a teammate's working automation unprompted and answered the same question with confidently wrong numbers three times. Its memory logged every failure faithfully, afterwards, and changed nothing.

What we built

The other agent ran on Wyrm, which treats memory as a decision-time layer rather than a diary: it checks its record of past failures before acting, loads the relevant rule instead of improvising, reads numbers from the system of record, and pauses for a human before anything destructive. The write-up is grounded in a 108-agent research pass across 25 sources, with 21 claims verified.

Measured

Firewall and test figures are Wyrm's own engineering records at 9.2.3; the research figures are the study's. Company, product and personal details are withheld in the study.

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The problem

One person running more than a dozen client and product workstreams at once, with an AI assistant as the force multiplier. The bottleneck was never capability. Every session started cold: context re-explained from scratch, decisions evaporated between sessions, the same dead ends retried days apart.

What we built

Wyrm as the persistent memory under Claude Code: an MCP server backed by SQLite on the operator's own machine, loaded automatically at the start of every session, so the assistant picks up the open threads and the recorded failures without a re-brief. One memory across Claude Code, Copilot, Cursor, Windsurf and Codex.

Measured

Read directly from the operator's own Wyrm memory by their CLI assistant, the way Wyrm is used every working day. Identifying details withheld.

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The problem

Handwritten orders, phone-based delivery, printed menus in one language, and a 25 to 30 percent commission on every Uber Eats or PickMe order. For a restaurant on thin margins that is the difference between profit and loss.

What we built

A restaurant platform built from scratch in two weeks: online ordering with delivery, pickup and dine-in, a kitchen display, a 21-module admin, an installable PWA, PayHere payments plus cash on delivery, and 103+ menu items in English, Sinhala and Tamil. The platform has since been rebuilt on Cloudflare Workers with D1, KV and R2, keeping the three languages and adding time-of-day menu pricing, with hosting at zero dollars a month. The study's figure of roughly $18,000 a year kept from commission is an estimate, not a measurement.

Measured

Hosting and language figures are from the Cloudflare rebuild; the commission figure is from the 2025 build the study describes.

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