Agentic AI makes workflow architecture a leadership issue
Agentic AI shifts the leadership question from which AI tool to buy to which decisions, workflows, data and permissions should be encoded into software.
Insights
Practical engineering notes for business-critical software.
Articles on software modernisation, applied AI, workflow automation, architecture, maintainability and long-term operation.
Operational security beats symbolic control
Data location matters, but real control depends on access, logging, monitoring, backup, recovery, dependency health and operational ownership.
AI agents need budgets, logs and a kill switch
AI agents are not ordinary software users. They can consume tokens, call tools, repeat loops and trigger actions. They need operational controls before they enter production.
Why B2B customer portals fail when the back-end is disconnected
A customer portal is not just a front-end project. It depends on product data, customer data, documentation, service workflows, permissions and system integration.
When finance work becomes a software problem
Manual finance work is often a sign of disconnected systems, unclear workflows and missing automation foundations — not a lack of effort from the finance team.
Connected systems before AI agents
AI agents can only act usefully when the systems around them are connected, permissioned, observable and maintained. Integration work comes before agentic automation.
The Technical Review for AI-ready software
Before building AI workflows, companies need a clear technical picture of their systems, data, integrations, access control, deployment and operational gaps.
AI adoption is not AI capability
Many companies now use AI, but fewer have built real AI capability. The difference is whether AI is connected to useful data, workflows, systems, access control and operation.
Agile delivery with fixed budgets: how to keep flexibility without losing control
An article about budget control, scope discipline and adaptable software delivery.
How to measure whether an AI workflow is actually useful
An article about evaluating AI workflows by operational value rather than novelty.
From copy-paste work to connected workflows: where automation should start
A practical guide to finding the first automation opportunities.
How to build AI workflows safely when data cannot leave the company uncontrolled
A practical security and data-boundary article for AI workflows.
Accessibility as software quality, not just compliance
A software-quality perspective on accessibility.
EventStorming and workflow mapping before software development
An article on understanding workflows before building software.
Application maintenance after launch: ownership, monitoring, updates and documentation
An article about what must happen after software goes live.
Not every prototype should survive: moving from AI-assisted prototype to maintainable software
An article about AI prototyping, technical debt and production readiness.
Internal tools become business-critical software faster than companies expect
An article about why internal tools need architecture, operation and ownership.
The practical role of human review in AI-assisted workflows
An article about approval, escalation and accountability in AI workflows.
Data foundations before AI: why poor data quality turns automation into risk
An article about data quality, ownership and access before AI implementation.
Monolith, microservices or hybrid: choosing a modernisation path without unnecessary complexity
A practical architecture article about choosing a modernisation path by context.
When a CMS, platform or framework reaches end-of-life: what to review before upgrading
A guide to end-of-life upgrades and platform review.
What an Application Modernisation Review should include
A diagnostic article defining the areas to review before modernising a system.
Why integration is the missing foundation for automation and AI
An article about APIs, data flow and connected systems as a prerequisite for automation.
AI agents inside business systems: useful patterns, limits and human review
A practical article on where AI agents are useful and where they need control.
From AI experiments to production-ready workflow automation
A guide to moving from AI pilots to reliable, maintained workflows.
Shadow AI: how companies lose control of data before they notice
An article about unmanaged AI adoption, data exposure and practical governance.
AI readiness: the data, access and workflow questions to answer before building anything
A practical readiness article for companies that want useful AI, not disconnected experiments.
How to decide whether to modernise, rebuild or replace a business-critical application
A practical guide to choosing a lower-risk path for an existing system.