Every team is different.
The outcome we’re after isn’t.
Three different businesses. The same pattern: real money going in, not enough clarity coming out.
Here's what happened next.
CASE STUDY 1
From AI experiment to production
RESULTS AT A GLANCE
Two AI vendors tested
One in production
One $30K USD-a-month vendor stopped
The problem
The company was running parallel pilots with two AI vendors and needed someone to bridge business stakeholders, technical teams and the vendors themselves.
One pilot had become hard to judge. There was little visibility into how the product was built, how releases were managed, how quality was tested or how the AI's rules worked.
The vendor relationship had blurred too, making it hard to separate partnership optimism from evidence.
What I did
I brought structure and accountability to both pilots. I documented commitments, tracked issues and defects, chased open questions and pushed for clear answers on the vendor's development and QA processes.
As concerns kept recurring, I gave leadership a candid view of the risk of continuing.
On the second pilot, I supported testing, helped internal teams understand the product and prepared them for rollout.
The result
Leadership had the evidence to make two very different calls.
For one vendor, the delivery, quality and transparency concerns supported stopping, ending an $30K USD-a-month spend.
For the other, the team finished testing with confidence and took ownership of the rollout. It's now used in Operations.
Why it worked
I was there to help leadership understand what was actually happening, weigh the evidence and make the right call.
CASE STUDY 2
Regaining control of scope on a fixed-fee project
RESULTS AT A GLANCE
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30+ backlog requests triaged
Scope changes handled as explicit change requests
Phase 2 delivered a week ahead of the agreed timeline
The problem
I joined as Phase 1 was wrapping up. It had seen significant scope creep, and there was real concern about whether the next fixed-fee phase could be delivered profitably.
More than 30 extra requests sat in the backlog, and new asks kept arriving through code review comments, Slack side channels and stakeholder conversations.
What I did
I worked with the development team and client stakeholders to set clear expectations on scope and priorities.
I watched new requests as they landed, challenged anything outside the agreed scope, and made sure informal asks didn't quietly become commitments. When something new was worth more than existing work, I ran the prioritization so lower-value items came out instead of piling more on.
I worked through the 30+ requests to decide which became formal change requests, which closed, and which the client's own team should own. Internally, weekly updates rebuilt executive confidence in the engagement.
The result
Phase 2 started with clear expectations on both sides.
Scope changes became explicit decisions, not hidden additions.
The team could say yes to valuable new requests without losing control of the original commitment.
Why it worked
A good “no” comes with a reason and a better use of the team's time.
CASE STUDY 3
Getting an ecommerce platform back on track
RESULTS AT A GLANCE
$100K+ already invested
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Launched three months after the reset
Visible capacity gains within four weekly sprints
The problem
More than a year into an ecommerce rebuild, the business had spent over $100K with very little visibility into what was done, how much was left or when the site could launch.
The Product Owner was juggling a design role while coordinating an overseas development team, without enough product or delivery support.
What I did
I set up a structured delivery approach in Jira: one-week sprints, sprint goals, story pointing and clear ticket ownership.
I mentored the Product Owner through consolidating requirements from several documents into one backlog, and we worked out the team's real capacity.
We split launch-critical MVP scope from everything else, such as data migration, payments and shipping.
I also set up regular stakeholder reporting on progress, remaining work, risks and timelines.
The result
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A clear view of the work left before launch
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A prioritized, structured backlog
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Reliable delivery data for planning
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More confidence in the development team's capacity
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A realistic launch plan leadership could understand and track
The engagement was extended through go-live, and the site launched three months after the reset.
Why it worked
The turning point was creating honest visibility into the work, the remaining effort and the team's real capacity.
