Why Enterprises Need To Care About Decision Logic, Not Just The UI
A polished interface can still hide decision logic no one can explain. Enterprises need to care not only about what customers see, but about the rules, thresholds, and decisions their software makes underneath.
Decision Intelligence Is Becoming the Control Layer for Enterprise AI
Decision intelligence is moving from dashboards and analytics toward modeled, governed, executable decisions. For enterprises using AI to build software and agent workflows, the decision logic itself needs to be readable, testable, auditable, and deterministic.
What Anthropic’s Research on Self-Improving AI Means for Every Regulated Enterprise
Anthropic recently published When AI builds itself, a data-backed account of how much of the company’s own development is now handled by its models. The striking finding isn’t that Claude now authors most of the code Anthropic merges.
Why Determinism Is the Missing Piece For EU AI Act Compliance
The EU AI Act is no longer a distant regulatory concern. It applies in full from August 2026. Yet for many organizations deploying AI agents and automated decision-making tools, there is a critical gap in their compliance strategy: their AI systems are fundamentally non-deterministic.
Why Your AI Agents Can’t Pass an Audit (And How to Fix It)
You’ve deployed an AI agent to handle loan pre-screening, then the regulator calls your compliance officer.
Agentic AI Hype vs Reality: What to Expect Next
Gartner predicts 40% of agentic AI projects will be canceled by 2027.
AI Helped Me Build It…But I Don’t Know How It Works. Sound Familiar?
Vibe coding feels fast until production breaks and no one knows why.
Deterministic Tools For AI Agents (Without Writing Code)
Lena Hall demos how to use Leapter with n8n to build relaible Agentic Automation.
Why Agents Fail at Logic (and How to Fix It)
AI agents can write code, summarize documents, plan tasks, and even run commands.
Mind the Gap: Why We Don’t Trust AI-Generated Code (Yet)
AI-generated code is useful but we don’t trust it. Not fully. Not yet.