Alchemaize CATALYST: AI-DLC Transformation Program
Alchemaize, Inc. · Software Development
Certification per AWS Marketplace.
Evidence tier Source Confirmed · 3 captures on record
What the publisher says
As described on AWS Marketplace.
**THE PROBLEM**
Engineering organizations have spent heavily on AI tooling — Q Developer licenses, Bedrock credits, Copilot subscriptions — without a corresponding improvement in delivery velocity or software quality. The tools are capable. The methodology hasn't changed. Teams are running AI-era tools inside a human-era process, and the friction shows in every sprint review.
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**THE METHODOLOGY**
CATALYST adopts the AWS AI-Driven Development Lifecycle (AI-DLC), developed by AWS Principal SA Raja SP. AI-DLC positions AI as a central collaborator — not an autocomplete tool — that creates plans, asks clarifying questions, and implements only after human validation. Delivery happens in **Bolts** (replacing sprints) through three phases: **Inception** (AI generates requirements and stories via Mob Elaboration, team approves), **Construction** (AI proposes architecture and writes code via Mob Construction, team decides), and **Operations** (AI deploys and documents from accumulated context, team signs off).
**THE ENGAGEMENT**
CATALYST delivers in four tracks, each purchasable separately or as a progression:
- **AI-DLC Discovery (1 day):** Leadership readiness assessment, bolt simulation, and custom adoption roadmap.
- **AI-DLC Pilot Bolt (2 weeks):** Embedded Alchemaize coach guides the team through their first real bolt cycle. Kiro and Amazon Q Developer configured with the CATALYST Starter Kit.
- **AI-DLC Transformation (90 days):** Full org adoption. Toolchain deployed, all engineers trained, three supervised bolt cycles, Center of Excellence established, custom Kiro steering documents and Amazon Q Developer rules authored for the organization.
- **AI-DLC Continuity (quarterly):** Post-transformation retainer for bolt reviews, rule refinement, new team onboarding, and methodology updates.
**THE CATALYST STARTER KIT**
Every engagement deploys Alchemaize's proprietary Kiro steering documents and Amazon Q Developer rules into the customer's project repositories. These documents encode the AI-DLC methodology, the team's architectural standards, and Alchemaize's delivery playbooks — so every AI interaction is guided by the full context of how that organization builds software. The methodology lives in the toolchain, not a slide deck.
**AWS SERVICES ACTIVATED**
Amazon Q Developer (org-specific project rules), Kiro IDE (per-team steering documents), Amazon Bedrock (Claude Sonnet 4 + Haiku), Amazon Bedrock Knowledge Bases, Amazon Bedrock Guardrails, Amazon CodeCatalyst (bolt tracking), AWS CDK, Amazon CloudWatch, AWS X-Ray, AWS Secrets Manager.
**WHY ALCHEMAIZE**
Alchemaize is the only APN partner delivering named AI-DLC methodology transformations. Our team includes former AWS CSMs and Solutions Architects with deep enterprise AI/ML adoption experience. We have shipped multiple production applications on Amazon Bedrock — including Knowledge, Workflow, and Multi-Agent architectures — using the same methodology we teach. CATALYST is not theoretical. It is how Alchemaize builds.
Highlights
Highlighted by the publisher on AWS Marketplace.
Alchemaize is the only AWS Partner Network member delivering named AI-DLC methodology transformations. Our engagements are built on the AWS AI-DLC framework published by AWS Principal SA Raja SP — the same methodology AWS field teams are actively recommending to enterprise customers. When an AWS account team encounters a customer asking about AI-DLC, Alchemaize is the go-to implementation partner.
Every CATALYST engagement deploys Alchemaize's proprietary Kiro steering documents and Amazon Q Developer rules into the customer's repositories. This is not documentation. It is the AI-DLC methodology encoded into the tools the team uses every day — persistent across sessions, consistent across teams, refinable as practices evolve. The customer leaves with a living system, not a PDF playbook.
Alchemaize does not teach what it hasn't done. We have shipped multiple production applications on Amazon Bedrock — including Knowledge Agents, Workflow Agents, and Multi-Agent orchestrators on AgentCore — using the same AI-DLC bolt methodology we deploy in CATALYST. Former AWS CSMs and Solutions Architects on staff who have guided enterprise AI/ML adoption from strategy through production.
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