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Method · Hireable · Forward-thinking

AI-era Product Development Life Cycle

Idea to spec to build, when AI compresses the build half

A practical operating pattern for moving from idea to spec to build when AI speeds up production but raises the cost of unclear judgment.

Seventeen slides, async-share register. The seven moves below in expanded form, with SPF and Celine as worked examples. Open in a new tab ↗

What problem this method solves

AI can compress build time. It does not magically clarify judgment, scope, sequencing, risk, adoption, or accountability. AI does not remove product judgment; it makes product judgment more load-bearing.

Where it appears in the portfolio

SPF, Celine, and this site's own spec → design → build rhythm.

The reusable pattern

  1. Frame. Human judgment: outcome and boundary. AI: draft problem frames. Risk: shipping motion, not value. Artifact: framing brief.
  2. Gather. Human judgment: signal quality. AI: cluster notes. Risk: noisy inputs. Artifact: evidence stack.
  3. Shape. Human judgment: options and tradeoffs. AI: generate alternatives. Risk: fake optionality. Artifact: option set.
  4. Specify. Human judgment: constraints. AI: spec drafting. Risk: ambiguous handoff. Artifact: decisioned spec.
  5. Build. Human judgment: implementation fidelity. AI: code acceleration. Risk: brittle output soup. Artifact: runnable prototype.
  6. Validate. Human judgment: what counts as success. AI: summarize findings. Risk: vanity metrics. Artifact: validation notes.
  7. Learn. Human judgment: keep, change, or kill. AI: pattern extraction. Risk: repeated mistakes. Artifact: decision log.

When to use it

Use it when teams feel faster but less aligned, especially in messy B2B and lightly regulated domains.

What I would measure next

Spec revision cycles, re-opened decisions, and build-to-validation latency.