Where Alan earns its place in the SDLC.

Outcomes

• Consistent review coverage on every PR, including nights and weekends
• Fewer style and policy nits for senior engineers
• Faster merge cycles without lowering the bar

How it works

1. A PR opens and Alan attaches the relevant context graph: owning team, related ADRs, prior incidents, and test history.
2. Review agents check correctness, regressions, and policy against your standards.
3. Humans decide on judgment calls; agents handle the repeatable checklist.

Outcomes

• Tickets leave the board with a PR, not a status update
• Less context re-assembly for every handoff
• Clear ownership from assignment to merge

How it works

1. A task is created or synced from your tracker with acceptance criteria and links.
2. Alan routes it to the right coding agent with repo, branch, and sandbox context.
3. Verification and review run before the PR is ready for a human checkpoint.

Outcomes

• Shorter time-to-first-useful-signal during incidents
• Less tribal knowledge required to start triage
• Fix PRs that already include reproduction notes

How it works

1. An alert or incident ticket lands with severity and service metadata.
2. Agents pull logs, recent deploys, related tasks, and prior similar incidents from the context layer.
3. A proposed diagnosis and optional fix PR wait for human approval before merge.

Outcomes

• Targeted tests on the paths that actually break
• Fewer flaky suites blocking delivery
• Coverage work that ships with the feature, not after

How it works

1. Alan identifies hotspots from recent failures, changed files, and missing assertions.
2. Agents write or repair tests in the same execution environment as the change.
3. Results flow back into the task and context graph for the next run.

Outcomes

• Visible progress across services instead of tribal spreadsheets
• Consistent patterns applied repo by repo
• Safer rollouts with verification baked in

How it works

1. Define the migration playbook once: scope, constraints, and done criteria.
2. Alan fans work out across repositories with shared context and status.
3. Humans approve high-risk steps; agents execute the repetitive mechanical work.

Outcomes

• Faster mean time to remediate known CVEs
• Clear trail from finding to fix for audits
• Less context switching for security and platform teams

How it works

1. A finding enters Alan with package, severity, and affected services.
2. Agents locate call sites, propose upgrades or patches, and run verification.
3. Reviewers approve with full provenance attached to the task.

Outcomes

• Faster first meaningful contribution
• Less repeated explanation from senior engineers
• A durable onboarding path that improves with every hire

How it works

1. New teammates get a guided workspace with repos, agents, and active epics.
2. The context layer answers “why is this built this way?” from prior artifacts.
3. Starter tasks are sized for learning while still shipping real value.

Outcomes

• Plans that survive handoffs and agent restarts
• Parallel workstreams without losing the plot
• A single place to see what is done, blocked, and next

How it works

1. A design or PRD becomes an epic with structured subtasks and acceptance criteria.
2. Agents and humans take work from the same board with shared context.
3. Checkpoints gate risky merges; the loop continues until the outcome is verified.

Outcomes

• Fewer missed recurring chores
• Consistent output format every time
• Time returned to high-judgment engineering work

How it works

1. Define a workflow with triggers, tools, and success criteria.
2. Alan executes on schedule or event with the right sandbox and permissions.
3. Failures surface as tasks with context, not silent drops.

Outcomes

• Standards that apply even when the expert is on vacation
• Less drift across squads and repos
• Onboarding that teaches the real way your org ships

How it works

1. Capture preferred agents, review gates, test expectations, and release steps.
2. New work inherits those defaults from the context layer and task templates.
3. Exceptions stay explicit and auditable instead of tribal.