The board
Dutch B2B commerce · Blueprint prototype, 2 weeks
Agents take the order. People keep the decisions.
An urgent order in minutes, not an hour
- Building an AI toolShould we build a custom AI tool or buy SaaS?Buy SaaS when your process matches how the tool works. Build when the work is yours alone: your approvals, your exceptions, your mix of systems. Then watch the gaps. If people copy data between tools every week, those hours are the budget. A custom tool earns its cost when it removes them.
- Getting your team to use itWhy do AI pilots stall before real use?AI pilots stall because a demo only proves the tool can work. Real use needs a team to choose it every week. Pilots stall in 4 places. The build never fit a real job. The team keeps the old spreadsheet. Nobody trusts the agent to act. 1 wrong number in a money flow ends it.
- Getting your team to use itWhy do users stop using AI features after the first week?Because the first week runs on novelty, and novelty is not a job. The demo moment amazes, then the blank prompt box starts asking the user to work. A feature survives when it attaches to something the user already does every week. Most AI features live in their own tab, waiting. Habits do not form in tabs nobody opens.
- Getting your team to use itHow do you get a team to actually use a new AI tool?Design the first week of use as carefully as the tool. Put it where the task already starts, so nobody has to remember it. Fill the first step in for them. Show what the agent did and let people correct it. Then track weekly use after launch, and fix what people skip.
AI SaaS · Built solo, live at proux.design
Agents do the research. Every answer cites its source.
Every answer cites its source, across 350+ UX principles
- Getting your team to use itWhy do AI apps lose subscribers faster than normal apps?Because the wow moment is not a habit. RevenueCat's 2026 data puts AI app annual retention at 21.1%, against 30.7% for everything else. The demo converts, then daily life asks a harder question: is this still worth opening. Most AI apps never design for that question. They monetize the novelty and lose the month 2 user.
- Trusting AI with moneyHow do you stop an AI agent making a mistake with money?You limit what it can do alone. The agent pays only inside the rules you set: approved payees, a limit, a monthly budget. Each payment waits 10 minutes before it goes out, so you can undo it. Anything outside the rules waits for a person. Every step is logged, with the rule it followed.
- Trusting AI with moneyWhy does 1 wrong AI answer break trust in my product?Because trust in software is asymmetric. 10 right answers build it slowly. 1 confident wrong answer spends it all at once. Loss aversion runs the math. A wrong answer is a loss, and losses weigh about twice an equal gain. The fix is not a better model. It is designing the recovery, the moment after the mistake.
- Trusting AI with moneyHow do you fix drop-off in fintech onboarding and KYC?People quit KYC when a step asks for trust it has not earned. Compliance sets the rules, so the fix is the order, the reasons and the effort. Say why before you ask. Let an agent read each document and fill the form. The customer only checks what it flags. Let people stop and resume.
- Being found by AIHow do ChatGPT, Claude, Perplexity and Google read a product site?They read the words people can see. Google crawls, renders and ranks, and uses structured data for rich results. AI assistants like ChatGPT, Claude and Perplexity fetch the page text and quote it. Most never see code hidden in scripts. So the answer has to live in the visible copy, worded the same on every page.
- Being found by AIWill AI shopping agents kill my store's conversion?Not kill. Reroute. AI agents already comparison-shop, fill carts and complete checkouts. The buyers behind them still decide who earns the sale. 2 funnels now matter: people who need trust and agents who need structure. Stores designed for both convert both. Stores designed for neither lose quietly to whichever competitor answered the agent first.