Engagement model

A calm, senior engagement model.

No offshore handoffs, no padded teams, no account managers in front of the builders. You work directly with the people writing the code, in short cycles that ship production software from week one.

In one paragraph

Wai Tech engagements run in four phases: Discover, Design, Build and Operate, with direct access to senior engineers and designers throughout. Work runs in short cycles with weekly production releases, and AI is embedded across delivery, from discovery through to production systems. The result: platforms ship in roughly half the conventional timeline, without compromising on quality or control. Most builds run 2–6 months; audits run 2 weeks.

Four phases

Discover, Design, Build, Operate.

The shape is simple on purpose. Each phase has named outcomes and a specific cadence, so you always know what to expect next, so you can step in and steer at any point.

01 · DISCOVER

Listen first, with AI as the note-taker.

A week of working sessions to map the problem, the users, the business model, and the constraints. We synthesise interviews and competitor teardowns with LLM tooling, so the brief lands in days, not weeks. You leave with a shared document, not a pitch deck.

Artefacts
  • Problem brief
  • AI-synthesised interview notes
  • Competitor & AEO teardown
  • Named success metrics
1-2 weeks
02 · DESIGN

Prototype in days.

Low-fi to clickable prototype inside the first fortnight. AI generates first-pass variants in v0, Lovable and Figma AI, senior design picks, refines and pressure-tests against real data. You click through the product before the architecture is committed.

Artefacts
  • Clickable prototype
  • Component library
  • Architecture decision records
  • Delivery plan
1-3 weeks
03 · BUILD

Ship weekly, AI in the loop.

Direct collaboration with senior engineers, shipping in short cycles with production releases from week one. AI is embedded into the development workflow, alongside testing, observability and release management. You see progress continuously, not in batches.

Artefacts
  • Production releases
  • Evaluation harness
  • Observability dashboards
  • Sprint retros
2-6 months
04 · OPERATE

Stay close.

SLAs, observability, and on-call rotation, or a clean handover. LLM-assisted runbook generation, AI-drafted incident post-mortems, and monthly AEO scorecards so your platform keeps getting cited as it grows.

Artefacts
  • SLA + on-call
  • Auto-generated runbooks
  • AEO monitoring
  • Transfer-of-ownership plan
Ongoing / handover
Engagement models

Four shapes. Pick the one that fits.

Most of our work falls under ‘Retained squads’. But not every problem needs one, and we don't dress up a two-week audit as a six-month contract. Here are the four shapes we actually offer.

Retained engagement

Ongoing access to a senior team working directly on your platform. We prioritise outcomes over headcount, aligning work to a shared roadmap and shipping continuously.

Best for
Ongoing product build
Typical term
3–12 months

Fixed-scope project

A clearly defined outcome with scope, success criteria and delivery plan agreed upfront. Used for launches, rebuilds, or critical platform components.

Best for
Bounded deliverables
Typical term
4–12 weeks

Embed + accelerate

Senior engineers work alongside your team to unblock delivery, improve velocity and lift engineering standards in real time.

Best for
Capability uplift
Typical term
2–6 months

Audit + plan

A short engagement focused on clarity. We assess your platform, identify risks and opportunities, and deliver a practical plan forward.

Best for
Before committing
Typical term
2 weeks
Team & AI tooling

Senior-only. AI in every hand.

Every engagement is led by senior engineers and designers, working directly with you. AI is embedded across delivery, not as a feature, but as part of how the work gets done. That combination is where the speed and quality come from.

Engineering

TypeScript, Next.js, Go, Python, Postgres, AWS, paired with Claude Code, Cursor and GitHub Copilot for every engineer.

Design & prototyping

Figma with AI-assisted variants (v0, Lovable, Figma Make). Senior design refines the output, not the blank page.

Delivery

Linear / Jira, GitHub, Slack, with LLM-assisted PR review, auto-generated release notes and incident post-mortems.

Observability & evals

Sentry, Datadog, OpenTelemetry, plus evaluation harnesses for every AI-powered feature we ship. No shadow-mode AI in production.

Frequently asked

How we actually run.

Still unsure? Send us a note, we reply within one business day.

How large are your teams?
We don’t structure engagements around fixed team sizes. You work directly with senior engineers and designers, and we scale involvement based on what the platform actually needs, not a predefined shape.
What ceremonies and cadence do you run?
Work runs in short cycles with weekly production releases. We keep coordination lightweight, with focused planning and review sessions, and async updates in between to protect deep work.
How do you handle communication with our team?
Shared Slack (or Teams) channel with your engineers, a shared Linear/Jira project, a shared Figma file, and a shared docs space. The same tools we use internally, no vendor walls.
Who owns the code and the IP?
You do. All source code, design files, infrastructure, and decisions sit in repositories and accounts that you own. Wai Tech commits against your main branch.
What does pricing look like?
Most engagements run on a monthly retainer priced against team size and capacity. A retained senior squad of four starts around AUD $65k/month. Fixed-price projects are quoted per scope. We share pricing openly on the first call.
Do you work on-site or remotely?
Remote-first, on-site for discovery kickoffs and key milestones. Our team is based across Australia, New Zealand, and the UK, so we can cover working hours in AU, EU, and most of the US.
How do you handle handovers at the end of an engagement?
A four-week overlap by default: paired pull requests, runbooks, architecture decision records, and a live on-call shadow. We only consider an engagement done when your team is confidently running the system in production without us.
How do you use AI in delivery?
Aggressively, and deliberately. Every engineer pairs with Claude Code or Cursor for production code. First-pass UI is generated with v0, Lovable or Figma AI and refined by senior design. Discovery notes and competitor research are synthesised with LLM tooling. For any AI-powered feature we ship, an evaluation harness ships alongside it. The compounding effect is real: most builds deliver in roughly half the time a conventional studio would quote, without compromising on code quality.
Can you help us show up in ChatGPT, Claude and Perplexity?
Yes. Our Answer Engine Optimisation (AEO) practice runs citation audits across ChatGPT, Claude, Gemini and Perplexity, re-engineers content and schema so LLMs can cite you cleanly, and sets up monthly scorecards tracking citation share, paraphrase accuracy and outbound click-through. Every site we build is AEO-ready by default.
What about evaluations and safety for AI features?
Any AI-powered feature we ship has an evaluation harness built alongside it: golden-set tests, regression checks across model versions, and observability on prompt/response pairs. We also set up feature flags and kill-switches so you can roll AI features back safely if a new model version misbehaves.
Start a project

Ready to ship?

A short note is enough. We'll reply within one business day with a named lead and a few good questions, not a form letter.