diff --git a/aws-managed-definitions/README.md b/aws-managed-definitions/README.md index 6b0eb47..dbfbad0 100644 --- a/aws-managed-definitions/README.md +++ b/aws-managed-definitions/README.md @@ -16,8 +16,8 @@ Out-of-box transformation definitions provided by AWS for common migration and u | General | [Codebase Analysis](comprehensive-codebase-analysis/codebase-analysis.md) | Static analysis and documentation for migration planning | | Readiness | [Modernization Readiness Analysis](readiness-analysis/modernization-readiness-analysis.md) | Scans portfolios for cloud-native maturity gaps and maps findings to AWS modernization pathways | | Readiness | [Agentic Readiness Analysis](readiness-analysis/agentic-readiness-analysis.md) | Evaluates whether systems are ready to be safely called by AI agents — covering APIs, identity, state management, human-in-the-loop, and observability | -| Readiness | [Portfolio Modernization Readiness](readiness-analysis/portfolio-modernization-readiness.md) | Aggregates per-repo MOD reports into portfolio-level roadmap and cross-cutting analysis | -| Readiness | [Portfolio Agentic Readiness](readiness-analysis/portfolio-agentic-readiness.md) | Aggregates per-repo ARA reports into portfolio-level cross-cutting analysis | +| Readiness | [Portfolio Modernization Readiness](readiness-analysis/portfolio-modernization-readiness-analysis.md) | Aggregates per-repo MOD reports into portfolio-level roadmap and cross-cutting analysis | +| Readiness | [Portfolio Agentic Readiness](readiness-analysis/portfolio-agentic-readiness-analysis.md) | Aggregates per-repo ARA reports into portfolio-level cross-cutting analysis | ## Directory Structure @@ -44,6 +44,8 @@ aws-managed-definitions/ └── readiness-analysis/ ├── modernization-readiness-analysis.md ├── agentic-readiness-analysis.md - ├── portfolio-modernization-readiness.md - └── portfolio-agentic-readiness.md + ├── portfolio-modernization-readiness-analysis.md + ├── portfolio-agentic-readiness-analysis.md + └── references/ + └── program-library.md # AWS Program & GTM catalog; loaded by the two portfolio TDs ``` diff --git a/aws-managed-definitions/readiness-analysis/agentic-readiness-analysis.md b/aws-managed-definitions/readiness-analysis/agentic-readiness-analysis.md index b7ceba3..015806a 100644 --- a/aws-managed-definitions/readiness-analysis/agentic-readiness-analysis.md +++ b/aws-managed-definitions/readiness-analysis/agentic-readiness-analysis.md @@ -1889,6 +1889,15 @@ The complete report structure, for reference: ``` +### Next Steps — Engagement Programs (Portfolio-Level) + +This per-repo report intentionally does NOT recommend AWS engagement programs (MAP, EBA, AppMod, AI Assessment, SHIP, ACP, etc.). Program eligibility depends on cross-repo scope, customer segment, ARR, and partner context that a single-repo analysis does not have. + +Engagement-level program recommendations are produced by the **Portfolio Agentic Readiness Analysis**, which aggregates all per-repo ARA reports and evaluates them against the shared AWS Program & GTM Library. Run the portfolio TD after all per-repo reports are generated. + +Code-level remediation for this repo is captured in the BLOCKERs, RISKs, and INFO sections above. + + ## Constraints and Guardrails Strictly follow these rules at all times: @@ -2200,8 +2209,8 @@ Ordered by severity (High → Medium → Low) then by section order (AUTH → AP Source: `remediation_roadmap.items[]` **Recommended Actions:** -- Custom Transformation row (always present) -- AWS Programs subsection: EBA, MAP +- AWS Transform Custom row (always present) — expand analysis to additional repositories +- Engagement-program recommendations (MAP, EBA, AppMod, etc.) are NOT produced per-repo; they come from the Portfolio Agentic Readiness Analysis. If no portfolio analysis is available, this subsection shows only the AWS Transform Custom row plus a pointer to run the portfolio TD. **Agent Deployment Recommendation** (footer block): diff --git a/aws-managed-definitions/readiness-analysis/modernization-readiness-analysis.md b/aws-managed-definitions/readiness-analysis/modernization-readiness-analysis.md index 5c561f9..c0c7688 100644 --- a/aws-managed-definitions/readiness-analysis/modernization-readiness-analysis.md +++ b/aws-managed-definitions/readiness-analysis/modernization-readiness-analysis.md @@ -1719,6 +1719,14 @@ The evidence index compiles all file references cited across the detailed findin Include every file path that appears in any finding's evidence field. Group by directory for readability if the list exceeds 20 entries. +### Next Steps — Engagement Programs (Portfolio-Level) + +This per-repo report intentionally does NOT recommend AWS engagement programs (MAP, OLA, AppMod, EBA, VMCCO, etc.). Program eligibility depends on cross-repo scope, customer segment, ARR, on-prem/migration context, and partner relationships that a single-repo analysis does not have. + +Engagement-level program recommendations are produced by the **Portfolio Modernization Readiness Analysis**, which aggregates all per-repo MOD reports and evaluates them against the shared AWS Program & GTM Library. Run the portfolio TD after all per-repo reports are generated. + +Modernization guidance for this repo is captured in the pathway detail subsections, top gaps, and detailed findings above. + ## Constraints and Guardrails @@ -2184,6 +2192,8 @@ The full visual contract is defined inline below — do NOT reference external f - Modernization Recommendation footer block (emoji-headlined with top-3 High-severity recommendations). - Footer line (`Generated by AWS Transform · Modernization Readiness Analysis Report`). +> **Note on the "programs" tab / Recommended Actions:** In the per-repo MOD report these render modernization pathways (Move to X) and pathway-mapped learning materials only — NOT AWS engagement programs (MAP, OLA, AppMod, etc.). Engagement-program recommendations are produced exclusively by the Portfolio Modernization Readiness Analysis from the shared AWS Program & GTM Library. The per-repo `recommended_actions` content is limited to AWS Transform Custom (expand-analysis) plus a pointer to run the portfolio TD. + **HTML-escaping discipline.** Every data value rendered in HTML originates from the JSON artifact (MD prose is NOT part of the HTML round-trip contract). All attacker-controlled strings MUST be HTML-escaped before embedding: repo names, evidence file paths, finding titles, finding descriptions, recommendation text, pathway names, and any other string that originates from repository content or from free-text fields in `additionalPlanContext`. Escape `<`, `>`, `&`, `"`, `'` at render time. This is the same escaping discipline applied to the ARA HTML artifact. #### Slug Derivation diff --git a/aws-managed-definitions/readiness-analysis/portfolio-agentic-readiness-analysis.md b/aws-managed-definitions/readiness-analysis/portfolio-agentic-readiness-analysis.md index ab4a8c7..7e6a28b 100644 --- a/aws-managed-definitions/readiness-analysis/portfolio-agentic-readiness-analysis.md +++ b/aws-managed-definitions/readiness-analysis/portfolio-agentic-readiness-analysis.md @@ -19,7 +19,7 @@ The transformation follows a 9-step pipeline: 6. **Cross-Cutting RISKs** (Step 4b): Identify RISKs meeting the scaling threshold (max(3, 33% of applicable repos)), split by RISK-SAFETY and RISK-QUALITY tiers 7. **Dependency Mapping** (Step 5): Construct service dependency map from dependency_overrides 8. **Remediation Guidance** (Step 6): Generate portfolio-level remediation for cross-cutting BLOCKERs -9. **Agentic Programs** (Step 7): Recommend AI DLC, AXE, Innovation EBA where triggered +9. **Agentic Programs** (Step 7): Recommend AI DLC, AXE, Innovation EBA, and programs from the shared AWS Program & GTM Library (`references/program-library.md`) where triggered 10. **Portfolio-Level Questions** (Step 8): Evaluate PORT-ARA-Q1 through PORT-ARA-Q5 — capabilities only visible across multiple repos The output is a **four-artifact bundle** containing: @@ -36,7 +36,7 @@ The MD report contains: - Cross-cutting RISKs (same risk question appearing in max(3, 33% of applicable repos)) - Service dependency map from dependency_overrides - Portfolio-level remediation guidance for cross-cutting blockers -- Agentic program recommendations (AI DLC, AXE, Innovation EBA) +- Agentic program recommendations (AI DLC, AXE, Innovation EBA, plus relevant AWS Program & GTM Library programs) - Service-by-service summary (repo name, profile, blocker count, risk count) This portfolio TD focuses exclusively on cross-cutting BLOCKER/RISK identification across multiple ARA reports. It does not include modernization pathways, roadmap phases, numeric scores, technology preferences, or resource allocation recommendations. @@ -547,39 +547,33 @@ If `context` was provided in additionalPlanContext, use it to tailor the remedia ### Step 7: Recommend Agentic Programs -Based on the portfolio-wide analysis findings, recommend relevant agentic enablement programs and engagement workshops. +Based on the portfolio-wide analysis findings, recommend relevant agentic enablement programs and AWS GTM programs from the shared **AWS Program & GTM Library** in `references/program-library.md`. Load that file when evaluating recommendations — it is the authoritative catalog and contains the full agent instructions (signal patterns, exclusions, qualification criteria, prioritization, grouping, status filtering, and a reasoning checklist), including the three ARA agentic anchor programs (AI DLC, AXE, Innovation EBA). Include a program only if its trigger condition is met. If no programs are triggered, include the brief note in 7.2 instead. -#### 7.1 Program Catalog and Trigger Logic +#### 7.1 Evaluating the Library from ARA Findings -Evaluate each program against its trigger condition. Include a program in the recommendations only if its trigger condition is met. Multiple programs can be triggered simultaneously — they serve different purposes and are not mutually exclusive. +Use the `[ARA-anchor]`, `[ARA]`, and `[ARA+MOD]`-tagged programs in the library and map ARA's vocabulary as described in the library's "Mapping findings to triggers" section: -| Program | Description | Trigger Condition | How to Evaluate | -|---------|-------------|-------------------|-----------------| -| **AI DLC (AI Driven Development Lifecycle)** | Workshop for adopting the AI Driven Development Lifecycle, emphasizing two dimensions: (1) AI Powered Execution with Human Oversight — AI creates detailed work plans, seeks clarification, and defers critical decisions to humans who possess contextual understanding and business knowledge; (2) Dynamic Team Collaboration — as AI handles routine tasks, teams unite in collaborative spaces for real-time problem solving, creative thinking, and rapid decision-making, shifting from isolated work to high-energy teamwork that accelerates innovation and delivery. | Portfolio shows teams without established AI-assisted development practices, or when engineering maturity findings indicate manual development workflows that could benefit from AI-driven automation. | Check ENG section findings across the portfolio. If 50%+ of services have RISK-QUALITY or worse findings on ENG-Q1 (Infra Governance), ENG-Q2 (CI/CD + Contracts), or ENG-Q3 (Rollback), recommend AI DLC. Also recommend if the portfolio context mentions desire for AI-assisted development practices. | -| **AXE (Agent Experience Engagement)** | A strategic methodology that helps enterprises implement agentic AI solutions by starting with desired customer and employee experience and working backwards to define AI agents and technical architecture. Built on the proven D2E methodology with 580+ successful engagements, AXE delivers a six-phase framework covering business process mapping, task identification, evaluation metrics, data architecture, governance, and guardrails. The Guardrails & Boundaries phase aligns with ARA, which evaluates whether target systems have the technical controls needed to safely support autonomous agents. Together, they provide a complete assess-to-implement pathway: ARA validates system readiness while AXE designs the agent experience and implementation roadmap. | Portfolio shows 3+ services in "Pilot-Ready" or "Agent-Ready" state, or when business has defined customer/employee experience goals but lacks technical implementation roadmap. | Count services with profile Agent-Ready or Pilot-Ready. If count >= 3, recommend AXE. Also recommend if the portfolio `context` describes experience-level goals (e.g., "customer support agent", "employee productivity") without a corresponding technical implementation plan. | -| **Innovation EBA** (AIML-GenAI) | A 3-day sprint-based, interactive engagement that enables customers to build AI/ML models or deliver a Generative AI use case in an accelerated fashion using AWS services and prescriptive guidance. Targets customers with higher cloud maturity who want to leverage AI/ML to solve business problems and innovate faster. Follows the 4-step EBA framework (Executive Alignment → Readiness → Accelerate → Transform At Scale) with workstreams including Foundations, Data Engineering, GenAI Build/Evaluate, UI Integration, ML Ops, and Command Center. Develops customer skills through learning-by-doing and builds/accelerates a GenAI use case pipeline based on a blueprint developed during the EBA. | Portfolio context indicates AI/ML or GenAI is a strategic imperative, executive sponsorship exists, use cases deliver critical business value, data strategy exists, and the customer is committed to production deployment within ~90 days. Additionally, the portfolio should show a backlog of AIML-GenAI use cases and the customer team has some AIML-GenAI skills committed to upskilling. | Check portfolio `context` for signals of: (1) AI/ML or GenAI as strategic priority, (2) executive sponsorship mentioned, (3) existing data and data strategy (e.g., services with established data pipelines, DynamoDB/Aurora/S3 data stores), (4) use cases in categories like customer experience (chatbots, post-call analytics, personalization), productivity (intelligent search, summarization, code generation), business operations (IDP, fraud detection, predictive maintenance), or content creation. Also recommend if 3+ services have production-ready data stores AND the portfolio context describes GenAI ambitions beyond what AXE alone covers. | +- **Agentic anchor programs** (AI DLC, AXE, Innovation EBA) — defined in the library's "Agentic Enablement Programs (ARA Anchors)" section with their own signal patterns and evaluation logic. These are ARA-only and group under Engagement Models. +- **"3+ High-severity findings across any dimension"** → count unified `High` findings (cross-cutting BLOCKERs from Step 4, plus conditional BLOCKERs resolved as High) across the portfolio. +- **Readiness profiles** → use the exact ARA profile names: `Agent-Ready`, `Pilot-Ready`, `Pilot-Ready (Safety Concerns)`, `Remediation Required`, `Not Agent-Integrable`. Use the profile distribution from the executive dashboard (Step 3). +- **A dimension "showing problems"** → that ARA category has 2+ `Medium`/`High` findings (e.g., SHIP triggers when `Authentication & Authorization` has 2+ Medium/High findings; Well-Architected Review when `Engineering Maturity` or `Observability` has 2+ Medium+ findings). +- **Customer segment** (Enterprise / SMB / ISV / Startup / WWPS) → infer from the portfolio `context` and `service_inventory`. -#### 7.2 Program Sequencing Guidance +Apply the library's selection rules: cap recommendations at **3–5**, prioritize by direct finding match → segment fit → entry-point-before-follow-on, group as **Funded Programs → Engagement Models → GTM Motions**, sequence logically (Assessment → Funding → Execution → Optimization, and for the anchor programs AI DLC → AXE → Innovation EBA), and never recommend `Retiring` or not-yet-imminent `Launching` programs. Run the library's reasoning checklist before finalizing. -When multiple programs are triggered, recommend them in this order: - -1. **AI DLC** (if triggered) — Run first to establish AI-driven development practices before agentic work -2. **AXE** (if triggered) — Run after AI DLC to design the agent experience -3. **Innovation EBA** (if triggered) — Run when the customer is ready to accelerate an AI/ML or GenAI use case into production (can run in parallel with AXE if use cases are independent) - -If only one program is triggered, recommend it directly without sequencing context. - -#### 7.3 Program Recommendations Output +#### 7.2 Program Recommendations Output For each triggered program: -- **Program name** — AI DLC, AXE, or Innovation EBA +- **Program name** — e.g., AI DLC, AXE, Innovation EBA, or any library program (MAP, AI Assessment, SHIP, ACP, etc.) - **Relevance** — Why this program is recommended based on portfolio findings -- **Trigger findings** — Specific portfolio metrics that triggered the recommendation +- **Trigger findings** — Specific portfolio metrics that triggered the recommendation (using ARA profile/severity language) - **What it provides** — Brief description of the program's value - **Suggested timing** — When to run relative to other programs or analysis phases - **Next step** — Recommended action (e.g., "Request engagement via AWS Solutions Architect") +Group the rendered output under **Funded Programs → Engagement Models → GTM Motions** (the three agentic anchor programs are Engagement Models). Cap at 3–5 total. Do not expose any internal numeric maturity score. + If no programs are triggered, include a brief note: "No specific agentic program recommendations based on current findings. As the portfolio's agentic readiness improves, re-assess to identify program eligibility." @@ -910,11 +904,27 @@ Group related BLOCKERs that can be addressed together.> > These are engagement-level recommendations based on the portfolio's agentic readiness > profile. Discuss with your AWS Solutions Architect to determine eligibility and timing. +> Recommendations are capped at 3–5 and grouped by type. (No internal maturity scores are exposed.) + +#### Funded Programs + +| Program | Relevance | Trigger Findings | Suggested Timing | Next Step | +|---------|-----------|-----------------|------------------|-----------| +| | | | | | + +#### Engagement Models | Program | Relevance | Trigger Findings | Suggested Timing | Next Step | |---------|-----------|-----------------|------------------|-----------| | | | | | | -| | + +#### GTM Motions + +| Program | Relevance | Trigger Findings | Suggested Timing | Next Step | +|---------|-----------|-----------------|------------------|-----------| +| | | | | | + + ### Program Details @@ -1102,7 +1112,7 @@ The Portfolio ARA JSON artifact MUST emit these top-level keys in the order show | `findings[]` | Per-repo findings propagated up. Each entry is a 12-field per-repo finding plus `repo_name`. One entry per (repo × question_id). Used by webapp Findings tab. | | `cross_cutting_findings[]` | Portfolio-aggregated findings where the same question_id fires at the same tier across 2+ repos (BLOCKER) or meets the scaling threshold (RISK, max(3, 33% of applicable repos)). One entry per question_id. Used by webapp Cross-Cutting view. | | `remediation_roadmap` | See §"Remediation Roadmap" below | -| `recommended_actions[]` | Canonical agentic programs (AI DLC, AXE, Innovation EBA) | +| `recommended_actions[]` | Agentic anchor programs (AI DLC, AXE, Innovation EBA) plus triggered AWS Program & GTM Library programs, grouped Funded → Engagement → GTM | | `portfolio_level_findings[]` | PORT-ARA-Q* cross-portfolio findings | | `dependency_map` | Dependency map | @@ -1246,13 +1256,15 @@ The ARA execution-sequencing narrative (Phase 1 BLOCKER resolution, Phase 2 RISK ### Recommended Actions -The Portfolio ARA JSON emits `recommended_actions[]` as an array of agentic-program entries. Minimum-set coverage: +The Portfolio ARA JSON emits `recommended_actions[]` as an array of program entries. Entries come from two sources: the three ARA-specific agentic anchor programs, and triggered programs from the AWS Program & GTM Library (`references/program-library.md`). The anchor programs always appear (with their resolved `status`); library programs appear only when triggered. -| `id` | `name` | `acronym` | `type` | -|---|---|---|---| -| `ai-dlc` | AI Driven Development Lifecycle | AI DLC | workshop | -| `axe` | Agent Experience Engagement | AXE | program | -| `innovation-eba` | Innovation EBA | Innovation EBA | program | +Anchor program coverage: + +| `id` | `name` | `acronym` | `type` | `group` | +|---|---|---|---|---| +| `ai-dlc` | AI Driven Development Lifecycle | AI DLC | workshop | Engagement Models | +| `axe` | Agent Experience Engagement | AXE | program | Engagement Models | +| `innovation-eba` | Innovation EBA | Innovation EBA | program | Engagement Models | Each entry carries: @@ -1262,6 +1274,7 @@ Each entry carries: "name": "Agent Experience Engagement", "acronym": "AXE", "type": "program", + "group": "Engagement Models", "status": "Triggered", "trigger_reason": "19 BLOCKERs across authentication and data classification; structured implementation engagement recommended.", "suggested_timing": "After initial triage", @@ -1270,9 +1283,9 @@ Each entry carries: } ``` -`status` ∈ {Triggered, Applicable, Not Triggered}. `trigger_reason` is non-empty prose explaining why the program fires. +`group` ∈ {Funded Programs, Engagement Models, GTM Motions}. `status` ∈ {Triggered, Applicable, Not Triggered}. `trigger_reason` is non-empty prose explaining why the program fires (using ARA profile/severity language, never an internal numeric score). The total triggered set is capped at 3–5 per the library's selection rules; library entries carry `acronym: null` where the program has no acronym. -The MD artifact renders this under an H2 heading **"## Recommended Actions"**. The "## Agentic Program Recommendations" label is retained as an H3 subheading under that H2 to preserve rich program prose without creating duplicate H2s. +The MD artifact renders this under an H2 heading **"## Recommended Actions"**, grouped Funded Programs → Engagement Models → GTM Motions. The "## Agentic Program Recommendations" label is retained as an H3 subheading under that H2 to preserve rich program prose without creating duplicate H2s. --- @@ -1294,7 +1307,7 @@ Subsections: 1. **Portfolio Status** — "Out of {N} repositories analyzed, {A} are agent-ready and can integrate with AI agents immediately, {B} are pilot-ready for read-only operations, and {C} require remediation before agent deployment. The analysis identified {H} high severity findings (blockers) and {M} medium severity findings (risks)." 2. **Key Findings** — Top 3 cross-cutting high severity areas as bullet list with repo counts 3. **Remediation Plan** — 3-phase numbered list with finding counts and timelines -4. **Recommended Actions** — Bullet list of triggered programs (AI DLC, AXE, Innovation EBA) with reasons +4. **Recommended Actions** — Bullet list of triggered programs (agentic anchors AI DLC/AXE/Innovation EBA plus any triggered AWS Program & GTM Library programs) with reasons **Stats Card Row** (4 cards): @@ -1347,10 +1360,12 @@ Source: `remediation_roadmap.items[]` grouped by phase #### Recommended AWS Programs Tab -Table columns: `Program`, `Description`, `Why Recommended`, `Duration` +Table columns: `Program`, `Group`, `Description`, `Why Recommended`, `Duration` - Source: `recommended_actions[]` filtered to `status == "Triggered"` -- Canonical programs: AI DLC, AXE, Innovation EBA +- Group values: `Funded Programs`, `Engagement Models`, `GTM Motions` — render as grouped sections in that order (or a Group column), omitting any group with no triggered programs +- The triggered set can include ANY `[ARA]` / `[ARA+MOD]` / `[ARA-anchor]` program from the AWS Program & GTM Library — not just the agentic anchors. Examples that may appear from ARA findings: MAP / MAP for AI Modernization (Funded), AI Assessment Program (Funded), SHIP (Non-Funded → grouped under Funded Programs per the library's grouping rule), Well-Architected Review, AI DLC / AXE / Innovation EBA / ACP / GenAI Innovation Center (Engagement Models), AgentStorming Workshop, Agentic-led Modernization Sales Play (GTM Motions) +- Capped at 3–5 total per the library's selection rules. Do not display any internal numeric maturity score. #### Footer diff --git a/aws-managed-definitions/readiness-analysis/portfolio-modernization-readiness-analysis.md b/aws-managed-definitions/readiness-analysis/portfolio-modernization-readiness-analysis.md index 29ac18e..57e275b 100644 --- a/aws-managed-definitions/readiness-analysis/portfolio-modernization-readiness-analysis.md +++ b/aws-managed-definitions/readiness-analysis/portfolio-modernization-readiness-analysis.md @@ -22,7 +22,7 @@ The transformation follows these implementation steps: 9. **Dependency-Aware Phased Roadmap** (Step 6): Generate 4-phase roadmap with dependency-based service ordering 10. **Pathway Aggregation** (Step 7): Aggregate pathway triggers across the portfolio 11. **Synthesis** (Step 8): Integration opportunities, risk analysis, resource allocation -12. **AWS Programs & Engagement Recommendations** (Step 9): Recommend MAP, MMP, WAMP, EBA, OLA, VMP, ISV WMP where triggered +12. **AWS Programs & Engagement Recommendations** (Step 9): Recommend programs and GTM motions from the shared AWS Program & GTM Library (`references/program-library.md`) where triggered 13. **Portfolio-Level Questions** (Step 10): Evaluate PORT-MOD-Q1 through PORT-MOD-Q5 — capabilities only visible across multiple repos The output is a **four-artifact bundle** (per the Four-Artifact Output Contract below) containing: @@ -42,7 +42,7 @@ The MD report contains: - Integration opportunities - Risk analysis with likelihood-impact matrix - Resource allocation recommendations -- AWS Programs & Engagement Recommendations (MAP, OLA, MMP, VMP, WAMP, EBA, ISV WMP) +- AWS Programs & Engagement Recommendations (from the shared AWS Program & GTM Library — MAP, OLA, AppMod, EBA, VMCCO, SHIP, etc., where triggered) - Learning materials mapped to portfolio skill gaps - Service-by-service summary @@ -1019,19 +1019,20 @@ For each identified risk: > **This section appears ONLY in portfolio reports, NEVER in individual reports.** AWS programs are engagement-level decisions scoped to the customer's overall estate, not per-repo. The portfolio view has the right scope to make these recommendations. -Based on the portfolio-wide analysis findings from previous steps, evaluate each of the 8 AWS engagement programs below against its trigger condition. Include a program in the recommendations only if its trigger condition is met. If no programs are triggered, include a brief note instead. +Based on the portfolio-wide analysis findings from previous steps, recommend relevant AWS programs and GTM motions from the shared **AWS Program & GTM Library** in `references/program-library.md`. Load that file when evaluating recommendations — it is the authoritative catalog and contains the full agent instructions (signal patterns, exclusions, qualification criteria, prioritization, grouping, status filtering, and a reasoning checklist). Include a program only if its trigger condition is met. If no programs are triggered, include the brief note in 9.2 instead. -#### 9.1 Programs Catalog and Trigger Logic +#### 9.1 Evaluating the Library from MOD Findings -| Program | Acronym | Trigger Condition | How to Evaluate | -|---------|---------|-------------------|-----------------| -| Migration Acceleration Program | MAP | Portfolio has 3+ repos with workloads NOT yet on AWS (on-premises or another cloud provider) | Check individual report findings for non-AWS hosting signals: (1) no AWS IaC detected (no CDK, CloudFormation, or Terraform with AWS provider), (2) no AWS SDK references in application code, (3) deployment targets referencing non-AWS infrastructure (Azure, GCP, bare-metal, VMware, on-prem data centers, physical server configs), (4) self-hosted CI/CD with no cloud provider integration (Jenkins on-prem, GitLab self-hosted without cloud runners). If 3+ repos show these signals, recommend MAP. MAP is ONLY for net-new workloads migrating to AWS — it does NOT apply to workloads already running on AWS in any form, including EC2-hosted legacy applications. A PHP monolith on EC2 is already on AWS and does not qualify for MAP regardless of how unmodernized it is. | -| Optimization and Licensing Analysis | OLA | Any repo has Oracle, SQL Server, VMware, or commercial license findings | Check individual report findings for DATA-Q4 (stored procedures / commercial SQL) and INF-Q2 (managed DB) scores. If any repo's findings mention Oracle, SQL Server, VMware, or other commercial database/license references, recommend OLA. | -| Microsoft Modernization Program | MMP | Any repo has .NET or Windows workloads detected | Check APP-Q1 (Programming Languages) findings. If any repo uses C#, .NET, ASP.NET, or VB.NET, recommend MMP. | -| VMware Modernization Program | VMP | Any repo has VMware references in IaC or deployment configs | Check individual report findings for VMware, vSphere, ESXi, or vCenter references. If found, recommend VMP. | -| Windows App Modernization Program | WAMP | Any repo has Windows-based deployment targets | Check individual report findings for Windows Server, IIS, or Windows-specific deployment references. If found, recommend WAMP. | -| Experience-Based Acceleration | EBA | Portfolio has 2+ repos with triggered pathways AND overall score < 3.0 | Count repos with at least one triggered pathway AND overall score < 3.0. If count >= 2, recommend EBA. Specify which pathway(s) are most prevalent for the EBA engagement focus. | -| ISV Workload Migration Program | ISV WMP | Portfolio includes ISV or third-party software workloads | Check findings for references to third-party commercial software, ISV applications, or packaged software deployments. If found, recommend ISV WMP. | +Use the `[MOD]` / `[ARA+MOD]`-tagged programs in the library and map MOD's vocabulary as described in the library's "Mapping findings to triggers" section: + +- **Pathways** → use the exact MOD pathway names (`Move to Cloud Native`, `Move to Containers`, `Move to Open Source`, `Move to Managed Databases`, `Move to Managed Analytics`, `Move to Modern DevOps`, `Move to AI`). Use the aggregated pathway plan from Step 7. +- **"Multiple High-severity findings"** → count unified `High` findings across services (from cross-cutting analysis). **"High Effort"** → the finding `effort` field (`High`/`Medium`/`Low`). +- **Classification / category health** → use `severity_status` (`Ready`/`Needs Work`/`Critical`) and `score_rating` (`Mature`/`Partial`/`Needs Work`/`Not Ready`). **Do NOT use or expose the internal 1–4 score** anywhere in the recommendations output. +- **Workload-specific triggers** (VMware, Windows/.NET, Oracle, SAP, Kafka, mainframe) → use the technology stack detected during discovery and the per-service findings. +- **On-prem / migration triggers** (MAP, OLA, Migration Evaluator, VMCCO) → MOD scope is AWS-targeting workloads and excludes on-prem. Trigger these from portfolio/service `context` references (on-prem, data center, VMware estate, "migrating from…") or IaC evidence of non-AWS/VMware providers (`vsphere_*`, bare-metal) — NOT from MOD findings about workloads already on AWS. A legacy app already on EC2 does not qualify for MAP. +- **Customer segment** (Enterprise / SMB / ISV / Startup / WWPS) → infer from portfolio `context` and `service_inventory`. + +Apply the library's selection rules: cap recommendations at **3–5**, prioritize by direct finding match → segment fit → entry-point-before-follow-on, group as **Funded Programs → Engagement Models → GTM Motions**, sequence logically (Assessment → Funding → Execution → Optimization), and never recommend `Retiring` or not-yet-imminent `Launching` programs. Run the library's reasoning checklist before finalizing. #### 9.2 Program Recommendations Output @@ -1039,10 +1040,12 @@ For each triggered program: - **Program name and acronym** - **Relevance** — Why this program is recommended based on portfolio findings -- **Trigger findings** — Specific portfolio metrics that triggered the recommendation (e.g., "4 of 6 services have overall score < 2.5") +- **Trigger findings** — Specific portfolio metrics that triggered the recommendation (using severity/classification language, never the internal numeric score — e.g., "4 of 6 services classified Remediation Required", "Move to Containers triggered for 3 services") - **What it provides** — Brief description of the program's value - **Next step** — Recommended action (e.g., "Request MAP engagement via AWS Solutions Architect") +Group the rendered output under **Funded Programs → Engagement Models → GTM Motions**. Cap at 3–5 total. + If no programs are triggered, include: "No specific AWS program recommendations based on current findings. As the portfolio evolves, re-assess to identify program eligibility." @@ -1725,11 +1728,29 @@ in exactly one column per pathway row. ### Recommended Programs +> Recommendations are capped at 3–5 and grouped by type. Trigger findings use severity and +> classification language only — the internal 1–4 maturity score is never exposed here. + +#### Funded Programs + +| Program | Acronym | Relevance | Trigger Findings | Next Step | +|---------|---------|-----------|-----------------|-----------| +| | | | | | + +#### Engagement Models + | Program | Acronym | Relevance | Trigger Findings | Next Step | |---------|---------|-----------|-----------------|-----------| | | | | | | -> If no programs are triggered: +#### GTM Motions + +| Program | Acronym | Relevance | Trigger Findings | Next Step | +|---------|---------|-----------|-----------------|-----------| +| | | | | | + +> Omit any group heading that has no triggered programs. +> If no programs are triggered at all: > "No specific AWS program recommendations based on current findings. As the > portfolio evolves, re-assess to identify program eligibility." @@ -2044,7 +2065,7 @@ The Portfolio MOD JSON artifact MUST emit these top-level keys in the order show | `repositories[]` | Per-repo roll-up | | `findings[]` | Lightweight portfolio finding index. See "Portfolio `findings[]` entry shape" below. | | `remediation_roadmap` | See §"Remediation Roadmap" — grouping `pathway` | -| `recommended_actions[]` | Canonical AWS programs (MAP, MMP, WAMP, EBA, OLA, VMP, ISV WMP) | +| `recommended_actions[]` | Triggered AWS programs from the AWS Program & GTM Library (`references/program-library.md`), grouped Funded → Engagement → GTM | | `pathways[]` | All 7 AWS Modernization Pathways with JSON-pointer back-references; see §"Pathways Aggregation" | | `dependency_map` | Portfolio dependency map | | `roadmap_phases[]` | Optional, additive | @@ -2200,19 +2221,21 @@ MD rendering under an H2 heading **"## Remediation Roadmap"** matching the webap ### Recommended Actions -The Portfolio MOD JSON emits `recommended_actions[]` with minimum-set coverage: +The Portfolio MOD JSON emits `recommended_actions[]`. Programs are drawn from the AWS Program & GTM Library (`references/program-library.md`); each entry carries a `group` field (`Funded Programs` / `Engagement Models` / `GTM Motions`) so the webapp can render the grouped output. The library is the authoritative source for the program set, trigger logic, and grouping. -| `id` | `name` | `acronym` | `type` | -|---|---|---|---| -| `map` | Migration Acceleration Program | MAP | program | -| `mmp` | Microsoft Modernization Program | MMP | program | -| `wamp` | Windows App Modernization Program | WAMP | program | -| `eba` | Experience-Based Acceleration | EBA | program | -| `ola` | Optimization and Licensing Analysis | OLA | program | -| `vmp` | VMware Migration Program | VMP | program | -| `isv-wmp` | ISV Workload Migration Program | ISV WMP | program | +Each entry envelope: + +| Field | Description | +|---|---| +| `id` | Stable slug for the program (e.g., `map`, `ola`, `appmod-assessment`, `ship`) | +| `name` | Full program name (e.g., Migration Acceleration Program) | +| `acronym` | Program acronym where one exists, else `null` | +| `type` | `program` | +| `group` | `Funded Programs` / `Engagement Models` / `GTM Motions` | +| `status` | `Triggered` / `Applicable` / `Not Triggered` | +| `trigger_reason` | Non-empty prose stating the finding(s) that triggered (or did not trigger) the program — using severity/classification language, never the internal 1–4 score | -Same entry envelope as Portfolio ARA. `status ∈ {Triggered, Applicable, Not Triggered}` with non-empty `trigger_reason`. Emitted under the H2 heading **"## Recommended Actions"**. +The triggered set is capped at 3–5 per the library's selection rules. Same entry envelope as Portfolio ARA. Emitted under the H2 heading **"## Recommended Actions"**. --- @@ -2332,11 +2355,13 @@ Source: `remediation_roadmap.items[]` grouped by phase + `roadmap_phases[]` #### AWS Programs & Engagement Recommendations -Table columns: `Program`, `Relevance`, `What You Get`, `Suggested Timing` +Table columns: `Program`, `Group`, `Relevance`, `What You Get`, `Suggested Timing` - Source: `recommended_actions[]` +- Group values: `Funded Programs`, `Engagement Models`, `GTM Motions` — render as grouped sections in that order (or a Group column), omitting any group with no triggered programs - Relevance values: `Triggered`, `Applicable`, `Not Triggered` -- Show ALL programs (not just triggered) +- The triggered set can include ANY `[MOD]` / `[ARA+MOD]` program from the AWS Program & GTM Library. Examples that may appear from MOD findings: MAP, OLA, AMA, AppMod Assessment / PoC Funding (Funded), VMCCO, Well-Architected Review (Non-Funded → grouped under Funded Programs per the library's grouping rule), AML / Immersion Days / ProServe Residency (Engagement Models), ModNet / Agentic-led Modernization Sales Play (GTM Motions) +- Show the recommended set only (capped at 3–5 per the library's selection rules) — do NOT render the full program catalog (88 programs). Do not display any internal numeric maturity score. #### Pathways Tab (MOD-only — ARA does not have this) diff --git a/aws-managed-definitions/readiness-analysis/references/program-library.md b/aws-managed-definitions/readiness-analysis/references/program-library.md new file mode 100644 index 0000000..07fb1dd --- /dev/null +++ b/aws-managed-definitions/readiness-analysis/references/program-library.md @@ -0,0 +1,548 @@ +# AWS Program & GTM Library + +> **Purpose:** This reference is loaded by the Portfolio Agentic Readiness (portfolio-ara) and Portfolio Modernization Readiness (portfolio-mod) Task Definitions during their program-recommendation step. The analysis agent uses it to recommend relevant AWS programs and GTM motions in the "Next Steps / Recommended Programs" section of the generated portfolio report, based on the actual findings already produced. +> +> **Scope:** Program recommendations are an engagement-level decision and are produced ONLY by the two portfolio TDs — never by the per-repo ARA or MOD TDs. The portfolio view has the cross-repo and customer-segment context required to qualify these programs. +> +> **Source:** APN Programs Roadmap (Apr 2026) + AWS Highspot (Jun 2026). Compiled by Kevin Shin, 2026-06-03. Programs indexed: 88 — Tier 1 detailed: 35 (32 from the source library + 3 ARA agentic anchor programs); Tier 2 compact index: 53. + +--- + +## How the Agent Uses This File + +After the portfolio analysis has produced its findings (cross-cutting BLOCKERs/RISKs and readiness profiles for ARA; aggregated pathways, severity counts, and classification tiers for MOD), evaluate which programs are relevant and emit a short recommendation list. Follow these rules exactly: + +1. **Recommend only when qualification criteria are met.** Each program lists signal patterns, "DO NOT recommend when" exclusions, and qualification criteria. A program is eligible only when its signal patterns match the findings AND none of its exclusions apply. +2. **Cap at 3–5 recommendations per report.** Never exceed 5. Fewer is better than overwhelming the seller. +3. **Prioritize in this order:** + 1. Direct finding match (the strongest signal pattern matches an actual finding) + 2. Customer segment fit (Enterprise / SMB / ISV / Startup / WWPS — inferred from portfolio `context` and `service_inventory`) + 3. Entry-point programs (no prerequisites) before follow-on programs (with prerequisites) +4. **Group recommendations under three headings, in this order:** `Funded Programs` → `Engagement Models` → `GTM Motions`. (Partner/ISV, Startup, Training, and Workload-Specific programs map into the closest of these three groups — funded offers go under Funded Programs, hands-on/consulting offers under Engagement Models, sales plays and positioning under GTM Motions.) +5. **Never recommend programs marked `Retiring`** and never recommend programs marked `Launching` unless the launch is imminent (see Status Key). +6. **Sequence logically:** Assessment → Funding → Execution → Optimization. Do not recommend a follow-on program without surfacing its prerequisite. +7. **Do not expose internal scoring.** The MOD internal 1–4 maturity score is internal only. When citing MOD evidence in a recommendation, reference unified severity (`High` / `Medium` / `Low`), `severity_status` (`Ready` / `Needs Work` / `Critical`), `score_rating` (`Mature` / `Partial` / `Needs Work` / `Not Ready`), or pathway/profile names — never the numeric score. +8. **Run the reasoning checklist** (at the end of this file) before finalizing the list. + +### Mapping findings to triggers — vocabulary alignment + +This library is consumed by two different analyses with different finding vocabularies. When a signal pattern below references a "finding" or "dimension," interpret it against the actual emitted vocabulary: + +**ARA (portfolio-agentic-readiness):** +- ARA emits findings with unified severity `High` / `Medium` / `Low` and native severity `BLOCKER` / `RISK-SAFETY` / `RISK-QUALITY` / `INFO`. +- ARA readiness profiles are exactly: `Agent-Ready`, `Pilot-Ready`, `Pilot-Ready (Safety Concerns)`, `Remediation Required`, `Not Agent-Integrable`. +- ARA category (dimension) display names are exactly: `API Surface`, `Authentication & Authorization`, `State Management`, `Human-in-the-Loop`, `Data Accessibility`, `Discovery & Documentation`, `Observability`, `Engineering Maturity`. +- "3+ High-severity findings across any dimension" → count unified `High` findings (BLOCKERs + conditional BLOCKERs resolved as High) across the portfolio / a service. +- A dimension "showing problems" → that category has 2+ `Medium`/`High` findings. ARA has no "Blocked"/"Needs Work" labels (those are MOD-only); translate accordingly. + +**MOD (portfolio-modernization-readiness):** +- MOD emits findings with unified severity `High` / `Medium` / `Low`; per-category `severity_status` is `Ready` / `Needs Work` / `Critical`; `score_rating` is `Mature` / `Partial` / `Needs Work` / `Not Ready`. +- MOD pathway names are exactly: `Move to Cloud Native`, `Move to Containers`, `Move to Open Source`, `Move to Managed Databases`, `Move to Managed Analytics`, `Move to Modern DevOps`, `Move to AI`. +- MOD finding `effort` field is `High` / `Medium` / `Low` — use it for "High Effort" signal patterns. +- **On-prem / VMware / data-center triggers:** MOD analyzes workloads already targeting AWS and explicitly excludes on-prem from scope. Programs whose signal is "on-prem workloads" (OLA, Migration Evaluator, VMCCO, MAP) must trigger from portfolio/service `context` references (e.g., "running on EC2 from a legacy data center", "VMware estate", "migrating from on-prem") or from IaC evidence of non-AWS/VMware providers (`vsphere_*`, bare-metal configs) — NOT from MOD findings about workloads that already run on AWS. + +`[ARA]`, `[MOD]`, or `[ARA+MOD]` tags on each program indicate which analysis the program is most relevant to. A program may be surfaced by either portfolio TD when tagged for both. Programs tagged `[ARA-anchor]` are agentic enablement programs surfaced only by the portfolio ARA TD. + +--- + +## AGENTIC ENABLEMENT PROGRAMS (ARA Anchors) + +> These three programs are surfaced **only by the portfolio ARA TD**. They are agentic-readiness-specific and have no MOD equivalent. They group under **Engagement Models** in the rendered output. When multiple are triggered, sequence them: AI DLC → AXE → Innovation EBA (Innovation EBA may run in parallel with AXE when use cases are independent). + +### AI DLC (AI Driven Development Lifecycle) `[ARA-anchor]` +- **Description:** Workshop for adopting the AI Driven Development Lifecycle, emphasizing two dimensions: (1) AI Powered Execution with Human Oversight — AI creates detailed work plans, seeks clarification, and defers critical decisions to humans who possess contextual understanding and business knowledge; (2) Dynamic Team Collaboration — as AI handles routine tasks, teams unite in collaborative spaces for real-time problem solving, creative thinking, and rapid decision-making, shifting from isolated work to high-energy teamwork that accelerates innovation and delivery. +- **Signal patterns:** Portfolio shows teams without established AI-assisted development practices, or engineering-maturity findings indicate manual development workflows that could benefit from AI-driven automation. +- **How to evaluate:** Check `Engineering Maturity` (ENG) findings across the portfolio. If 50%+ of services have a `Medium`+ finding on ENG-Q1 (Infra Governance), ENG-Q2 (CI/CD + Contracts), or ENG-Q3 (Rollback), recommend AI DLC. Also recommend if the portfolio `context` mentions a desire for AI-assisted development practices. +- **Delivers:** Adoption of AI-driven development practices and team collaboration model. +- **Segment:** All. +- **Sequencing:** Run first — establishes AI-driven development practices before agentic work. +- **Pairs with:** AXE, Innovation EBA. + +### AXE (Agent Experience Engagement) `[ARA-anchor]` +- **Description:** A strategic methodology that helps enterprises implement agentic AI solutions by starting with desired customer and employee experience and working backwards to define AI agents and technical architecture. Built on the proven D2E methodology with 580+ successful engagements, AXE delivers a six-phase framework covering business process mapping, task identification, evaluation metrics, data architecture, governance, and guardrails. The Guardrails & Boundaries phase aligns with ARA, which evaluates whether target systems have the technical controls needed to safely support autonomous agents. Together they provide a complete assess-to-implement pathway: ARA validates system readiness while AXE designs the agent experience and implementation roadmap. +- **Signal patterns:** Portfolio shows 3+ services in `Pilot-Ready` or `Agent-Ready` state, or business has defined customer/employee experience goals but lacks a technical implementation roadmap. +- **How to evaluate:** Count services with profile `Agent-Ready` or `Pilot-Ready`. If count >= 3, recommend AXE. Also recommend if the portfolio `context` describes experience-level goals (e.g., "customer support agent", "employee productivity") without a corresponding technical implementation plan. +- **Delivers:** Agent experience design, six-phase implementation roadmap, governance and guardrails. +- **Segment:** Enterprise. +- **Sequencing:** Run after AI DLC to design the agent experience. +- **Pairs with:** AI DLC, Innovation EBA, ACP. + +### Innovation EBA (AIML-GenAI) `[ARA-anchor]` +- **Description:** A 3-day sprint-based, interactive engagement that enables customers to build AI/ML models or deliver a Generative AI use case in an accelerated fashion using AWS services and prescriptive guidance. Targets customers with higher cloud maturity who want to leverage AI/ML to solve business problems and innovate faster. Follows the 4-step EBA framework (Executive Alignment → Readiness → Accelerate → Transform At Scale) with workstreams including Foundations, Data Engineering, GenAI Build/Evaluate, UI Integration, ML Ops, and Command Center. Develops customer skills through learning-by-doing and builds/accelerates a GenAI use case pipeline based on a blueprint developed during the EBA. +- **Signal patterns:** Portfolio `context` indicates AI/ML or GenAI is a strategic imperative, executive sponsorship exists, use cases deliver critical business value, a data strategy exists, and the customer is committed to production deployment within ~90 days. The portfolio should also show a backlog of AIML-GenAI use cases and a customer team committed to upskilling. +- **How to evaluate:** Check portfolio `context` for: (1) AI/ML or GenAI as strategic priority, (2) executive sponsorship, (3) existing data and data strategy (services with established data pipelines, DynamoDB/Aurora/S3 data stores), (4) use cases in customer experience (chatbots, post-call analytics, personalization), productivity (intelligent search, summarization, code generation), business operations (IDP, fraud detection, predictive maintenance), or content creation. Also recommend if 3+ services have production-ready data stores AND the `context` describes GenAI ambitions beyond what AXE alone covers. +- **Delivers:** Accelerated GenAI/AIML use-case build with a reusable blueprint and pipeline. +- **Segment:** Enterprise (higher cloud maturity). +- **Sequencing:** Run when the customer is ready to accelerate a use case into production; may run in parallel with AXE if use cases are independent. +- **Pairs with:** AI DLC, AXE, GenAI Innovation Center. + +--- + +## FUNDED PROGRAMS + +### MAP (Migration Acceleration Program) `[ARA+MOD]` +- **Signal patterns:** 3+ High-severity findings across any dimension (ARA) or 3+ services classified `Remediation Required`/`Not Ready` (MOD); MODA shows multiple "Move to" pathways requiring significant investment; customer has migration-scale workload referenced in `context`. +- **DO NOT recommend when:** Opportunity <$500K ARR; customer only needs assessment (recommend OLA / AppMod Assessment instead); single-app modernization (recommend AppMod PoC instead); workload is already running on AWS with no net-new migration (MAP is for net-new migration to AWS). +- **Qualification:** $500K+ ARR opportunity; committed migration/modernization plan; partner engaged; workloads identified. +- **Funding:** Credits + partner cash (up to 30% ARR via SPI). +- **Delivers:** Migration/modernization support, tools, training, partner expertise. +- **Segment:** Enterprise, SMB (MAP Lite for <$500K). +- **Time to value:** 3–6 months. +- **Activation:** Create opp in AWSentral + MAP tag; engage MAP SA. +- **Prerequisite:** OLA or Migration Evaluator recommended first. +- **Pairs with:** EBA, OLA, AppMod Assessment. + +### MAP for AI Modernization `[ARA+MOD]` +- **Signal patterns:** ARA profile is `Remediation Required` or `Pilot-Ready` AND customer has a modernization need to enable agentic/AI workloads; MODA `Move to AI` pathway triggered. +- **DO NOT recommend when:** Customer only needs AI assessment (recommend AI Assessment Program); no modernization needed (architecture already agent-ready, i.e., ARA `Agent-Ready`). +- **Qualification:** MAP-eligible opp + AI modernization use case per Jan 2026 eligible list. +- **Funding:** MAP credits (AI use cases). +- **Delivers:** Modernization specifically for AI readiness. +- **Segment:** Enterprise. +- **Prerequisite:** Standard MAP qualification + AI use case validation. +- **Pairs with:** AI Assessment, Agentic Catalyst Program. + +### EBA (Experience-Based Acceleration) `[ARA+MOD]` +- **Signal patterns:** Multiple `High` effort remediation items in findings; customer team lacks hands-on experience with target architecture; deal stalled on technical validation. (MOD: 2+ services with a triggered pathway AND `Partial`/`Needs Work`/`Not Ready` classification.) +- **DO NOT recommend when:** Customer has strong internal engineering team; findings are mostly Low effort; customer just needs assessment not execution. +- **Qualification:** >$500K ARR; stalled deal needing technical validation; customer commits team for immersive engagement; executive sponsor. +- **Funding:** Funded engagement (varies). +- **Delivers:** Immersive hands-on migration with AWS/partner teams; real workload migration. +- **Segment:** Enterprise. +- **Time to value:** 4–8 weeks. +- **Activation:** Engage EBA team via SpecReq. +- **Prerequisite:** Opportunity identified; technical scope defined. +- **Pairs with:** MAP, AML. + +### AppMod Assessment `[MOD]` +- **Signal patterns:** MODA findings across multiple pathways but customer hasn't committed to a modernization approach; customer needs a business case before funding approval. +- **DO NOT recommend when:** Customer already knows what they want to modernize (recommend AppMod PoC instead); already has MAP engagement. +- **Qualification:** Qualified+ stage opportunity; customer considering modernization but needs business case. +- **Funding:** Funded assessment (varies). +- **Delivers:** Business case, detailed migration plans, modernization execution roadmap. +- **Segment:** Enterprise, SMB. +- **Time to value:** 2–4 weeks. +- **Activation:** Engage AppMod specialist. +- **Prerequisite:** None (entry point). +- **Pairs with:** MAP, AppMod PoC Funding. + +### AppMod PoC Funding `[MOD]` +- **Signal patterns:** MODA pathway triggered (`Move to Containers` or `Move to Cloud Native`) and customer wants to validate the approach on a specific application before scaling. +- **DO NOT recommend when:** Customer needs full business case first (recommend AppMod Assessment); scope is portfolio-wide (recommend MAP). +- **Qualification:** Identified modernization target (containers/serverless); technical team available; needs feasibility proof. +- **Funding:** PoC credits (varies). +- **Delivers:** Fast PoC for containers/serverless modernization. +- **Segment:** Enterprise, SMB. +- **Time to value:** 2–4 weeks. +- **Activation:** Request via AppMod specialist or scalable GTM POC mechanism. +- **Prerequisite:** None (can be entry point or post-assessment). +- **Pairs with:** AppMod Assessment, MAP. + +### AppMod Partner Accelerator `[MOD]` +- **Signal patterns:** Same as AppMod PoC + a partner is driving the engagement; partner has AppMod competency. +- **DO NOT recommend when:** No partner involved; customer wants AWS-direct engagement. +- **Qualification:** Partner-driven; customer + partner aligned on AppMod scope. +- **Funding:** $100K co-funding. +- **Segment:** Enterprise. +- **Prerequisite:** Partner engaged with AppMod competency. +- **Pairs with:** MAP, ISV Accelerate. + +### AI Assessment Program `[ARA]` +- **Signal patterns:** ARA profile is `Pilot-Ready` or `Agent-Ready` AND customer wants to define an AI/agentic strategy but hasn't started; customer asks "what should we do with AI?" +- **DO NOT recommend when:** Customer already has AI strategy (recommend Agentic Catalyst instead); findings are all about modernization not AI (recommend AppMod Assessment). +- **Qualification:** Seller-led pre-sales; customer exploring AI/GenAI/Agentic but needs strategy + ROI modeling. +- **Funding:** $15K (SMB) / $30K (Enterprise). +- **Delivers:** AI strategy assessment, use case discovery, ROI modeling. +- **Segment:** Enterprise ($30K), SMB ($15K). +- **Time to value:** 2–3 weeks. +- **Activation:** Seller-led; submit through assessment process. +- **Prerequisite:** None (entry point). +- **Pairs with:** Agentic Catalyst, GenAI Innovation Center. + +### OLA (Optimization & Licensing Assessment) `[MOD]` +- **Signal patterns:** Portfolio/service `context` indicates on-prem workloads needing migration; customer hasn't quantified savings; VMware or Microsoft licensing referenced in `context` or IaC. (Trigger from context/IaC, not from MOD findings about already-on-AWS workloads.) +- **DO NOT recommend when:** Customer already has business case data; workloads already on AWS with no licensing concern. +- **Qualification:** Customer has on-prem workloads; willing to share infrastructure data. +- **Funding:** No cost to customer (AWS pays partner). +- **Delivers:** On-prem compute/storage/licensing analysis + AWS migration modeling (avg 36% compute savings, 45% licensing cost reduction). +- **Segment:** Enterprise, SMB. +- **Time to value:** 2–3 weeks. +- **Activation:** Submit through Assessment Central. +- **Prerequisite:** None (entry point, often first step before MAP). +- **Pairs with:** MAP, Migration Evaluator, VMCCO. + +### AMA (AWS Modernization Assurance) `[MOD]` +- **Signal patterns:** Large VMware estate referenced in `context`/IaC; MODA shows `Move to Containers` or infrastructure modernization needed; competitive risk (Broadcom/Azure). +- **DO NOT recommend when:** <2000 VMs; deal <$2M ARR; no competitive pressure; customer timeline >12 months. +- **Qualification:** 2,000+ VMs; deal >$2M ARR; competitive risk; migration within 12 months; executive commitment. +- **Funding:** Migration costs + up to 50% yr1 run costs + training + licensing. +- **Segment:** Enterprise (large). +- **Time to value:** 6–12 months. +- **Activation:** VMCCO team engagement; AMA funding request (Bar Raiser certified = 5-day approval). +- **Prerequisite:** OLA completed; MAP qualified. +- **Pairs with:** VMCCO, MAP, VMP. + +### MDF (Market Development Funds) `[MOD]` +- **Signal patterns:** Partner-led engagement where the partner needs marketing/demand-gen support. +- **DO NOT recommend when:** No partner involved; customer-direct engagement. +- **Qualification:** Partner with relevant competency/program enrollment. +- **Funding:** GenAI $50K, Agentic AI $25K, MSP $50K, Enterprise $50K, LOB $50K, Connect $50K, Startup $30K, SMB $25K, ISVA $25K. +- **Segment:** Partner-facing (all segments via partners). +- **Prerequisite:** Partner enrolled in relevant program. +- **Pairs with:** ISV Accelerate, PGP, BOX. + +### Migration Evaluator `[MOD]` +- **Signal patterns:** Early-stage conversation; customer considering migration but no data; needs a directional business case before deeper engagement. (Trigger from `context`, not from on-AWS findings.) +- **DO NOT recommend when:** Customer already has OLA data; already committed to migration. +- **Qualification:** Any customer considering migration; willing to install data collector or provide inventory. +- **Funding:** Free tool. +- **Segment:** All. +- **Time to value:** 1–2 weeks. +- **Activation:** Self-service or SA-assisted. +- **Prerequisite:** None (entry point). +- **Pairs with:** OLA, MAP. + +--- + +## NON-FUNDED PROGRAMS + +### SHIP (Security Health Improvement Program) `[ARA+MOD]` +- **Signal patterns:** ARA `Authentication & Authorization` dimension has 2+ `Medium`/`High` findings (e.g., on AUTH-Q5 hardcoded credentials, AUTH-Q6 audit logging, AUTH-Q1 machine identity); or MOD `Security Baseline` category `severity_status` is `Needs Work`/`Critical`; findings mention hardcoded credentials, no audit logging, missing identity management. +- **DO NOT recommend when:** Security findings are minor (Low severity only); customer already has strong security posture (ARA Auth dimension has no Medium/High findings). +- **Qualification:** Any AWS customer; no minimum spend; ~2hr customer commitment for discovery. +- **Funding:** Free (no cost). +- **Delivers:** Security assessment, personalized recommendations, improvement roadmap using NIST framework. +- **Segment:** All. +- **Time to value:** 2 weeks. +- **Activation:** Submit SpecReq to engage SHIP Champion. +- **Prerequisite:** None (entry point). +- **Pairs with:** MAP (if funding needed for security remediation). + +### VMCCO (VMware Cloud Customer Obsession) `[MOD]` +- **Signal patterns:** `context`/IaC references VMware, vSphere, ESXi, or virtual machines; MOD shows infrastructure-level blockers; customer mentioned Broadcom licensing concerns. +- **DO NOT recommend when:** No VMware workloads; customer already committed to a non-VMware path. +- **Qualification:** Customer with VMware workloads (any size); especially post-Broadcom license changes. +- **Funding:** Free GTM motion + funded options (AMA for >$2M). +- **Delivers:** Migration pathways, decision trees, sales guidance, funding navigation. +- **Segment:** Enterprise, SMB. +- **Activation:** Engage AWS Infrastructure Migration & Modernization Specialists; tag in AWSentral. +- **Prerequisite:** None (entry point). +- **Pairs with:** OLA for VMware, MAP, AMA, VMP. + +### Well-Architected Review `[ARA+MOD]` +- **Signal patterns:** ARA `Engineering Maturity` or `Observability` dimension has 2+ `Medium`+ findings; or MOD findings span multiple categories without clear prioritization. +- **DO NOT recommend when:** Customer has already done WAR recently; findings are focused on one specific pathway (recommend the pathway-specific program instead). +- **Qualification:** Any AWS customer with workloads in production. +- **Funding:** Free. +- **Delivers:** Architecture review against 6 pillars; prioritized improvement recommendations. +- **Segment:** All. +- **Time to value:** 1–2 weeks. +- **Activation:** Partner-led or SA-led. +- **Prerequisite:** None. +- **Pairs with:** AppMod Assessment, MAP. + +### AWS Transform Custom `[ARA+MOD]` +- **Signal patterns:** Any finding (this IS the tool generating findings); recommend for additional repositories not yet analyzed. +- **DO NOT recommend when:** Customer has already run ARA/MODA on all relevant repos. +- **Qualification:** Customer with code repos to analyze; self-service or SA-led. +- **Funding:** Free (self-service). +- **Delivers:** AI-powered code analysis, modernization recommendations, agentic readiness scoring. +- **Segment:** All. +- **Activation:** Self-service via AWS Transform Custom console. +- **Prerequisite:** None. +- **Pairs with:** AppMod Assessment, ARA/MODA (expand scope). + +--- + +## PROSERVE & ENGAGEMENT MODELS + +### Agentic Catalyst Program (ACP) `[ARA]` +- **Signal patterns:** ARA profile is `Pilot-Ready` or `Agent-Ready` and customer is an ISV wanting to build agentic products; customer in ideation stage. +- **DO NOT recommend when:** Customer is not an ISV; customer needs modernization before AI (recommend MAP/AppMod first); customer already has agentic products in production. +- **Qualification:** ISV customer; in ideation stage; C-suite commitment; willing to dedicate exec + tech team for 1 week. +- **Funding:** Free (week-long engagement). +- **Delivers:** Executive alignment, technical build days, curated use cases, solution architecture, ROI preview. +- **Segment:** ISV only. +- **Time to value:** 1 week (engagement) + 12 months (production). +- **Activation:** Nomination by account team. +- **Prerequisite:** None (entry point for ISVs). +- **Pairs with:** ISV Booster, AI Assessment. + +### Immersion Days `[ARA+MOD]` +- **Signal patterns:** Findings show `High` effort remediation in specific areas (containers, serverless, observability) and customer team lacks that specific skill; MODA pathway requires a new technology the customer hasn't used. +- **DO NOT recommend when:** Customer team already skilled in target technology; findings are strategy/funding problems not skill problems. +- **Qualification:** Technical team available for 1-day hands-on; specific service/architecture interest identified. +- **Funding:** Free (1-day workshop). +- **Delivers:** Hands-on deep-dive on specific AWS services/architectures. +- **Segment:** All. +- **Time to value:** 1 day. +- **Activation:** Request via SA or ProServe. +- **Prerequisite:** Specific skill gap identified. +- **Pairs with:** EBA, AML. + +### AML (Application Modernization Lab) `[MOD]` +- **Signal patterns:** MODA `Move to Containers` or `Move to Cloud Native` + multiple `High` effort findings + customer team needs both training and guided execution (the training/execution need is inferred from `context` or surfaced in the engagement, not from code). +- **DO NOT recommend when:** Customer just needs a PoC (recommend AppMod PoC); customer has strong modernization experience; scope is assessment not execution. +- **Qualification:** Customer team available for training + guided modernization; Windows/.NET or Java workloads typical. +- **Funding:** Funded (credit incentive available via Windows Modernization Credits). +- **Delivers:** Modernization training + guided execution. +- **Segment:** Enterprise. +- **Time to value:** 4–8 weeks. +- **Activation:** Engage ProServe. +- **Prerequisite:** Modernization target identified. +- **Pairs with:** EBA, MAP, Microsoft Modernization Program. + +### GenAI Innovation Center `[ARA]` +- **Signal patterns:** ARA profile is `Agent-Ready` and customer wants to co-innovate on GenAI solutions (not just integrate agents into existing apps). +- **DO NOT recommend when:** Customer needs modernization first; customer just wants agent integration (recommend ACP or AI Assessment). +- **Qualification:** Strategic account; customer building GenAI solutions; willing to co-innovate. +- **Funding:** Free (innovation program). +- **Delivers:** Comprehensive GenAI innovation + delivery program. +- **Segment:** Enterprise (strategic). +- **Activation:** SA nomination. +- **Prerequisite:** AI strategy defined; architecture agent-ready. +- **Pairs with:** AI Assessment, Agentic Catalyst. + +### ProServe Residency `[ARA+MOD]` +- **Signal patterns:** ARA profile is `Remediation Required`/`Not Agent-Integrable` with 10+ High/Medium findings spanning most dimensions (or MOD `Not Ready` with broad High counts); customer needs sustained expert support over months; complexity too high for workshops. +- **DO NOT recommend when:** Findings are focused (1–2 dimensions); customer can execute with workshops + PoC; budget not available for paid engagement. +- **Qualification:** Complex transformation; customer budget for paid engagement; 3–12 month program. +- **Funding:** Paid engagement (varies). +- **Delivers:** Dedicated AWS experts working alongside customer teams. +- **Segment:** Enterprise. +- **Time to value:** 3–12 months. +- **Activation:** Engage ProServe. +- **Prerequisite:** Scope defined; budget approved. +- **Pairs with:** MAP (to fund), EBA (lighter alternative). + +--- + +## GTM MOTIONS & SALES PLAYS + +### Agentic-led Modernization Sales Play `[ARA+MOD]` +- **Signal patterns:** The ARA/MODA report itself IS the proof point; findings demonstrate legacy apps need modernization to become agent-ready; use the report as the conversation starter. +- **Qualification:** Customer interested in agent-ready architecture; ARA/MODA findings in hand. +- **Delivers:** Full-stack transformation positioning to unlock agent-ready architecture. +- **Activation:** Use ARA/MODA report as first-call evidence; reference Highspot sales play. +- **Pairs with:** MAP, AppMod Assessment, ACP. + +### AWS Pathways for VMware Workloads (VMCCO) `[MOD]` +- **Signal patterns:** VMware workloads referenced in `context`/IaC; infrastructure-level findings. +- **Qualification:** Customer has VMware workloads. +- **Delivers:** Decision tree for migration pathways, objection handling, funding navigation. +- **Activation:** Reference VMCCO decision tree; engage IMM specialists. +- **Pairs with:** VMCCO, OLA for VMware, AMA. + +### ModNet (Microsoft Workload Modernization) `[MOD]` +- **Signal patterns:** MODA shows Windows/.NET/IIS/SQL Server workloads; findings reference Microsoft licensing or Windows-specific tech debt. +- **Qualification:** Customer with Microsoft workloads (.NET, SQL, Windows). +- **Delivers:** AI-powered Microsoft workload modernization positioning + financial incentives. +- **Activation:** Reference ModNet on Highspot. +- **Pairs with:** Microsoft Modernization Program, AML, AWS Transform for Windows. + +--- + +## PARTNER & ISV PROGRAMS + +### ISV Accelerate (ISVA) `[ARA+MOD]` +- **Signal patterns:** Customer IS an ISV partner; ARA/MODA run on their SaaS product; they want to co-sell with AWS. +- **DO NOT recommend when:** Customer is an end-user enterprise (not an ISV). +- **Qualification:** ISV partner; listed on Marketplace or co-selling. +- **Funding:** Co-sell incentives + $25K MDF. +- **Segment:** ISV only. +- **Pairs with:** ISV Booster, ACP, SaaS Factory. + +### ISV Booster Program `[ARA+MOD]` +- **Signal patterns:** ISV customer with $1M–$50M ARR; slow/negative growth; ARA/MODA shows their product needs modernization to compete. +- **Qualification:** $1M–$50M ARR ISV; negative or slow growth; nominated. +- **Funding:** ACP + Enhanced Passport + VIR (3 pillars). +- **Segment:** ISV only. +- **Pairs with:** ISV Accelerate, ACP. + +### SaaS Factory `[MOD]` +- **Signal patterns:** MODA findings show multi-tenancy gaps, SaaS architecture debt; customer is an ISV building SaaS on AWS. +- **Qualification:** ISV building multi-tenant SaaS on AWS. +- **Funding:** Free technical enablement. +- **Segment:** ISV only. +- **Pairs with:** ISV Accelerate, OneSaaS. + +--- + +## STARTUP PROGRAMS + +### AWS Activate `[ARA+MOD]` +- **Signal patterns:** Customer is an early-stage startup; ARA/MODA run on their MVP/prototype; needs credits to execute modernization. +- **DO NOT recommend when:** Customer is an established enterprise. +- **Qualification:** Startup; early stage; apply via accelerators or direct. +- **Funding:** Up to $100K credits (varies by tier). +- **Segment:** Startup only. +- **Pairs with:** Global Startup Program, Kiro Startup Credits. + +--- + +## TRAINING & ENABLEMENT + +### AgentStorming Workshop `[ARA]` +- **Signal patterns:** ARA report generated but customer wants to identify WHERE to deploy agents in their business processes (beyond code readiness); customer interested in agentic transformation beyond single-repo scope. +- **DO NOT recommend when:** Customer only needs code-level remediation; not ready for process-level agentic thinking. +- **Qualification:** Customer exploring where AI agents can transform processes. +- **Funding:** Free (workshop). +- **Delivers:** Cognitive complexity analysis + EventStorming to identify agent-ready business processes. +- **Segment:** All. +- **Activation:** Engage Agentic Transformation team. +- **Pairs with:** ARA/MODA (code-level), ACP (ISVs), AI Assessment. + +### AWS AI League `[ARA]` +- **Signal patterns:** ARA findings indicate team skill gaps in AI/agent development; customer wants to upskill teams before implementing agent integrations. +- **Qualification:** Customer team interested in AI upskilling; willing to run an internal tournament. +- **Funding:** Free (gamified). +- **Segment:** Enterprise. +- **Pairs with:** Immersion Days, ACP. + +--- + +## WORKLOAD-SPECIFIC PROGRAMS + +### Oracle DB@AWS Pilot Promotion `[MOD]` +- **Signal patterns:** MODA `Move to Managed Databases` pathway with Oracle-specific findings. +- **Qualification:** Oracle DB customer in NAMER; partner engaged; MAP funding eligible. +- **Funding:** MAP funding for Oracle DB migration. +- **Segment:** Enterprise (NAMER only). +- **Pairs with:** MAP, OLA for Databases. + +### Kafka Migration Program `[MOD]` +- **Signal patterns:** MODA `Move to Managed Analytics` pathway with Kafka/streaming references. +- **Qualification:** Customer running Kafka on-prem or self-managed. +- **Funding:** Funded migration. +- **Segment:** Enterprise. +- **Pairs with:** MAP. + +### Microsoft Modernization Program `[MOD]` +- **Signal patterns:** MODA findings reference Windows Server, .NET Framework, IIS, SQL Server; `Move to Containers` or `Move to Cloud Native` for Windows workloads. +- **Qualification:** Windows/.NET workloads; partner engaged. +- **Funding:** AWS-funded partner solutions. +- **Segment:** Enterprise. +- **Pairs with:** ModNet, AML, AWS Transform for Windows. + +--- + +## TIER 2: COMPACT INDEX (Additional Programs) + +> **Agent instruction:** Scan this index after selecting Tier 1 recommendations. If the customer's technology stack, workload type, or segment matches a Tier 2 program better than any Tier 1 option, surface the Tier 2 program instead. Format: one-liner with trigger condition. The same 3–5 cap, grouping, and status rules apply. + +### Funded Programs (not in Tier 1) +| Program | Trigger Condition | Segment | Funding | +|---------|-------------------|---------|---------| +| MAP Lite | Migration opp <$500K ARR; too small for full MAP | SMB | Credits (lite package) | +| AIAF Strategic Pilot | Post-AI Assessment; high-value use case identified; ready for funded pilot | Enterprise | Funded pilot | +| OLA for Databases | On-prem Oracle/SQL Server; evaluating DB migration specifically | Enterprise, SMB | Free (AWS pays partner) | +| OLA for VMware | VMware environment; needs vCenter data analysis before migration decision | Enterprise | Free (AWS pays partner) | +| Must Win Fund (MWF) | Competitive deal at risk (Azure, GCP poaching); need credits to close | Enterprise | Up to 25% ARR | +| VMware Modernization Program (VMP) | Partner-led VMware modernization; partner has VMware competency | Enterprise | Partner funding | +| AWS Windows Modernization Incentive Credits | Customer in AML engagement for Windows workloads | Enterprise | Credit incentive | +| Data & AI Partner Funding Hub | Data or AI workload with partner engagement; need aggregated funding view | Enterprise | Various | +| Project Rubicon | Massive deal ($10M+ ARR); multi-year strategic transformation | Enterprise (largest) | Large-scale | +| SAP RISE Acceleration Program | SAP customer evaluating RISE with migration to AWS | Enterprise | AGI-funded | +| Proof of Concept (POC) - Scalable GTM | Partner or customer needs quick funded PoC validation | All | Funded PoC | +| Innovation Sandbox | Customer needs experimentation environment for new AWS capabilities | Enterprise | Sandbox funding | + +### Non-Funded Programs (not in Tier 1) +| Program | Trigger Condition | Segment | Notes | +|---------|-------------------|---------|-------| +| MRA (Migration Readiness Assessment) | Early-stage; customer not committed to migration; need readiness check | All | Free; entry point before MAP | +| MRP (Migration Readiness Planning) | Post-MRA; customer committed, needs execution plan | All | Free; follows MRA | +| AWS Cloud Resilience Program | Findings show availability/DR gaps; production workloads at risk | Enterprise | Free | +| Assessment Central | Customer doesn't know which assessment to start with; need hub view | All | Free; umbrella for OLA/Storage/etc. | + +### ProServe & Engagement (not in Tier 1) +| Program | Trigger Condition | Segment | Notes | +|---------|-------------------|---------|-------| +| Project Vidya | Internal: SA/account team needs AI-powered customer research prep before engagement | Internal | Agentic consulting platform | +| Project Uplift | Customer needs multiple engagement types combined (EBA + CDP + Jumpstart) | Enterprise | Combined package | +| Mainframe Modernization Service | COBOL/mainframe workloads detected; committed to replatform/refactor | Enterprise | ProServe-led (paid) | +| The RAPID Initiative | VMware/IMM pipeline acceleration; 5-step formula for any IMM deal | Enterprise | Programs + funding | + +### Partner & ISV (not in Tier 1) +| Program | Trigger Condition | Segment | Notes | +|---------|-------------------|---------|-------| +| ISV WMP (Workload Migration Program) | ISV partner migrating customer workloads to their SaaS platform | ISV | GTM + funding; expanding to BYOL Q2 2026 | +| OneSaaS | ISV or services firm adopting/offering SaaS; any maturity stage | ISV | GTM resources | +| AWS Marketplace Multi-Product Solutions | ISV with multiple products wanting bundled Marketplace listing | ISV | Listing capability | +| ISV MDF (Marketing Dev Funds) | ISVA partner needing marketing development support ($25K) | ISV | $25K; requires PRM + Co-Sell | +| BOX (Business Outcomes Xcelerator) | Partner focused on measurable business outcomes, not just tech deployment | Partners | Expanded to BCAPs at GPS 2026 | +| BVR (Business Value Realization) | Post-sale; customer adopted AWS; partner leads value realization tracking | Enterprise | Launching Q2 2026 at NYC Summit | +| PGP (Partner Greenfield Program) | Partner building new AWS practice in Migration, GenAI, or Security | Partners | Enablement + funding + co-sell | +| SBAI (Small Business Accelerator) | Partner-led/indirect selling to SMB, ISV, or mid-size customers | SMB, ISV | Tools + enablement + GTM | +| MSP Incremental Growth Incentive | MSP partner with >15% YoY managed services revenue growth | Partners (MSP) | 10–25% of incremental rev (cap $5M) | +| MPOPP (Marketplace Private Offer Partner Program) | Partner transacting through Marketplace private offers | Partners | Incentives | +| RAPID for ISVs | Small/medium ISV growing through Distributors | ISV | Launching Q4 2026 | +| RAPID for Marketplace | Reseller driving customer purchases through Marketplace/CPPO | Partners | Launching Q4 2026 | + +### Startup (not in Tier 1) +| Program | Trigger Condition | Segment | Notes | +|---------|-------------------|---------|-------| +| AWS Global Startup Program | Startup at any stage; comprehensive engagement needed | Startup | Full resource access | +| Kiro Startup Credits | AI-native startup using AI-powered dev tools | Startup | 3 credit pathways | +| Worldwide Startup Partners Hub | Startup ISV onboarding to APN | Startup | Onboarding resources | + +### GTM Motions & Sales Plays (not in Tier 1) +| Program | Trigger Condition | Segment | Notes | +|---------|-------------------|---------|-------| +| Agentic AI for SaaS Providers & ISVs | Customer is SaaS/ISV exploring agentic AI opportunities | ISV | Sales play | +| Efficient Compute Sales Plays | Findings show compute cost concerns; right-sizing opportunity | Enterprise | GTM motion | +| AWS Security Agent Sales Play | Customer interested in automated security across dev lifecycle | Enterprise | Sales play | +| Zero Trust for AI Sales Play | Customer building AI; needs to prove identity/data flow authorization | Enterprise | 3-phase engagement | +| SAP RISE Acceleration Sales Play | SAP customer; RISE migration opportunity | Enterprise | AGI sales play | +| Enterprise Support Sales Play | Gap in current support coverage identified | Enterprise | Sales play | + +### Training & Enablement (not in Tier 1) +| Program | Trigger Condition | Segment | Notes | +|---------|-------------------|---------|-------| +| AWS GameDay | Technical team wants hands-on gamified learning on real scenarios | All | Free | +| VMCCO Bar Raiser Program | Internal: migration specialist wanting expedited AMA approvals (5d vs 27d) | Internal | Certification | +| Database Upskill Program | Customer/partner team doing DB migration; skill gap in target DB | Enterprise | Training | + +### Workload-Specific (not in Tier 1) +| Program | Trigger Condition | Segment | Notes | +|---------|-------------------|---------|-------| +| Countdown Premium/Platinum | Complex database migration needing tiered support | Enterprise | Paid support tiers | +| AWS Transform for Windows | Windows/.NET/IIS workloads; code repo available for automated analysis | Enterprise | Free (AI-powered tool) | +| Mainframe Modernization (WWPS) | WWPS customer with mainframe; committed + budgeted | WWPS | ProServe (paid) | +| SAP on AWS | SAP workload migration; MAP eligible + AGI-funded | Enterprise | MAP + AGI | +| End of Support Migration | Customer on EOL software (Win Server 2012, SQL 2014, RHEL 7, etc.) | Enterprise | MAP eligible | +| Think Big for Small Business Boost (TBSB) | Public sector small business focus | WWPS only | Varies | +| Partner Transformation Program (PTP) | WWPS partner transformation | WWPS only | Varies | +| SMB Competency (updated Q2 2026) | Partner with SMB Competency; greenfield SMB efforts | Partners (SMB) | $25K MDF + community | +| Amazon Connect Competency | Partner with 4+ Connect case studies; implementation expertise | Partners | Launching Q2 2026 | + +--- + +## AGENT REASONING CHECKLIST + +After selecting Tier 1 recommendations, verify before emitting: + +1. ☐ Did I check whether the customer's workload type (VMware, Windows, Mainframe, Oracle, SAP, Kafka) has a workload-specific program? +2. ☐ Did I check whether the customer is a Startup or ISV (different program universe)? +3. ☐ Did I check whether the customer is WWPS (geo-restricted programs available)? +4. ☐ Did I include at least one entry-point program (no prerequisites)? +5. ☐ Did I avoid recommending follow-on programs without their prerequisites? +6. ☐ Did I cap recommendations at 3–5 (avoid overwhelming the seller)? +7. ☐ Did I sequence recommendations logically? (Assessment → Funding → Execution → Optimization; and for ARA anchors, AI DLC → AXE → Innovation EBA) +8. ☐ Did I group output as Funded Programs → Engagement Models → GTM Motions? +9. ☐ Did I exclude any `Retiring` programs and any `Launching` programs whose launch is not imminent? +10. ☐ Did I avoid exposing the internal MOD 1–4 maturity score anywhere in the output? + +--- + +## STATUS KEY + +- All programs listed here are **Active** as of June 2026 unless noted below. +- **Launching** (do not recommend unless launch is imminent): BVR (Q2 2026, NYC Summit), Amazon Connect Competency (Q2 2026), RAPID for ISVs (Q4 2026), RAPID for Marketplace (Q4 2026). +- **Evolving:** MAP is evolving to "Unified MAP" (migration + AI) at re:Invent 2026. ISV WMP expanding scope to BYOL + net-new in Q2 2026. +- No programs are currently marked **Retiring**. If a future revision marks a program Retiring, the agent MUST NOT recommend it. + +--- + +*Last updated: 2026-06-03* +*Source: APN Programs Roadmap (Apr 2026) + AWS Highspot (Jun 2026)* +*Programs indexed: 88 — Tier 1 detailed: 35 (32 source + 3 ARA agentic anchors); Tier 2 compact: 53*