A fixed-fee review and diagnostic for product engineering organizations with 25–80 engineers. I identify the few system-level issues causing delivery drag and give you a concrete 30-day action plan.
Team size
25–80 engineers
Stage
Post-product, with operating history
Owner
Founder, CEO, CTO or VP Eng
Not for
Interim CTO or hands-on coding
Growth was supposed to make delivery more predictable.
You know something is off. The hard part is that the visible symptoms are rarely the real cause.
Offers
Not sure yet? Start with the Review. If you book the Diagnostic within 30 days, the full Review fee rolls into it.
Outside read
A fast outside read before committing to a full diagnostic.
Core engagement
A bounded diagnosis of why delivery slowed and a 30-day action plan.
15 business days. Bounded by design.
Most leadership teams spend 3–5 hours total. Interviews are targeted, not open-ended.
01
Leadership context, current friction points, and the core operating artifacts: org structure, planning rhythms, delivery signals, team setup.
02
A focused set of conversations across leadership and selected team members to understand where delivery drag is actually coming from.
03
Mapping the few issues causing the most operational friction across org design, planning, management load, ownership, and team structure.
04
A clear diagnosis, the evidence behind it, and a practical 30-day action plan.
What you get
The Diagnostic report is structured for leadership to act on quickly.
Series B marketplace, 55 engineers in 6 squads, delivery slowing after a platform rearchitecture. The next roadmap slipped by nine weeks.
Executive summary
Delivery has slowed because the rearchitecture shifted ownership boundaries faster than the org structure absorbed.
Root cause 1
Payments ownership is contested. Three squads each have documented ownership of parts of the payments flow. Every cross-squad change now requires coordination no one planned for.
30-day plan · Week 1
Split the payments domain along a single clear axis: auth-to-checkout vs. settlement-to-reconciliation. Assign each half to one squad.
Risk to watch
If the payments split happens but the planning rhythm doesn't, the split won't hold.
Anonymised by default.
Industry, region, and engagement type are enough to show the shape of the work. The recurring engagement: choose the technology, direct the people who run it, and be accountable for what happens after.
References available on request, under NDA where appropriate.
Technical leadership and advisory
Engaged to make the foundational technical decisions for a new product rather than to write it. Selected the stack — Vue and Node on TypeScript, across Azure, AWS and Google Cloud — defined the developer roles the build would need, and hired into them. Led development through to a fully operational product, then handed over and exited. Nearly three years, ending by design rather than by attrition.
Systems delivery and integration
Why me
Current operator.
I lead engineering in a live scale-up environment. My perspective comes from the operating seat, not retrospective consulting theory.
Pattern recognition across engineering systems.
I've spent 20 years across IC, management, and leadership roles in multiple industries. The same failure patterns repeat more often than founders think.
Real AI adoption experience.
I designed and ran three AI adoption pilots in a real organization. That connects AI to delivery, hiring, and team design — not just tooling.
Post-product software companies where engineering grew, management layers appeared, and delivery became less predictable.
This is a bounded diagnostic. Sharp, fast, and specific. It is not the right engagement if:
Contact
I take on a small number of engagements at a time. Expect a response within 2 business days.
Prefer direct?
petar@deseirose.com