Infinite Mind vs Thoughtworks

Thoughtworks Joins Anthropic’s Claude Network as a Select-Tier Services Partner

Thoughtworks has partnered with Anthropic to join its Claude Network as a Select-Tier Services Partner, expanding its AI capabilities.

ThoughtWorks Flags AI-Accelerated Shadow IT; Structural Fix Proposed

The ThoughtWorks Technology Radar (April 2026) called out "AI-accelerated shadow IT" under Caution. The article argues this is one visible instance of a broader cloud resource lifecycle governance problem (create, use, modify, abandon, delete) that predates AI tooling but is accelerated by it. HackerOne triage revealed S3 bucket takeover patterns where deleted resources left ghost references that attackers could exploit. The author describes a structural fix: a mechanical "specification gate" that snapshots cloud provider state and evaluates it against a catalog of safety invariants (3,000+ invariants), blocking violations across all lifecycle phases. An open-source engine (Stave) implements this approach and the author frames it as necessary to remove a two-tier system of reviewed core workflows and ungoverned shadow workflows.

• The ThoughtWorks Technology Radar (April 2026) listed "AI-accelerated shadow IT" under Caution.
• HackerOne triage found S3 bucket takeover patterns where deleted buckets left surviving references (DNS, CloudFront, application code) that attackers could claim.
• The lifecycle governance problem spans five phases: Create, Use, Modify, Abandon, Delete and predates AI tooling; AI accelerates creation but not the underlying governance gap.

OLAP and OLTP Lines Are Blurring

A developer article explains how recent extensions and engine architectures are narrowing the gap between OLTP (transactional) and OLAP (analytical) workloads. It describes how extensions such as pg_lake decouple storage to cloud data lakes using Apache Iceberg while offloading analytical execution to an isolated, vectorized DuckDB process to avoid impacting the operational database. The author maps end-to-end execution flow, resource safety boundaries, and scheduling differences between macro-distributed query engines and micro-morsel (embedded/vectorized) processing engines. The post links to a detailed GitHub DeepDiveDuckDB repository for a full architecture layout. The piece is a technical analysis aimed at data engineers and platform architects.

• The article argues OLAP and OLTP workload boundaries are blurring because new approaches let analytical queries run without starving transactional databases.
• pg_lake is described as decoupling the storage plane into cloud data lakes using Apache Iceberg.
• The OLAP execution path can be offloaded to an isolated background process running a vectorized DuckDB engine to protect the operational database.