From intent
to a checked deliverable.
DropKit / DK2 coordinates AI-assisted software work through plans, builds, evidence and independent review. This case describes a bounded internal delivery trial.
- Project
- DropKit / DK2
- Maturity
- Active development
- Evidence
- Internal accepted-app trial
- 01Intent
- 02Plan
- 03Build
- 04Check
- 05Review
- 06Export
ILLUSTRATIVE METHOD / NO CUSTOMER RECORDS
The situation
Software construction spans more than one prompt or coding session. Plans change, attempts fail and a new builder needs to know which candidate is actually being reviewed.
What mattered
The project needed durable records of decisions, attempts, failures and review outcomes. A deliverable had to remain tied to the files that were checked.
What I built
I built a local platform workflow for bounded AI-assisted work: planning, implementation, verification, independent review and export, with project state preserved between steps.
What the trial showed
A documented internal trial took a small app through independent review and a checked export. Saved test records and the delivery evidence connect that result to the accepted candidate.
This is a specific internal proof. Development continues on the wider platform, reliability and recovery workflow; the successful trial does not imply that every later candidate has been accepted.
What this demonstrates
Practical software construction, workflow orchestration and evidence management. I can build the mechanism that keeps an AI-assisted delivery inspectable, as well as the application inside it.
EVIDENCE & MATURITY
Internal delivery evidence dated September 2026 records an accepted small app, test runs and a matching export. Current platform records also show ongoing development. This is not a commercial release or a general autonomous-delivery guarantee.
Related governed AI capabilities
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