activate. / ideas in motion
Ideas, methods and field lessons on strategy, innovation, product and AI. Written to recognise a signal, make a decision and go deeper when it matters.
RSSInnovation · Learning
Since the public launch of ChatGPT based on GPT-3.5, interaction with AI has expanded from conversation to files, tools, search, code and agents. Memorised features expire; the ability to experiment and evaluate remains.
Read articleInnovation · Product · Learning
A conversation revealed a need: to find an exact quote inside hours of audio or video. Around two hours later, AudioFind existed as a small, usable tool. The case shows which problems begin to deserve software when building a first answer costs much less.
Read articleStrategy · Product
When creating a first version becomes cheaper, the bottleneck is no longer turning requirements into code. Product leadership comes to mean selecting problems, designing evidence and deciding which options should not survive.
Read articleStrategy · Innovation
If AI reduces the cost of creating specific software, we may not spend less on software. We may build many more solutions for problems that previously did not clear the economic threshold for a project.
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Many organisations reject AI because it is “in the cloud” while already trusting email, documents and customer data to other cloud providers. That contradiction does not prove that AI is safe; it shows that we need to apply the same coherent analysis to every service.
Read articleProduct · Learning
The problem with vibe coding is not the use of AI. It is the removal of the mechanisms that let us understand, verify and evolve software. Repairing such an application begins by recovering a model of the system, not by generating more code.
Read articleInnovation · Product
One person can direct an agent system capable of covering many functions of a software team. That does not remove work or collaboration: it makes context, roles, quality controls and boundaries explicit.
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Waterfall tried to predict. Agile learned to iterate. Agentic engineering reduces the cost of each cycle again. That does not make agile principles obsolete, but it does require us to revisit ceremonies and artefacts designed for a different speed of execution.
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Introducing AI into engineering is not a matter of handing out licences and waiting for productivity. The workflow must be redesigned, the team must agree where AI can help, quality must remain visible and individual discoveries must become team capability.
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The difference is not that an agent writes better. A chatbot holds a conversation; an agent controls a workflow, uses tools, observes the result and decides what to do next.
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Using an AI chat does not mean that an organisation has adopted AI. This framework distinguishes five levels according to autonomy, integration, accountability and the system’s ability to learn.
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A prototype is not there to prove that an idea was good. It helps us discover which part of the idea we still do not understand. Prototype-Driven Development shortens the distance between a conversation, shared evidence and the next decision.
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