See dates, price and enrol on Maven →
At a glance
| Format | Live, cohort-based, on Maven; four sessions of two hours, all recorded |
| Schedule | One two-hour session a day over four consecutive days; cohorts run regularly — current dates on Maven |
| Price | €200, covered by the Maven satisfaction guarantee; team discounts and reimbursement templates available |
| Rating | 4.8 out of 5 from 328 ratings |
| Participants so far | Lawyers from hundreds of firms and legal departments |
| Prerequisites | None. No coding, no software to install — nearly everything runs in the browser |
What the course is
AI Lab for Lawyers is a cohort-based course delivered live on Maven: four sessions of two hours each, eight hours in total, with every session recorded so you can catch up or re-watch. It is called a lab on purpose. You will spend most of the time building things with AI rather than listening to slides about it — although you also get more than 300 practical slides to keep.
Everything runs in the browser. There is no software to install and no code to write. Complete beginners who have only ever typed a question into ChatGPT are welcome; so are experienced users, because the material goes far beyond the “prompt engineering” tips that circulate on LinkedIn. The tools on screen include ChatGPT, Claude Cowork, Perplexity, Harvey and Legora.
Who it is for
- Innovative lawyers who want to use AI to win and serve clients — the business-development module alone has paid for the course for many participants.
- Curious lawyers who want AI in their skill set to work faster and better, without compromising quality or confidentiality.
- Forward-thinking lawyers who want to understand where the profession is heading and position themselves ahead of it.
Participants so far have come from hundreds of firms and legal departments, including Wolf Theiss, Norton Rose Fulbright, Paul Hastings, Pillsbury, Taylor Wessing, Withers, Simmons & Simmons, Charles Russell Speechlys, Cuatrecasas, Uría Menéndez, Arthur Cox, Lenz & Staehelin, Bär & Karrer, Arendt & Medernach, Kobre & Kim, Maples Group, Walkers, KPMG and Siemens. The course is rated 4.8 out of 5 by 328 participants.
What you will learn
The syllabus has six modules, each mixing a short explanation with live building.
| Module | What you will be able to do afterwards |
|---|---|
| AI fundamentals and prompting | Explain what an LLM does when it “answers” — tokens, context windows, training and inference, hallucinations, reasoning models, search, RAG and deep research — and write prompts that give sufficient context, define the task and outcome, assign roles, set constraints, specify output formats, provide examples, break work into stages and use self-critique. |
| Legal research, drafting and document analysis | Research legal questions from primary sources, legislation and case law across jurisdictions; verify citations; produce research memos; draft contract clauses, emails, memos and pleadings from client instructions in the right tone and style; run contract review and due diligence. |
| Working with files, data and multimodal AI | Analyse PDFs, extract information and tables, work with spreadsheets, create charts, analyse images and scans, transcribe and summarise meetings, turn voice or handwritten notes into structured work product, and create presentations. |
| Custom AI systems, agents and automation | Set up projects and workspaces, reusable instructions, prompt libraries and knowledge bases; build custom assistants on your firm’s own know-how; move from prompts to workflows to agents; connect email, calendars and databases with n8n, Make and Zapier, with human approval and sensible autonomy limits. |
| Vibe coding, business development and productivity | Build simple software without coding — calculators, questionnaires, document generators, client-intake apps and legal decision trees; produce client alerts and LinkedIn content; prepare for conferences and client meetings; research prospects, draft pitches and proposals, and repurpose your content. |
| Risks, regulation and the future of legal work | Handle professional secrecy, confidentiality, privilege and data protection; read provider terms and data-retention settings; distinguish consumer from enterprise AI; deal with hallucinations, disclosure, supervision, billing and AI policies; understand the EU AI Act and where automation is taking the billable hour, junior training and the AI-native firm. |
The course is deliberately about building with AI. Risk and regulation are covered in the final module and in passing elsewhere, but if you need an ethics CLE, pair the course with the ethics and regulation guides on this site.
What is included
- 4 live sessions × 2 hours, in a small international cohort
- Lifetime access to the recordings
- 300+ practical slides
- A community of peers from other firms
- Optional homework assignments
- Certificate of completion (useful for CLE/CPD records and for the EU AI Act’s AI-literacy obligation)
- The Maven satisfaction guarantee
Many participants have the course fee reimbursed by their firm; Maven provides an email template, receipts and the certificate for that purpose. Private cohorts for firms and legal departments, and group and student discounts, are available on request — email niklas.schmidt@wolftheiss.com or book a 15-minute introductory call.
Who teaches it
The course is taught by Dr. Niklas Schmidt, Partner at Wolf Theiss Attorneys-at-Law in Vienna, where he heads the firm-wide tax team. He is admitted as a lawyer and as a tax adviser, has invested thousands of hours in researching practical AI for legal work, has tried out hundreds of AI apps and runs an armada of AI agents that work for him every day. He has given around 450 presentations over 20 years, mostly at international conferences, and founded the WT Crypto Academy, attended by more than 1,000 lawyers who rated it 4.8 out of 5 on average. More about the author →
How this site relates to the course
The free guides on this site cover the same ground as the course, in writing. If you read them all, you will know what to do. The course exists because knowing and doing are different skills: in the sessions you actually run the workflows, get your prompts critiqued live, compare notes with other lawyers and leave with working templates.