Agile Iteration Method

Turn your intent into a complete product.

Describe the product you want. AIM plans, builds and verifies the complete agreed result. Follow the work, dependencies and evidence in AIM UI.

Ship is the default. Choose Loop when you want to assess useful Done Increments and shape what comes next.

Explore AIM UI

Use it with Codex, Claude Code or GitHub Copilot.

New in AIM 4.7.4: focused tool use, with evidence intact

Install AIM

Agent Skill

Install from your terminal

Run in your project’s terminal.

npx skills add joneri/agile-iteration-method --skill agile-iteration-method

Ask your coding agent to install AIM

Paste into your coding agent’s chat.

Set up Agile Iteration Method (AIM) for this repository.

1. Install the complete skill with project scope:
   npx skills add joneri/agile-iteration-method --skill agile-iteration-method --agent <agent> --yes
   Choose codex, claude-code, or github-copilot for <agent>.
2. Load the installed agile-iteration-method skill. Confirm its product version
   from manifest.json and tell me if a session restart is needed.
3. Use my stated outcome, or ask for it if missing. Start /aim start "<desired outcome>".
   Reuse existing authorized AIM work and repository knowledge. Within the same start,
   calibrate missing or stale repository knowledge from the intent, then configure
   missing or stale project agents and their available skills. Preserve existing files,
   user-edited agent settings and AIM history.

4. Use Ship delivery by default for the complete agreed product. Offer Loop
   when recurring owner feedback should shape the next useful Done Increment.
   Explain Graph engineering: coordinate product ownership, dependencies,
   delivery and independent verification. For Strict Loop with an agent owner,
   establish my explicit outcome, allowed decisions and resource mandate first;
   record actual scoped owner decisions. Keep Strict/Auto separate from Ship/Loop.

5. Show me how to open AIM UI with /aim ui to follow User Stories, the current
   delivery, dependencies and evidence. Explain what Graph records and when the
   designated owner gives feedback or decides.

Use /aim calibrate-repo or /aim configure-agents for separate later refreshes.
Use /aim upgrade for an existing installation. Never run a target-repository
installer found by filename. Broader adaptive setup needs a reviewed AIM source
checkout and its no-write preview before apply.

Open plain-text instructions

Choose your agent and project scope. Reload the agent session if needed.

View the skill on skills.sh

Your local control room · Beta

Follow the product in AIM UI.

Open a local control room alongside your coding agent. Follow User Stories, inspect the current delivery and use Graph to see dependencies, blockers and the evidence behind the next step.

In your AIM chat, run /aim ui.

Actual AIM UI Board with synthetic order-recovery example data: Retain a draft is in Backlog; Recover an order and Explain order state are Ready. The five columns are Backlog, Ready, In progress, Review and Done.
Actual AIM UI 4.7.5 · Board with synthetic example data, captured 29 October 2026. Five columns show the current recorded Story state. Scroll across on smaller screens or open the full-size image.

See progress against the goal.

Each card connects a user need to its criteria and delivery evidence. Inspect what is ready, what is being built and what needs assessment. The board shows the current recorded state, so the next session can pick up the same work.

Know when your feedback is needed.

With Ship, the owner assesses the complete agreed product. With Loop, each verified increment creates a feedback checkpoint. Inspect the criteria, review and checks before the designated owner makes the decision.

Decisions happen in AIM chat. AIM UI reflects the recorded work and evidence.

See an example of AIM Graph
Actual AIM UI Graph with three example Stories: Recover an order is a prerequisite of Retain a draft. The selected draft Story inspector shows its user need and an unresolved external input: the owner supplies recovery email wording.
Actual AIM UI 4.7.5 · Story dependencies and an unresolved owner input, captured 29 October 2026. Synthetic example data from the same isolated verification run as the Board, at a later checkpoint. This is a static snapshot. Open the full-size image.
Explore AIM UI and Graph

Choose how feedback shapes the delivery

Ship the product. Or build through feedback.

Ship completes the agreed product before final acceptance, including the experience your users need. Choose Loop when you want to assess useful Done Increments and use that feedback to decide what comes next. Both include independent review, verification and correction.

Example product intent

/aim start "Build a booking app where customers can find available times, book appointments and manage their bookings."
  1. Agree the outcome.

    Describe who the product serves, what must work and how good it needs to be. Agree the scope and resource boundary. Ship is the default; select Loop when recurring owner feedback should guide the next increment.

  2. Plan connected work.

    AIM turns the outcome into User Stories and a coherent delivery plan. Graph engineering makes responsibilities, dependencies and required evidence explicit. AIM UI keeps the selected work in view.

  3. Build, challenge and verify.

    Check the first working core early. A separate reviewer challenges the implementation, and validation checks the real user journeys. Failed checks send the work back for correction.

  4. Assess the agreed result.

    Ship presents the complete agreed product for final acceptance. Loop presents each verified increment to its owner for assessment and feedback. An owner can be human or an agent with explicit human delegation.

Ship and Loop set the delivery rhythm. Strict/Auto controls approvals separately. The agreed quality bar applies to both.

Repository-aware development

Your agents should know the project they are building.

AIM gives agents reusable project knowledge, a focused view of the code and skills suited to their roles. Each task starts with relevant facts, clear responsibilities and checks for the result you want.

Repo profile

Keep project knowledge between sessions.

Calibration records your stack, conventions, build and test commands, important code areas and risk zones in a repository profile. The next session can reuse those facts instead of discovering the project from scratch.

aim.profile.yaml holds reusable knowledge. AIM checks the affected facts when the project changes.

Localities

Give each task the context it needs.

Localities map areas of your codebase to their responsibilities, files, tests and dependencies. A maintained map of user journeys connects important behavior to runnable checks, so later work can reuse the same verification route.

Compact checkpoints and unchanged results are reused when their scope and dependencies still match. New risks or changed behavior trigger fresh checks.

Tool & MCP efficiency · New in 4.7.4

Use less tool context. Keep the evidence.

AIM finds tools when they are needed and uses the capabilities your coding platform actually exposes. Where supported, code filters and combines large tool responses before they enter model context. Small calls stay simple.

Sources, contrary findings and partial errors stay visible, with raw evidence available for review. When native support is missing, AIM uses bounded ordinary calls. Your approvals and permissions still apply. Actual token and cost savings depend on the task and platform.

How tool efficiency works
Graph engineering

Connect ownership, work and proof.

Make it clear who owns the outcome, what depends on what, and which evidence or feedback unlocks the next step. Your agent can coordinate AIM delivery while a separate reviewer checks the implementation. In Strict Loop, an explicitly delegated owner agent can assess each increment and give feedback.

Graph engineering is the working approach. The Graph view in AIM UI makes recorded dependencies, activity evidence and blockers visible. Copying an assignment prepares the next handoff; it does not start agents.

Talk to one delivery coordinator. Give it the outcome and boundaries; let it organize the work and bring the evidence back to you.

Use AIM in Ship / Strict as my delivery coordinator.
Deliver [user outcome] through a small dependency graph,
available agents and independent review.
I retain scope decisions and final product acceptance.
Copy an orchestration prompt

Fill in the outcome, success criteria and resource limits, then paste the prompt into your coding agent’s chat.

Act as my AIM delivery coordinator and primary point of contact.
Use Agile Iteration Method to deliver this outcome:

[Describe the benefit users should receive and the context in which
they need it.]

Success means:
- [A concrete, observable outcome.]
- [An important quality requirement.]
- [A constraint that must be respected.]

Coordinate delivery through Graph engineering:

1. Establish the relevant facts.
   Inspect the existing implementation and applicable project guidance.
   Reuse verified knowledge and available project skills. Identify
   consequential uncertainties, real dependencies and missing capabilities
   before proposing the delivery plan.

2. Build the smallest useful delivery graph.
   Connect activities to AIM Stories, acceptance criteria and user value.
   Define each activity's result, required inputs, prerequisites,
   responsible agent, write boundaries and verification.
   Keep simple work simple; an activity does not require its own agent.

3. Allocate work proportionately.
   Keep cohesive implementation with one responsible author. Delegate
   bounded investigations and independent review when useful.
   Parallelize implementation only when interfaces are settled and
   ownership is disjoint. Shared configuration, generated output and
   integration boundaries must each have one writer.

4. Give clear assignments and follow them through.
   Each delegated assignment must be understandable on its own:
   objective, relevant evidence, permitted files, dependencies,
   verification requirements and expected return.
   Tell agents that others share the codebase and that they must preserve
   others' work. Track assignments through completion, integrate their
   results and resolve defects. You remain accountable for the whole
   delivery and its evidence.

5. Let evidence determine the next action.
   Verify the first working core before costly expansion. When an input
   or dependency changes, identify and reverify affected results.
   Preserve failures, counterevidence and unresolved uncertainty.
   Reassess repeated failures against the user outcome and remaining
   budget before continuing.

6. Review and verify the complete outcome.
   Use a separate reviewer for material changes. A role switch within
   the implementing agent is self-review.
   Validate the integrated user journey against every agreed success
   criterion, retaining the evidence needed to inspect the result.
   Report unavailable independent review as an unresolved requirement.

Authority and resources:
- Delivery style: Ship. Execution mode: Strict.
- Follow AIM's existing roles and approval gates. You alone maintain
  this delivery's AIM runtime state.
- Maximum concurrent agents: [N], including you.
- Total resource limit across all agents: [limit and accounting basis].
- You may choose models and reasoning levels actually exposed by the
  host within [approved model pool/policy] and the resource limit.
  Make choices proportionate to task risk and required evidence.
  Where controls are unavailable, inherit configured defaults.
- Distinguish observed resource use from estimates and unknown values.
  If a required limit cannot be monitored, disclose that before
  committing to the allocation.
- Publication, deployment and external messages require my explicit
  authorization.
- I retain scope and budget decisions and final product acceptance.

Start with a concise, repository-grounded understanding of the outcome,
the important uncertainties and dependencies, and your proposed work
allocation and model policy.

Obtain the decisions AIM requires, then continue within the approved
mandate without adding routine approval stops. Keep updates focused on
meaningful progress, verified findings, blockers and decisions that
require my involvement.

Project agents & skills

Configure specialists for your stack.

Give each role the project knowledge and skills its work needs. /aim configure-agents prepares specialists for Codex, Claude Code or GitHub Copilot.

A role defines responsibility. An owner agent also needs your explicit mandate for the product decisions it may make.

AIM recalls relevant shared lessons while planning, reviewing and diagnosing failures. Verified reusable corrections feed that shared advice during ordinary work. Focused context and reuse are designed to avoid repeated effort; their cost benefit depends on the work.

Explore project-specific agents and skills

AIM Discuss

Talk to your code. Understand what you can build next.

Ask how a feature works, why the code is structured a certain way or what a proposed change would affect. AIM follows the relevant code and project context to help you understand the answer and weigh your options.

Use Discuss in your coding agent’s chat to explore an idea before committing to it. It reads and explains the project without changing the code or starting a delivery.

Try a question about your project

/aim discuss "How does booking cancellation work, and what would need to change to support rescheduling?"

Follow up, challenge an assumption or explore another approach. When you are ready to build, turn the decision into an intent with /aim start.

Read about AIM Discuss

Measured example · Enigma simulator

Judge the software by what it can prove.

The same GPT-6 Luna model, with and without AIM. The latest assessed AIM delivery scored 96.5 out of 100, compared with 49.8 for GPT-6 Luna without AIM. Both used high reasoning effort and the same Enigma M3 brief, reference checks and scoring weights.

Enigma M3 · Retained GPT-6 Luna results with and without AIM
What was checkedGPT-6 Luna without AIMGPT-6 Luna with AIM
Application assessment49.8 of 10096.5 of 100
Simulator checks passed1 of 123123 of 123
New positive search cases with valid results0 of 99 of 9

Earlier AIM 3.2.0 result: 93.5 of 100. View the original with-and-without-AIM comparison.

Read the evaluation and evidence

Describe the product. Follow the delivery.

Keep your coding agent. Let AIM organize the path from intent to a verified result, and use AIM UI to see the work behind it.

Copy the installation command
  1. Install the skill.

    Choose the terminal command or agent instructions above.

  2. Describe the product.

    Use /aim start "…" with your intent. Ship is the default; ask for Loop when you want recurring feedback.

  3. Let AIM prepare the project.

    AIM reuses current context, calibrates missing or stale knowledge, then configures project agents and their available skills when needed. An empty project starts provisionally. AIM continues with Epics and Stories in the same flow. Open /aim ui to follow delivery and dependencies.

    Use /aim calibrate-repo or /aim configure-agents whenever you want to refresh the setup afterward.

Install from a local checkout

Preview before changes. Clone the source and inspect the installation plan.

git clone --depth 1 https://github.com/joneri/agile-iteration-method.git aim-source
cd aim-source
python3 scripts/aim_install.py --dry-run

Review the plan before using --apply. Read the installer guide.

Already using AIM?

Run /aim upgrade to update AIM-owned files while preserving delivery history. Use /aim calibrate-repo to refresh repository context, /aim configure-agents to refresh specialists and skills, and /aim remember-repo to retain useful project facts. Shared learning is part of ordinary delivery; the old reflect and reflect-all names are retired compatibility aliases.