Tag: #RiskManagement

Agentic Coding Is a Power Tool. Don’t Use It Like a Glue Gun.

Agentic coding tools (like Claude Code, OpenAI’s Codex agents) are making it ridiculously easy to turn an idea into working software. That’s exciting. It’s also where people can get into trouble – especially when non-developers or non-solution designers use these tools to build systems they can’t confidently secure, test, operate, or maintain.

Below is a pragmatic way to think about agentic tools: when they’re a superpower, when they’re a liability, and how to get value without accidentally creating a future incident (or an unmaintainable mess).

GenAI Adoption Opinions Seem Polarized – Pragmatism Will Win

If you follow the GenAI conversation closely, it can feel like whiplash – like there is no agreement. One day it’s “AI is rewriting the economy,” the next it’s “AI is all hype and risk.” It feels like we’re now in a “Great Divergence” – not just differing opinions, but two parallel realities shaped by incentives and where you sit in the organization (something I have seen in my own work – some organisations are embracing AI and realizing the benefits while other are flatly, not interested).

Claude Cowork – Before You Install an AI “Coworker”: Treat Agentic Tools Like Privileged Access

The newest wave of “desktop automation” tools look genuinely useful – and materially different from the assistants we’ve gotten used to. Tools like Claude Cowork and agentic browsers such as Perplexity Comet and ChatGPT Atlas don’t just answer questions; they can take actions across your files, tabs, and workflows. That shift changes the risk profile, fast.

Risk × Friction: How Much Human Oversight Should You Remove with GenAI?

GenAI is an accelerant. It speeds up decisions, output creation, and information flow, often without strengthening the system underneath. And many organisations are already running “hot”: highly optimised, tightly interconnected, little slack, and dependent on tacit knowledge.

So the real question isn’t just “How much can we automate?” It’s also “Where does speed strengthen the system – and where does speed increase fragility?”

GenAI Workflows – Sometimes Friction is Good (… and systems are fragile)

One of the challenges about GenAI adoption is simply getting started: picking tools, running pilots, training staff, and rolling out a plan. Another major challenge is where and how GenAI gets introduced into already fragile, tightly coupled organisational systems.

I was watching a Veritasium video (The Strange Math That Predicts (Almost) Anything) about complex systems and the moment they reach a “critical state.” A forest can look calm and stable right up until a single spark turns it into a massive wildfire. Not because the spark was special but because the system was already primed for runaway behaviour.

In a general sense, many organisations today look just like that forest, in a critical state.

GenAI Procurement: Why It’s Not Business as Usual

Buying a Generative AI solution, whether it is a discrete or embedded GenAI solution, isn’t like buying a CRM or ERP system. It’s a whole new ballgame, one where you can’t always see the rules, and the players (the models) can sometimes make up their own. GenAI procurement requires a fresh playbook. Let’s break down what’s changing, why it matters, and how you can stay ahead.