Why now: the timing window

Timing arguments are cheap, so this one is specific. Three independent clocks have to read the same time for this venture to work: the technology has to be able to carry consulting production, the beachhead market has to be forming, and the incumbents have to be unable to respond. All three are aligned now, and each one moves.

Clock one: AI crossed the production threshold

Until recently, AI could draft fragments of consulting work; now it carries whole production workflows. The current generation of frontier models one-shots tasks that were previously team-scale — the most cited public example is a 50-million-line code migration completed in a day that had been scoped at two team-months — and the agentic pattern of long-running, self-checking work loops has moved from demos into production at the companies that build these systems. The production layer of consulting (research, analysis, synthesis, documentation, monitoring) is precisely the work this generation does well, at a cost of dollars per deliverable rather than salaries.

The capability proof matters because the alternative explanations have run out. When an ASX-listed property group puts an AI agent over its SAP estate and 700 staff use it in production within 18 weeks of business-case approval, the question “is the technology ready?” is settled for the class of work we’re proposing to do.

And the threshold isn’t only that AI can carry production — it’s that agentic workflows now let the advisory process itself be rebuilt, not just sped up. This is the move the incumbents are not making: they bolt a copilot onto the existing motion to write the deck a little faster, leaving the process underneath unchanged. AI-native advisory — redesigning what the work is — is open precisely because the firms with the judgment are treating AI as an accelerant rather than a redesign.

The proof is loudest in law — the regulated profession furthest down this path. Harvey reached an ~$11B valuation delivering AI-native legal work at premium prices, and Legora hit $100M in annual recurring revenue inside 18 months — evidence that AI-native professional delivery commands value, not discount pricing, even in a liability-heavy field. The same curve is coming for the rest of professional services, including the work we do.

Clock two: the cohort is forming now

The companies our beachhead serves are being created in this window, not at some future point. Renewables passed 51% of Australia’s National Electricity Market in late 2025; the market operator’s 2026 system plan locks renewables, storage and transmission in as the build-out path to 2050; and the Renewable Energy Zone programme is bringing newly formed delivery entities into existence with hard digital obligations from day one. Industry practitioners describe 2026 as the year operators stop treating digital as an innovation project and start running it as their primary lever.

Formation timing is the wedge’s advantage. Greenfield is where AI-native delivery is most effective (the documented productivity gap between greenfield startup contexts and brownfield enterprise environments is roughly 100× versus 10%), and the embedded position is only available before a company builds an internal function. Once this cohort matures, the entry changes from “be the function” to “displace one”, and the economics and sales motion both degrade. The broader segment — regulated organisations that can’t afford to staff their compliance load — is not time-limited in the same way; but the renewables wedge, the cohort forming right now, is.

Clock three: incumbents are paralysed, not asleep

Most incumbents have mis-sized what’s happening — pricing AI as a five-to-ten-percent efficiency gain rather than the order-of-magnitude shift it is (section 2). And the minority who do grasp the magnitude can’t respond without dismantling the pyramid that pays their partners, so their observable behaviour is margin protection: graduate intakes cut roughly 30% at PwC and KPMG, 18% at Deloitte, 11% at EY, while delivery economics stay intact. AI is being layered onto their model, not allowed to replace it.

The sharpest magnitude signal comes from the top of the adjacent profession. The world’s largest law firm, Kirkland & Ellis ($10.6B revenue), is reportedly spending around $500M building its own internal AI platform — its chairman’s framing is that commodity tools have “raised the floor for everyone, but we don’t get hired for the floor.” That is not a firm that thinks this is a 5–10% tweak. But a half-billion-dollar self-build is an option only the giants have: the regulated scale-ups we serve can’t build it, can’t buy it at that scale, and can’t hire it — which is precisely the opening.

This is the textbook structural trap, and it does not last forever: the analyst who named the services-as-software category puts an 18-month horizon on providers demonstrating real AI-native delivery before being excluded from new mandates, and credible AI-native entrants are already forming overseas — Unity Advisory raised US$300M to do senior-only, AI-native CFO advisory; Distyl reached a US$1.8B valuation on AI-native enterprise delivery.

What closes the window

Three things, on different timescales. The cohort window closes as beachhead companies build internal teams — a 2026–2028 phenomenon. The differentiation window closes as “AI-native” stops being a distinction and becomes table stakes — the 18-month repricing clock. And the cost arbitrage narrows as subsidised inference normalises: enterprises now actively manage AI spend (98% of them, up from 31% two years ago), and the cost advantage will accrue to firms that engineered for token efficiency from the start rather than bolting AI onto old delivery.

None of these clocks says “wait and see”. Every quarter of delay surrenders formation-stage clients to whoever moves first, and the referral dynamics in a small market mean the first credible player sets the reference point. The honest tension — moving fast against the founding team’s employment constraints — is treated explicitly in the roadmap rather than wished away.

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