AI has made the work faster, but business results haven’t moved to match.

I find what’s delaying the value, then mentor your leaders and work hands-on so you deliver more, sooner.

Where the bottleneck is

Many AI rollouts change the tools and leave the organisation alone: who owns what, how work gets chosen, what gets rewarded. I spent ten years as an Agile coach, learning why process and tool changes do little when the wider system stays put. Now I’m an AI transformation lead who starts with the organisation, because that’s usually where the bottleneck really is.

I mentor leaders on how to change the organisation, coach them through it, and build tools I leave behind: one shows where work waits, another helps teams learn from their incidents.

I can drive as much of the change as you’d like, provided you give me the authority to do it and take ownership of the change with me.

Most recently I built and shipped three tools into a 25+ team organisation; only one needed an LLM, and it’s still in use there.

“[AAR Maker] turns a meeting Chris used to facilitate into a structured artifact the team produces continuously. Conservatively saves hundreds of engineering hours a year.”
Christophe Louvion, CTO

Problems I work on

Engineers feel faster, and the business doesn’t see it

The speed-up is real, and the time it saves usually ends up waiting somewhere else: for review, at a handoff, in an approval queue. I start with your delivery data and your people’s own accounts to find where, and what the waiting costs.

“…delivery of products that were viable sooner to our customers and stakeholders.”
SeAnne Cornelia, now Senior Product Manager at Optum (worked with me at Episource)

The bottleneck moved

Writing code got cheaper, so the queue moved to review, decisions and planning. I measure cycle time, throughput, work in progress and ageing across every team’s backlog to find which queue is holding things up. Then your leaders choose what to change, and I mentor them and work hands-on with their teams to see it through.

“He helped us focus our attention on understanding the real value of our work, making smarter priority calls, and mitigating the bottlenecks that had been slowing us down.”
Chris Butler, Manager, Software Engineering, NRC Health

Nobody can show what the AI spend buys

If you didn’t take a baseline before the tools arrived, I build one from your own tracker with Delivery Intelligence: forecast date ranges, and a cost-of-delay ranking that carries a dollar figure wherever the people asking for the work state the value they expect. It measures delivery and the value claimed for it, not the AI spend itself. At my last client it replaced the spreadsheet the leadership meeting used for the roadmap, and a second tool kept the tracker true: teams ran their stand-ups against it, and open issues fell.

“Delivery Intelligence and Quality reporting… surfaces risk and patterns early, so the conversation in the room is informed by evidence rather than impressions.”
Christophe Louvion, CTO

Growing pains, and nobody’s sure who owns what

I work out with you who owns what end to end, then change the team structure and the career ladders to match. At my last client, three value streams across 25+ teams ended up planning together every fortnight, each owning its own backlog, and the CTO and I reworked the career ladders, including how each role would use generative AI.

“Chris put a lot of guidelines in place that gave our [teams] more order in terms of organization and planning which ended up paying huge dividends.”
Isaac Hernandez, now Sr. Software Engineering Manager at Optum (worked with me at Episource)

Adoption stalls, and whoever drives it has no authority

I coded the charters of 50 AI-transformation roles: two carried written authority over structure, incentives, cross-functional design or P&L, and of the 13 reporting to a CEO or board, none did. I can advise your leaders or carry out the agreed work. For hands-on work, they give me the authority to do it and take ownership of the change with me.

“His coaching was evident when senior execs turned up to attend the course without missing any session.”
Venkatesh Krishnamurthy, now Product and Engineering Transformation Lead at Magentus (the trainer I brought in for a client)

Evidence

Reprioritised a whole portfolio at NRC Health

I led prioritisation of NRC Health’s whole epic portfolio with 30+ stakeholders, including C-level leaders, using forced-choice comparisons. Lower-ranked epics were stopped or cut, and work in process fell overnight; throughput rose, and we realised value sooner.

Advised through an acquisition into Optum

Advised Episource’s SVP Product and CPTO through acquisition and integration into UnitedHealth Group’s Optum, and developed their operating model: who decides what, and how work gets chosen and planned. The handbook we ran on there grew into Minimum Viable Bureaucracy: A Field Guide, free online. Managed five coaches supporting a 300+ person organisation, owning their development and performance reviews and hiring one. Speed-to-market and quality improved noticeably.

Lead inventor, PagerDuty patent

For PagerDuty’s OpsDex, I devised and ran regressions on incident data across the entire customer base, excluding research opt-outs, to produce a working operations-maturity index. US 9,367,810 B1 (2016).

One executive hired me four times

Christophe Louvion has hired me into four companies over the 18 years we’ve known each other. References available.

Edmund Hillary Fellow

The Edmund Hillary Fellowship ran New Zealand’s Global Impact Visa in partnership with the government; I was one of 525 Fellows selected from 3,400+ applicants. In 2023 I moderated EHF panels on generative AI’s impact on New Zealand and generative AI for gaming and startups.

My writing

Come Prepared to Die

My book for engineering leaders, serialising now, with the finale due by mid-October 2026. It argues that AI gains keep landing inside delivery structures designed before these tools existed, so the business doesn’t see them until the structure changes.

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