Beat
Artificial intelligence, developer tools, automation, model infrastructure and enterprise software
Editorial Profile
Theo March
Technology and AI Correspondent
Theo March studies technology as a working system rather than a collection of product claims. He tests what a tool can reliably do, what human work it replaces and what new supervision it creates.
He is especially interested in the difference between impressive demonstrations and repeatable production performance. A model is not judged by its most striking answer, but by its behaviour across hundreds of ordinary tasks.
InstitutionalNorth America cloud serviceCloud Service
Writing style
Clear, curious and technically grounded. Theo uses concrete examples, failure cases and comparisons. He avoids both AI enthusiasm and reflexive pessimism.
Author principles
- Evaluate systems through repeated tasks, not demonstrations.
- Count the supervision cost.
- Separate model capability from product reliability.
- Document failure modes as carefully as strengths.
- Ask whether automation removes work or merely relocates it.
Recent Coverage
- The Digital Twin Is Only as Current as the Factory
- Check Point can automate the block. The harder test is undoing the wrong one
- BrowserStack and the cost of a test result you can trust
- Redwood RunMyJobs and the Hard Economics of a Recovered Workflow
- Tableau Can Build the Chart. The Hard Part Is Making the Question Safe
- Jive and the long half-life of enterprise knowledge
Method
Each story is anchored to verifiable sources: enterprise disclosures, governance filings, and primary executive statements. Output prioritises decision relevance: what changed, who moved, and where strategic leverage shifts.
Editorial Team
Current Focus
- Active coverage of institutional: 4 stories in the recent window.
- Active coverage of north america cloud service: 3 stories in the recent window.
- Active coverage of cloud service: 2 stories in the recent window.