Where to start, what to leave out and what really happens in the first six months – without promises that do not hold.
A realistic course month by month — with the dip in month two, the three points where most people stop, and the signs that it is holding.
How tool sprawl arises, which four questions to ask per tool, and how to get from twelve to five in three steps without losing data or processes.
How many attempts are defensible, at what intervals, and what separates helpful following up from irritating — with the stop rules.
Five messages with purpose, spacing and content — why the first has to arrive within minutes, and what must not appear in any of them.
A points model with eight criteria that holds up even with few closed deals — separating fit from behaviour, and using negative points.
The step from a single request to a repeatable process — the three readiness conditions and the places a human has to stay.
Sorted by task rather than by vendor — with an assessment of effort, benefit and risk, and a clear recommendation on which three to start with.
The break point where most automation fails — with the definition both sides have to sign, the three handover models, and what happens to rejected leads.
Licence, setup, upkeep and the items that appear in no quote — with a worked calculation for three company sizes and the question of when it starts to pay.
The order of adoption decides whether the rest works: which building block comes first, and which four to leave out at the start.
MCP is the open standard through which AI systems access your own data and tools. How it differs from a normal interface, and what to settle first.
