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Walk into most marketing conversations right now and someone's showing off what AI produced. A landing page made in minutes, a week of emails in an afternoon, and a funnel plan drafted before lunch.
They exist but they’re not really built as one cohesive system.
A system is what decides how those pieces connect. Which offer the funnel actually serves. What happens the moment someone opts in. What the email sequence does differently on day three versus day seven. AI can generate any single piece on command. It has no opinion about how the pieces are supposed to fit together, because fitting them together was never the part it was asked to do.
This is worth sitting with on an execution day, because execution days are exactly when it's easiest to mistake a fast pile of pieces for a finished system. The page got built. The emails got written. Nothing about that guarantees they were built to work as one thing.
The tools build pieces quickly now. Someone still has to build the system the pieces live inside.
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24-Hour AI Workflow Blueprint — From Business Problem to Practical AI Plan
I developed a practical workflow-review system designed to help small businesses identify where AI can genuinely save time — and, just as importantly, where human judgement should remain in control.
The process starts with a structured business questionnaire covering repetitive tasks, existing software, time-consuming processes, desired improvements and areas that should not be automated.
That information is then analysed to identify bottlenecks, quick wins and realistic opportunities for AI assistance. The resulting Blueprint provides prioritised recommendations, practical workflows, suggested tools and prompts, implementation steps, and clear human/AI boundaries.
I also built and tested the supporting intake and delivery workflow so the complete review can be produced within 24 hours of receiving the required information.
The objective isn't “AI everywhere”. It's less repetitive work, clearer processes and practical improvements that a business can actually use.
This workflow was developed and internally tested as part of a live 30-day commercial AI experiment. No invented client results or hypothetical savings are presented here.
A client shouldn’t have to learn Webflow just to publish their next case study.
On a recent build, I spent a lot of time on the CMS: setting up reusable blocks and the logic that lets the team update content without rebuilding pages.
The tricky part is deciding how much control to give them. Too little, and every update becomes a request. Too much, and they’re suddenly responsible for the layout.
I want them to open the CMS, know what to do, and get on with their day. There’s a fair amount of work behind making that feel simple.
The CMS thinking here is spot on: the best handoff is the one that gives a client confidence without exposing all the complexity underneath.
Agent products resist normal product marketing. There's no single interface to screenshot and the category vocabulary has gone generic, so a feature list communicates almost nothing.
We built Heron's explanation as a four-beat scroll that runs the agent's actual loop. The model appears and is watched. Violations surface with plain language and a real IBC clause. An edit is applied after approval. The system learns the firm's standards.
Pacing was the main design problem. Each beat needed enough scroll distance to register as a separate action, without the section becoming so long that people bail before the payoff. The sequence carries the technical detail that would otherwise sit in a spec table.
The four-beat scroll is a smart way to make the agent’s loop feel tangible—much clearer than a static feature list. The restrained visual system gives the interaction room to breathe.