Keeping your judgment while AI keeps changing

We do not think a CEO should need to follow every model release to make a sound decision about AI. You are already carrying the consequences of enough decisions. Our job is to help translate a change in capability into a question worth asking about your business, and to be honest when an announcement gives you no reason to change course.

We are optimistic about the technology and selective about where to spend attention. A new release matters when it improves something that currently limits the work: a repeated error, a cost that prevents sensible use or an input the team cannot handle reliably. The launch itself is not the business case.

Choose what deserves attention

This creates a more manageable way to follow developments. Keep a short list of the limitations that currently affect your work. Perhaps a report requires too much correction, a file cannot be processed in the desired way or a connection is unavailable. A new announcement becomes relevant when it addresses one of those limitations or opens a genuinely useful possibility.

An illustrative team might be comfortable with its document preparation but frustrated by the effort required to investigate unusual movements. A new reasoning capability could deserve a controlled trial. A new visual style might be interesting without changing the priority. Relevance depends on the work, not the volume of attention around a release.

We are optimistic about the technology and selective about where to spend attention.

Maintain a small set of representative examples. Include ordinary tasks and the exceptions that have previously caused difficulty. Use those examples when considering a model change, and compare accepted outputs rather than first impressions. Record what improved, what became harder and whether the review burden changed.

Keep a practical test set

We would keep a small set of examples your team understands, including a failure case. Run those when a change looks relevant. Compare the accepted result and the review effort. That makes the conversation less dependent on whoever has the strongest opinion about a new product name.

The same discipline applies to news sources. Follow important claims to the original announcement and distinguish the provider’s statement from an independent assessment or someone’s interpretation. A concise summary is helpful when it preserves those boundaries. It should give the reader enough context to decide whether to investigate further.

There is room for optimism without urgency becoming the operating model. A business can improve its ability to experiment, document what it learns and adopt changes deliberately. Over time, that learning process may be more valuable than any single choice of model. It allows the organisation to adapt while keeping responsibility clear.

We want our industry notes and conversations to support that kind of judgment. We will bring attention to changes, ask what they mean in practice and leave space for uncertainty. The purpose is to make the next discussion more informed, whether it leads to a small experiment, a scoped engagement or a decision to wait.

Examples in this essay are illustrative, rather than accounts of client engagements.