The Interview, Analyze, Execute method, how we approach every engagement

Every engagement we take starts the same way. We sit with your team for ninety minutes a workflow, watch what is actually happening (not what the org chart claims), score your data and vendors for AI readiness, and ship a thin slice in week one. Then we expand from there.

Why the method exists

The method has a long arc. A few years back, three of us under the CaziSoft banner ran a multi-week evaluation of a midsize industrial operator. We talked to operators, engineers, finance, ops, leadership. We mapped what their systems claimed to do against what they actually did. The deliverable was a two-hundred-plus-page operational scan. That scan uncovered the opportunity that became a spun-out QA/QC product.

What we kept from that work is the rhythm. Not the page count.

Interview

We meet your people where the work happens. Sixty to ninety minutes per workflow. We listen for what the org cannot say about itself: the workarounds, the post-it notes, the spreadsheet that everyone secretly relies on. We do not assume the system of record is the system of truth.

The output of Interview is a stakeholder map, a workflow inventory, and a sharp list of automation surfaces. Nothing built yet. Nothing promised yet.

Analyze

We score your stack against where AI moves the needle. Where the data is clean enough for an agent to act on. Where a vendor is locking you in. Where there is a high-friction process that one well-scoped automation could compress by 80 percent.

We come out the other side with a bottleneck map, a quick-wins shortlist with budgets, and a build-versus-buy recommendation. If we think we are not the right studio for the job, we say so here. The fastest way to lose trust is to recommend the work you can sell instead of the work that should be done.

Execute

We ship a thin slice in week one. One agent, one workflow, observable. Evals at every step. We expand from there with two-week vertical slices.

The slice has to be real. It has to be live in staging. It has to be something you can click. The deliverables ratchet from there: orchestration layer, eval harness, observability, runbook for your team. By week six we have a thing that exists in production, with real users, with the seatbelt of an evaluation suite catching drift.

What this looks like in production

We have used this method to:

• Ship Smile PreVue (live on iOS + web, Vertex AI Gemini 3 Pro under HIPAA + BAA)
• Build Howdy Dispatch from zero to paying fleets (multi-tenant FastAPI, Capacitor iOS, Stripe billing)
• Rebuild a national nonprofit's online presence as a multi-tenant platform (in stealth)
• Pilot a B2B retail layer for RunLink across 45 stores

Every one of them started with someone telling us what they were doing wrong. Not what they wanted to build.

When to call us

When you have a problem worth shipping and not enough bandwidth to run the discovery yourself. When your team has tried the off-the-shelf AI tools and they did not stick. When you suspect there is leverage hiding in your operations and you do not trust a Big-4 firm to tell you what to build instead of how to build it.

We will tell you whether we are the right studio. And if we are, what the first week looks like.

Tell us what is broken at hello@yikesdude.com, or start a project.