AI in the SDLC: adoption pressure, delivery discipline
Most teams are adopting AI tooling faster than they are adapting the work around it. The question is where AI changes delivery outcomes, and where it only adds review load.
Read the articleIndependent CIO & CTO advisory
Technology strategy for software organizations.
Marcelis Digital advises CIOs, CTOs and enterprise architecture leaders across the technology agenda.
We turn executive intent into roadmaps, target architecture, team structure, governance and engineering sequence, then stay close enough to execution to make the plan real.
Highlighted points of view
Current takes on the market.
Architecture as a decision system
Architecture earns its place when principles become decisions, tests and consequences. Static diagrams are useful only when they change what teams do next.
Read the articleThe software organization behind engineering speed
Slow delivery is rarely solved by asking teams to move faster. The harder work is reducing cognitive load, shortening feedback and making platform work visible.
Read the articleRoadmaps that make the trade-offs explicit
A roadmap is useful when it ties funding, dependencies, platform readiness and stop rules together. Otherwise it becomes a calendar for unresolved decisions.
Read the articleThe problem
You probably have a strategy. The hard part is making it hold in execution.
Most technology choices at this level fail because strategy, architecture and delivery are treated as separate conversations, held by separate people, using separate evidence.
AI has sharpened the issue. Individual developers feel faster, but delivery metrics can disagree. Pilots accumulate. Delivery does not. The cost shows up later: architecture that documents a system nobody builds, platforms that sprawl without ownership, and roadmaps that collapse into backlogs.
The alternative is a strategy with a working spine: architecture that turns principles into decisions, governance that resolves trade-offs before they become workarounds, teams structured around real services and platforms, and a roadmap the organization can actually absorb.
Engagement starts
Bring the problem, not a polished brief.
Most useful conversations start with pressure: cost, speed, quality, architecture, AI or a decision that keeps coming back. Tell us what is not working. We will help frame the question and propose the smallest serious next step.
Start a conversationFocused assessment and due diligence
A short investigation of a live question before committing to a vendor, program or architecture decision. We review the evidence, separate symptoms from causes and recommend the next move.
Problem-to-plan advisory
For problems framed around cost, speed or quality: CRM replacement, application rationalization, architecture function, AI adoption or engineering speed. We shape the goal, the operating path and the first work worth funding.
Ongoing executive advisory
Recurring senior support for CIOs, CTOs and technology leaders navigating complex sequencing, AI adoption, architecture governance, software organization design or operating model decisions.
Where we help
Topics worth bringing early.
These are common pressure points for CIOs, CTOs, technology directors and senior architects: useful when a problem is too important to leave as a vague workstream, but not yet clear enough to fund with confidence.
AI in the SDLC
Move from AI tool adoption to a way of working: where AI improves delivery, where it adds review load, and which checks must stay close to engineering.
Enterprise architecture
Turn target architecture, standards and fitness functions into decisions teams can use, with clear trade-offs, governance and consequences.
Engineering productivity
Find the system constraints behind slow delivery: team boundaries, platform friction, cognitive load, release risk and feedback loops.
Roadmap and sequencing
Put funding, dependencies, platform readiness, stop rules and governance cadence into an order the organization can absorb.
Why Marcelis Digital
Expert consulting, without the generalist model.
Most technology advisory asks CIOs and CTOs to choose between two imperfect models: strategy teams with limited engineering depth, or implementation partners with a commercial interest in the answer.
Marcelis Digital is built around a different profile: consultants who came from engineering, architecture and technology leadership before learning the consulting craft. They can advise in the boardroom, work with executive ambiguity and understand the consequences for teams, platforms and codebases.
The firm deeply invests in internal tooling, AI and training around those experts. The buyer gets senior judgment, fewer handoffs and advice specific enough for engineering leaders to test.
Next step
Bring us the messy technology problem.
It does not need to be neatly framed. Bring the architecture call no one wants to own, the AI question the board keeps asking, the roadmap that will not settle, or the software organization problem that keeps resurfacing. Start with a conversation, a call or a coffee.
Start a conversation