Patterns we see repeatedly.
Short, opinionated writing from inside real revenue systems. No content calendar. Only things worth saying.
Why growth stalls after early traction
A practical breakdown of why the system that built your first $10M creates drag on the next $20M — and what has to change structurally, not just operationally.
The stage definition problem nobody talks about
Most pipeline inflation isn't caused by bad reps. It's caused by stage criteria that measure seller activity instead of buyer commitment.
Why forecasts decay over time
Without a shared definition of what 'evidence' means in a deal, forecasts become a negotiation between sales optimism and finance conservatism. Neither is right.
The hidden cost of solving the wrong problem
More pipeline, more tools, more headcount. When the underlying constraint is misunderstood, additional effort compounds the problem instead of solving it.
When AI makes your GTM worse
AI amplifies the system underneath it. If the system is misaligned, AI makes misalignment faster and more expensive. The diagnosis has to come first.
ICP drift — the silent revenue killer
ICP drift happens slowly. The accounts you're winning today look different from the accounts your product was built for. By the time it shows in metrics, the damage is done.
Growth engines vs. growth amplifiers — why more isn't working
Adding more pipeline, tools, or headcount to a broken revenue engine doesn't fix it — it scales the inefficiency. The engine has to be right before amplification makes sense.
The GTM revenue flywheel — how B2B growth compounds
Most B2B revenue systems run in parallel, not in sequence. The flywheel is a different design — where every stage produces signal that improves the next cycle of growth.
What these patterns look like in practice.
Narrative accounts of real engagements. Names and details anonymised by request — context available on a call.
14% → 22% win rate
The pipeline was full. Revenue was flat.
Read full case study →Forecasting58% → 84% forecast accuracy
The board wanted predictability. The team was guessing.
Read full case study →GTM Alignment94 → 58 day sales cycle
Sales cycles had doubled. The ICP had quietly changed.
Read full case study →MisdiagnosisExecution pressure → clarity
Fixing the 'obvious' problem made growth worse.
Read full case study →AI & ToolsMore signals → less clarity
AI increased activity but reduced GTM clarity.
Read full case study →The knowledge base.
The operating model, the playbooks, and a plain-English guide to every agent.
Recognise any of these patterns?
The diagnostic is the fastest way to find out which one is actually limiting your growth.
Start with a diagnostic