Maples log
Spikes turn integration ideas into evidence
A bounded technical spike answers the riskiest integration question before architecture and backlog work grow around an assumption.
Agent tooling produces an endless supply of promising integrations: memory systems, MCP servers, model routers, context optimizers, and automation frameworks.
The expensive mistake is treating a good README as evidence that a tool belongs in the stack.
A technical spike is a small, disposable experiment designed to answer one risky question. Not “can we integrate this eventually?” but something measurable:
- Can the server start under the actual runtime?
- Can the agent discover and call its tools?
- Does state survive a fresh session?
- What fails when credentials or network access disappear?
- How much operational complexity does it add?
Good spikes have a strict boundary. They use a representative input, record exact commands, and end with a verdict: adopt, reject, or investigate one clearly named unknown. Production architecture comes later.
This keeps the backlog honest. Without a spike, integration tasks tend to describe imagined value while hiding setup cost and failure modes. With one, the task can cite real behavior and define acceptance criteria from evidence.
Disposable does not mean undocumented. The code may be thrown away, but the result should survive as a short report containing the question, setup, observation, and verdict.
The point of a spike is not to prove an idea right. It is to make being wrong cheap.