Featured Stories

We see flow states in creative pursuits, sports, hobbies and mindfulness activities like yoga. It can also be extended to the digital product experience. Let’s explore the four principles of flow and ways you can use them to design more enjoyable and engaging user experiences.

This blogs argues that the success of a retrieval-augmented generation (RAG) system depends more on data quality, metadata and governance than on model tuning or pipeline optimization. Without clear metadata, document ownership, permissions and freshness controls, AI systems can retrieve outdated or incorrect information, leading to hallucinations. Ultimately, trustworthy AI requires well-structured, governed data, not just more advanced models.

The blog invites OpenEdge developers and others interested in Progress OpenEdge to join the community-driven “Progress Labs” Discord for real-time collaboration, practical knowledge sharing and informal conversation alongside (not replacing) the more structured Progress Community.

Trust is now the differentiator: AI capability is rising fast, but enterprise adoption depends on governance, explainability and control. User-first beats tool-first: The winning model is bringing AI into the flow of work, not forcing people to learn complex tooling. Boring is what scales: Predictable, policy-aligned and auditable AI is what turns pilots into production outcomes.

In HIPAA-regulated environments, even minor lapses could have serious consequences. Compliance-ready cloud file transfer software could help.

How the Semaphore platform enhances Microsoft Purview with semantic metadata, improving classification accuracy, scalability and governance readiness for enterprise AI and compliance.

ICYMI: Suzanne Reed on reclaiming strategy, streamlining martech and keeping marketing human.

Modern application transformation in 2026 is less about replacing technology and more about adopting a business‑first, continuously improving culture that unlocks data, modern UX and AI‑driven innovation without disrupting what already works.

AI fines are no longer theoretical; regulators are now enforcing control requirements as AI moves from pilots to production in financial services. The post explains why contracts alone won’t satisfy supervisors, what evidence regulators will expect to see in production and how organizations can operationalize governed, defensible AI with runtime guardrails, provenance, lineage and auditable controls—setting the agenda for the RegTech Conference in London on March 26.