Training course · Lovable · Consulting

Lovable for Consultants

Build web apps from prompts: take Lovable from idea to a working React app with Supabase backend, GitHub sync and deployment.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“Lovable for Consultants” is designed for roles such as Management and strategy consultants, IT and process consultants and In-house consulting teams and shows step by step how to use Lovable productively, safely and transparently in Consulting – from the fundamentals to advanced workflows.

Lovable lets you build web applications simply by describing what you need, with no programming knowledge required. In this course, business users from marketing, sales, HR, operations or product management learn how to turn an idea into a clickable, working application within hours: a landing page for a campaign, an internal tool for logging requests, a simple customer portal or a prototype that helps you pitch an idea convincingly inside your organisation.

The course is hands-on throughout. You work on a small project of your own and learn to state requirements clearly, store data securely, set up logins and publish the result. Just as important is a realistic perspective: which projects you can deliver without IT support, when to involve IT or your data protection officer, and how to hand a successful prototype over to a development team. That way you use Lovable productively without creating shadow IT or security risks.

Consulting thrives on rapid onboarding, structured analysis and persuasive communication – exactly where generative AI makes a difference. Consultants use AI assistants to get up to speed on new industries, synthesise interview notes, build hypothesis trees, analyse client data and develop storylines for steering committees. AI agents support desk research, document comparison and first slide drafts. At the same time, AI is reshaping the business model: clients expect faster results and ask what value consultants add beyond what they could generate with AI themselves. Consultants who use AI confidently shift their time from grunt work towards judgement, implementation support and relationship building.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Management and strategy consultants
  • IT and process consultants
  • In-house consulting teams
  • Independent consultants
  • Analysts and junior consultants

Typical challenges we address

  • Short ramp-up time for new clients, industries and topics
  • Large volumes of interviews, documents and data under time pressure
  • Heavy effort for slides, reports and proposals
  • Confidentiality of client information when using AI

What you will be able to do

  • You describe requirements in a way that lets Lovable generate a usable web application.
  • You create a landing page with a form and publish it on your own.
  • You build an internal tool with login, data storage and roles without any coding.
  • You develop clickable prototypes and use them to align with stakeholders.
  • Accelerate onboarding, research and synthesis in consulting projects with AI.
  • Develop structured storylines, slides and proposals with AI support.
  • Use AI in client work in line with confidentiality obligations and communicate its use transparently.

Course outline

Module 1 From idea to first draft
  • What Lovable can do and what happens behind the scenes, explained plainly
  • Breaking an idea down into goal, user groups, pages and content
  • Writing your first prompt and judging the result
  • Making small, precise change requests instead of starting from scratch
Module 2 Landing pages and web presence
  • Campaign and event pages with a clear message and call to action
  • Adding images, copy and your corporate design
  • Contact and registration forms that store submissions
  • Checking how pages look on mobile and desktop
Module 3 Internal tools and forms
  • Building input forms, overview lists and simple dashboards
  • Storing data in a database without writing SQL
  • Setting up logins and roles: who may see and change what
  • Spotting typical errors and fixing them with the undo history
Module 4 Customer portals and prototypes
  • Simple portals for customers or partners with a protected area
  • Clickable prototypes for product ideas and stakeholder presentations
  • Collecting feedback and implementing iterations in a focused way
  • Handing a well-documented prototype over to development or IT
Module 5 Publishing, security and ground rules
  • Publishing your app and making it available on your own domain
  • Personal data, GDPR and coordination with IT and data protection
  • Costs, usage limits and realistic effort
  • Recognising when a project belongs in professional developers’ hands
Module 6 Hands-on project: your own solution for Consulting
  • Interview synthesis board – A small app where interview notes are uploaded, tagged by theme and displayed as an overview with quotes for each topic area.
  • Bid checklist – An internal tool that captures requirements from tenders, maps them to proposal sections and highlights open items before submission. Formal exclusion criteria are flagged separately.
  • Benchmark calculator – A simple web app that compares a client's KPIs with stored reference values and highlights deviations graphically. Sources and dates of reference values are documented transparently.
Module 7 Data protection, quality & transfer to daily work
  • Client information is usually covered by confidentiality agreements and may only be processed in AI environments cleared contractually and under data protection law. AI use should be agreed with the client, and personal interview data must be handled in line with the GDPR.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Rapid onboarding

AI produces industry overviews, explains terminology, value chains and typical KPIs and drafts key questions for the kick-off – as a starting point to be verified with reliable sources.

Synthesising interviews

Notes from stakeholder interviews are organised by theme, pain point and quote, patterns and contradictions are drawn out and the results prepared as a basis for hypotheses.

Hypotheses and issue trees

Problems are broken down with AI into mutually exclusive, collectively exhaustive sub-questions, hypotheses are formulated and the required analyses and data sources derived. This quickly yields a robust workplan for the team.

Storylines and slides

Analysis results become pyramid-structured storylines, action titles and slide drafts, which the team then sharpens and builds out in the house style. The core message stays at the centre of every slide.

Proposals and bids

Tender documents are analysed, requirements turned into checklists and proposal sections on approach, work packages and team profile written with a clear focus. The client's evaluation criteria are addressed directly.

Faster data analysis

Client data is cleaned, analysed and visualised with AI support, for example for benchmarks, cost analyses or process KPIs, with documented calculation steps. Sanity checks safeguard quality before client presentations.

Possible hands-on projects

Interview synthesis board

A small app where interview notes are uploaded, tagged by theme and displayed as an overview with quotes for each topic area.

Bid checklist

An internal tool that captures requirements from tenders, maps them to proposal sections and highlights open items before submission. Formal exclusion criteria are flagged separately.

Benchmark calculator

A simple web app that compares a client's KPIs with stored reference values and highlights deviations graphically. Sources and dates of reference values are documented transparently.

Prerequisites

Confident use of a web browser and standard office software is all you need. No programming knowledge is required. Experience in consulting projects or analytical project roles; no programming skills required.

Technical requirements

A laptop with an up-to-date browser, a Lovable account (a paid plan is recommended for intensive use) and free GitHub and Supabase accounts.

Data protection & compliance

Client information is usually covered by confidentiality agreements and may only be processed in AI environments cleared contractually and under data protection law. AI use should be agreed with the client, and personal interview data must be handled in line with the GDPR.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Mon, 23 November 2026 Online Request
  • Mon, 7 December 2026 Berlin Request
  • Tue, 15 December 2026 Online Request
  • Fri, 15 January 2027 Online Request
  • Tue, 26 January 2027 Stuttgart Request
  • Thu, 4 February 2027 Online Request

Frequently asked questions

Do I own the code Lovable generates?

Yes. The output is standard React and TypeScript code that you can push to your own repository via the GitHub sync. From there it can be developed, tested and deployed entirely independently of Lovable. In the course we show you how to set this up properly from day one so you avoid any lock-in.

Is Lovable suitable for production applications?

For prototypes, MVPs, internal tools and modest customer-facing apps, yes, provided you review security and the data model carefully. Supabase Row Level Security, secrets handling and the maintainability of a growing codebase all need attention. The course covers exactly which checks make sense before you go live.

How does Lovable differ from Cursor or Claude Code?

Lovable is a browser-based app builder with a fixed stack, built-in hosting and Supabase integration, which makes it ideal for getting started quickly. Cursor and Claude Code work inside any existing codebase and technology. Many teams combine them: start in Lovable, then continue in the editor via GitHub.

Can I use client data in AI tools?

Only if the contract, NDA and your firm's policies permit it and the tool is covered contractually. It is often sensible to agree AI use with the client. The course shows how to work with anonymised data and set clear rules for project teams.

Will AI make consultants redundant?

Grunt work such as desk research or first slide drafts becomes cheaper. Judgement, industry experience, facilitation and implementation support remain in demand. Firms that use AI well deliver faster and can invest more time in real impact for clients. Value shifts towards advice quality and outcomes.

How much does “Lovable for Consultants” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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