Amazon Web Services
Amazon Web Services (AWS) is Amazon’s cloud-computing business. In this wiki, AWS appears as the organisation teaching customers how to use Amazon’s Working Backwards methodology, as a cloud certification ecosystem inside data/AI training paths, and as a source of applied thinking on agentic AI, AI-assisted software delivery, and enterprise agent architecture.
Key facts
- Type: Cloud platform / business unit
- Parent company: Amazon
- Relevant team in source: Digital Innovation and PACE, which stands for Prototyping and Customer Engineering [src-017]
- Method discussed: Working Backwards and PR FAQ for customer-led innovation [src-017]
- Example customers mentioned: SAP Sports One / TSG Hoffenheim and 3M [src-017]
- Training/certification role: Liora’s Data Scientist syllabus includes AWS Cloud Practitioner preparation and presents Liora as an Amazon Training Partner [src-050].
- Agentic AI voice: Rory Richardson, Director of Agentic AI GTM at AWS, explains AI-DLC, Project Mantle, agent hardening, build-versus-buy, and adoption culture [src-057].
What it does
In the AWS Events session, AWS presents working backwards as both an internal Amazon operating mechanism and an external customer-engagement method. The Digital Innovation and PACE team helps customers identify a specific customer persona, define a valuable problem, write a PR FAQ, prototype quickly, and test whether the solution is desirable, viable, and technically feasible [src-017].
The session frames AWS’s role as more than cloud infrastructure provider: AWS helps customers de-risk product bets by narrowing broad opportunity spaces into concrete customer problems, then moving quickly into frugal experiments and proof-of-concepts [src-017].
In the Liora syllabus, AWS appears as an employability and cloud-literacy credential. The Data Scientist path includes a one-day AWS Cloud Practitioner preparation module delivered remotely by certified Amazon Authorized Instructors [src-050].
In the AWS Humans in the Loop podcast, AWS appears as a practitioner environment for agentic AI. Richardson describes compressed development cycles, AI-assisted service creation, Project Mantle’s Bedrock rewrite, DevOps/SRE/security agents, AWS Transform for modernization, and the need to harden MCP servers and agent interfaces before treating them like production infrastructure [src-057].
Related
- See also: Amazon, Rory Richardson, Working Backwards, PR FAQ, Customer Co-Design, Minimal Lovable Product, AI Development Lifecycle, Agents As Microservices, Human-Agent Collaboration, Liora, Liora Data Scientist Bootcamp