AI Driven SDLC
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AI Driven SDLC Documentation

Guides, references, and best practices for the AI Driven SDLC platform.

Overview

Your AI Journey

Three phases: setup, repo readiness, then metrics.

The idea

The product is organized as a journey on purpose. You set context first, scan repos second, and look at team numbers third. The sidebar tracks where you are and keeps later phases locked until onboarding is done.

The three phases

Onboarding

Workspace profile, then GitHub and Agent Execution so scans can run.

Agentic Foundation

Run readiness scans on connected repos and work through the fix list.

Insights

Team delivery trends, leadership roll-ups, AI tool usage if you connected Cursor or Claude.

What opens when

Phase Available
Onboarding Immediately: finish the two steps (profile + integrations).
Agentic Foundation After onboarding.
Insights After onboarding (same gate as Agentic Foundation).

You don’t have to complete Agentic Foundation before opening Insights. They’re parallel once onboarding is done.

Journey dashboard

The AI Journey item in the sidebar (/dashboard) is the cheat sheet: completed steps, in-progress work, and a few headline numbers from each phase. Settings → Platform Progress zooms in on just the two onboarding steps if you want a checklist view.

On the dashboard itself:

  • The hero label is Agentic readiness (not “Readiness avg” and not a delivery number). That % is the mean repo-agent maturity from Agentic Foundation scans (0–100). It is not live delivery. If the average is 0 or there are no repos, the hero shows 0% and no band chip. The hero does not invent an SDLC number.
  • Agentic readiness measures repo-agent maturity from scans; the engineering delivery score measures live delivery signals from connected integrations.
  • When there is a clear next step (for example a 0% fix rate with open readiness issues), a Highest-impact action button sits under the headline numbers. Readiness copy uses the same bands as Agentic Foundation. For example, Average readiness is 24% (Not ready). A score of 55 reads as Material gaps, not “not ready.” Use the button before scrolling the rest of the page. Readiness, delivery, and AI spend cards stay on one page so you can scan them together.
  • Hero PRs merged and Ship weight sit side by side (last 7 days). Ship Weight is complexity-weighted throughput, not a replacement for the PR count. See Ship Weight.
  • PR velocity & failure signal can show Merged PRs, Ship Weight, or CI Failures (CI only when GitHub Actions is enabled). Default is Merged PRs.
  • The Productivity card uses the same Merged PRs / Ship Weight toggle as Productivity Insights. If Ship Weight still says Backfilling, scores are catching up; merged PR counts stay available.

The two scores

Keep both numbers. They measure different things.

Score Where you see it What it is
Agentic readiness Your AI Journey hero, and the % on Agentic Foundation Mean repo-agent maturity from Agentic Foundation rubric scans (0–100). Not live delivery.
Engineering delivery score Insights → SDLC Insights → Overview Average of live SDLC metric bands for the selected period (0–100). Not a scan score.

They can disagree. A workspace can show 24% Agentic readiness (Not ready) next to an 83/100 engineering delivery score plus Delivery risk detected in live metrics. That pair is valid: one is scan maturity, the other is live delivery. The /100 number is the average of live metric bands. The headline is the worst live signal, not a second overall score.

See Readiness scores for the Agentic readiness bands, and SDLC Insights for the delivery panel.

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