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Training options, not one fixed course

Every QA team starts from a different place. Some need a clear picture before committing. Some need skills quickly. Some want the framework itself to change, or want agents doing real work in it. Pick the option that fits, or let us suggest one after a call.

Every option is instructor-led AI test automation training first. When we set something up, like an AI-ready framework or an agentic system, we build it with your engineers and teach them to run it. They keep the skills after we leave.

Most teams follow this path: Assessment → Core or Accelerator → Coaching. Any option can start as a pilot with 3–5 engineers.

Built into every option

  • Instructor-led, with your engineers. Live sessions and hands-on work on your own code.

  • Before/after measurement with a results report. How we measure results

  • Manager check-ins at kickoff, mid-point, and final readout.

  • Your framework: Playwright with TypeScript/JavaScript, Cypress, or Selenium + Java.

  • Your approved AI tools, private cohorts of 3–15, remote or on-site.

  • NDA, no production data or personal data, and everything produced in your repo belongs to you.

  • GitHub Copilot
  • Claude / Claude Code
  • ChatGPT Enterprise / Codex
  • Gemini / Gemini Code Assist
  • Cursor
  • Amazon Q Developer
  • Windsurf
  • JetBrains AI
  • or whatever your company has approved

Tools we train on. Not partners or clients.

We train on the AI tools you already have.

We start with the tools you already have. Your team learns on whatever your company has approved, inside the framework it already runs.

  1. AI Readiness Assessment

    2 weeks

    1. Understand
    2. Build skills
    3. Keep it sharp
    Who it’s for
    Teams that want to start small, or leaders who need a clear picture before choosing a training program.
    Format
    A practical skills check, short interviews with a few engineers, read-only repo access or screen-share, and a readout with you and engineering leadership.
    The outcome
    A skills baseline for your team, a scored audit of your test framework, how far AI adoption has actually gone, and a prioritized training and improvement roadmap: quick wins, 30 days, 90 days. You also get our honest recommendation, including “you can do this yourselves” if that's true.
  2. Core Enablement

    4 weeks

    1. Understand
    2. Build skills
    3. Keep it sharp
    Who it’s for
    QA teams that need AI skills quickly, in the framework they already use.
    Format
    Live sessions plus hands-on labs on your own code, with office hours. Standard, lighter, or extended pace.
    The outcome
    Every engineer learns to use AI for test design, automation, and maintenance in your codebase, and to review what the AI produced. Each engineer finishes with a pull request in your repo, reviewed under your normal process. The team keeps a prompt library, AI instruction files tuned to your repo, an AI usage policy, and a review checklist. You get a before/after results report and a 30-day follow-up.
  3. Accelerator

    8 weeks

    Includes Agentic QA setup

    1. Understand
    2. Build skills
    3. Keep it sharp
    Who it’s for
    Teams that want the skills and a better framework, with AI working in the framework and in CI, and productivity measured during real delivery.
    Format
    Starts with the full Assessment. The first half builds skills; the second half applies them to your framework and your real work, with the instructor pairing with your engineers and reviewing PRs.
    The outcome
    Everything in Core, plus Agentic QA setup: we set up an agentic system in your framework with your engineers, and train them to run, extend, and review it. You also get a framework that AI tools can work with well, AI-assisted failure triage and reporting in CI, a coached sprint on your real backlog, productivity data from that sprint, internal AI champions to keep it going, and a 90-day roadmap. Follow-ups at 30 and 60 days.
  4. Manual-to-Automation with AI

    8 weeks

    1. Understand
    2. Build skills
    3. Keep it sharp
    Who it’s for
    Manual testers who know your product well but don't write code yet.
    Format
    Builds from coding basics to automation in your own framework. Skills are measured on coding fundamentals as well as AI use. This is where Techtorial's experience turning beginners into test engineers matters most.
    The outcome
    Manual testers learn to contribute Playwright tests in your framework, reviewed by a senior engineer on your team, with AI used as a tutor and reviewer, not a crutch.
  5. Coaching retainer

    Monthly, after any of the options above

    1. Understand
    2. Build skills
    3. Keep it sharp
    Who it’s for
    Teams that finished a program and want the habits to stick while the tools keep changing.
    Format
    Remote. Scope agreed in the proposal.
    The outcome
    Ongoing coaching: regular group office hours, async PR reviews with feedback, periodic metrics check-ins, and short sessions when new AI testing tools are worth your time.

Add-ons

Usually 1–2 weeks each. Agentic QA setup is scoped to your team in the proposal.

Each add-on works alone or alongside Core or Accelerator, and each one is taught: your engineers do the work with us and learn how to continue it.

Add-on · included in the Accelerator

Agentic QA setup

We set it up with you. Then we teach your team to run it.

Who it’s for
Teams whose engineers already use AI and now want agents doing real work in the test framework, not just chat help.
The outcome
Together we build an agentic system inside your own framework: coding agents, conventions and instruction files, skills, MCP servers, sub-agents, and AI in CI, set up for the AI tools your company has approved. Your engineers learn to run it, extend it, and review what it produces, so routine test work moves faster with a human review on every change.
Format
Hands-on, in your repo, with your engineers doing the setup alongside the instructor. Ends with a handover so your team owns and maintains it. Included in the Accelerator.
  • Coding agents
  • Conventions and instruction files
  • Skills
  • MCP servers
  • Sub-agents
  • AI in CI

Agents draft. Your engineers review and merge.

your-repo/AGENTS.mdCLAUDE.mdcopilot-instructions.mdskills/mcp.jsontests/plannerplans the testsgeneratorwrites the codehealerfixes broken testsMCP: browser, toolsCI pipelineyou reviewyour-repo/AGENTS.mdCLAUDE.mdcopilot-instructions.mdskills/mcp.jsontests/plannerplansthe testsgeneratorwritesthe codehealerfixesbroken testsMCP: browser, toolsyou reviewCI pipeline

Also available

  • Selenium/Java to Playwright migration with AI

    Your engineers learn a migration approach and migrate one slice of your suite with us, with checks that the results match.

  • API testing in depth

    Contract tests, test data, and chained API flows, taught on your own services.

  • Leadership session

    A half day for QA managers and engineering leadership on AI in QA strategy, agentic workflows, what to measure, and policy and risk.

  • Mobile (Appium) and performance smoke testing with AI

    On request.

Not sure where to start?

Get a proposal for your team

Tell us your team size, your framework, which AI tools you have, and what you want to improve. We'll come back with a recommended option, a schedule, and what we'll measure. Pricing is in the proposal.

proposal-for-your-teamRecommended optionScheduleWhat we'll measurefor your team