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L2· Law

Contract Lifecycle & Legal Ops

You learn to turn a team's contract positions into an AI review playbook, review marketplace and consumer terms against Indian law, and automate the tracking work, with a qualified person signing off every judgement.

Choose a planRead the syllabus
Who it is for
LLB students interested in commercial contracts, in-house legal teams and the legal operations work that keeps them running.
AI core
9 units · 20 h
This course
6 modules · 12 lessons · 3.2 h
Live projects
2, on Professional and Career
01Roles it prepares you for
  • Contract Analyst
  • Legal Ops Associate

The skills these roles ask for. Preparation, not a promise of a job.

02Tools you will use
  • Claude ProjectsFree tier
  • ChatGPT (free plan)Free tier
  • Google Docs (suggesting mode)Free tier
  • Google SheetsFree tier
  • n8n Community Edition (Saarthi-hosted)Saarthi sandboxVerified
  • SpotDraftCollege licenceVerified
  • AugustCollege licence
  • India CodeFree tier
  • Saarthi sandbox (synthetic contracts, policies and fact patterns)Saarthi sandbox

You never pay for a tool subscription. “Verified” means we checked the free access on the vendor’s own site this month. Tool names describe what you learn; no vendor endorses Launchpad.

03Syllabus

What you will learn, in order.

Lesson films are narrated with an AI voice, over visuals made with AI tools and checked by our team. Saarthi, the coach, is an AI. Mentors and reviewers are people.

Part 1 · The AI core, shared by every stream

00Set up your coach1 hLearn how the core works, write the learning-context document that tells every AI tool who you are, and set Saarthi up as a coach that makes you think instead of thinking for you.
  1. How this core works6 min
  2. Write your learning-context document8 min
  3. Seven roles for AI, and study modes7 min
01How LLMs work and fail2.5 hBuild a working mental model of a large language model: tokens, prediction, context windows and memory. Then learn its predictable failures (hallucination, sycophancy, stale knowledge, bad arithmetic) and reproduce them yourself.
  1. Tokens and next-word prediction7 min
  2. Context windows and memory7 min
  3. Hallucination, sycophancy and other failures8 min
  4. Lab: one prompt, three models, five failures8 min
02Description and context engineering3.5 hWrite briefs that get the right output the first time: role, task, context, examples and format. Then make them reusable with Claude and ChatGPT Projects, Gemini Gems, custom GPTs and NotebookLM, and learn to work with PDFs, spreadsheets and images.
  1. The brief: role, task, context, format8 min
  2. Examples and output formats7 min
  3. Projects in Claude and ChatGPT8 min
  4. Gems, custom GPTs and NotebookLM8 min
  5. Working with files: PDFs, spreadsheets, images8 min
03Verify everything2.5 hCheck AI output the way fact-checkers do: lateral reading, tracing citations and numbers to the original, using deep-research modes without trusting them blindly, and testing a prompt properly with a 10-case golden set.
  1. Lateral reading7 min
  2. Checking citations and numbers8 min
  3. Deep-research modes: use and limits7 min
  4. Your first eval: a 10-case golden set8 min
04Connectors and MCP2 hConnect AI to the places your work lives (Drive, Gmail, Sheets, business data) without writing code. Learn what an MCP server is, why a reviewed directory differs from unreviewed community servers, how to grant the least access that works, and how to keep browser extensions on a short leash.
  1. What connectors and MCP are8 min
  2. Trust, least privilege and the reviewed directory8 min
  3. Browser extensions and AI browsers7 min
  4. Lab: ask the seller-data MCP server, check every answer8 min
05Agents and automations3.5 hHand multi-step work to AI safely. Tell an agent from an automation, decide what to delegate, use browser and coding agents with care, and build an n8n workflow that uses AI with a human-approval step before anything leaves the system.
  1. Agents vs automations: what to delegate8 min
  2. Browser agents, safely7 min
  3. Automation basics with n8n and Zapier8 min
  4. Lab: build an automation with a human-approval step8 min
  5. Failure modes and your failure-mode note7 min
06AI for learning and careers1.5 hUse AI to learn faster without outsourcing the learning, write applications that still sound like you, and practise interviews out loud with Saarthi.
  1. Learning with AI, not instead of learning7 min
  2. Applications in your own voice7 min
  3. Mock interview with Saarthi8 min
07Diligence: law, ethics, integrity2.5 hThe rules that apply when you use AI in India: the DPDP Act 2023 and its 2025 Rules, academic integrity and disclosure, copyright (including where Indian law is still unsettled), and bias. You finish by writing your own AI-use policy.
  1. DPDP Act 2023: personal data and AI8 min
  2. Academic integrity and disclosure7 min
  3. Copyright and AI in India8 min
  4. Bias and fairness7 min
  5. Write your personal AI-use policy7 min
08Core capstone1 hPut all four Ds together on one anonymised marketplace settlement file: ask good questions, automate one step, verify every number against Saarthi's P&L engine, and defend your work live in five minutes.
  1. The capstone brief6 min
  2. Lab: ask, automate, verify8 min
  3. Prepare your 5-minute defence7 min

Part 2 · Contract Lifecycle & Legal Ops

01The contract lifecycle and where AI fits2 lessonsThe stages of a contract's life, the Contract Act basics every reviewer needs, and which tasks AI can safely take on.
  1. From request to renewal8 min
  2. Lab: map a small brand's contract portfolio20 min
02Review playbooks2 lessonsWrite positions as preferred, fallback and walk-away, turn them into an AI review prompt, and test it before anyone relies on it.
  1. Playbooks: your positions, written down8 min
  2. Lab: build and test an AI review playbook25 min
03Reviewing marketplace seller agreements2 lessonsRead the platform terms that govern a seller's business, from the seller's side, and map the risks clause by clause.
  1. What a seller signs up to8 min
  2. Lab: a seller-side risk map25 min
04Consumer-facing terms for D2C brands2 lessonsCheck a D2C brand's terms, returns and cancellation policies and checkout flows against the E-Commerce Rules, the 2026 amendment and the dark patterns guidelines.
  1. The E-Commerce Rules checklist8 min
  2. Lab: audit a D2C brand's terms and checkout25 min
05Obligations, renewals and legal-ops automation2 lessonsExtract obligations into a tracker, automate reminders with a human approval step, and measure the legal team's work.
  1. Obligations tracking and legal-ops metrics8 min
  2. Lab: obligations tracker and renewal reminders in n8n30 min
06Risk, confidentiality and ethics in contract work2 lessonsProtect contract data, assess AI vendors before using them, log AI use and know when to escalate to a lawyer.
  1. Using AI on contracts responsibly8 min
  2. Lab: vendor due diligence and an AI-use protocol20 min
04Live projects

Two briefs. Real-shaped work.

  1. Project 1

    Review playbook for seller–marketplace agreements

    Write a review playbook a small seller's legal adviser could use on marketplace seller agreements, and test it as an AI review set-up on a synthetic seller agreement and its linked policies. The playbook covers the clauses that most affect a seller's money and continuity, grounded in the Indian Contract Act, the E-Commerce Rules and the 2026 amendment. This is a training exercise, not legal advice.

    You hand in

    • Playbook covering at least ten clause types with preferred, fallback and walk-away positions, reasons, legal references and escalation owners
    • AI review set-up (project instructions and prompt) and its output on the synthetic agreement
    • Golden-set test results on three synthetic agreements with agreement rate and missed OUTSIDE clauses, before and after revision
    • Seller-side risk summary with practical actions and lawyer questions
    • AI-use log and a statement of which judgements require a qualified lawyer

    Data: Synthetic marketplace seller services agreements with linked policies and reference reviews from the Saarthi sandbox; statutes from India Code and the official gazette.. Reviewed by Saarthi against a published rubric, signed off by a mentor.

  2. Project 2

    D2C terms and returns policy against the E-Commerce Rules

    A synthetic D2C beauty brand asks you to check its terms of use, returns, refund and cancellation policies, grievance page and checkout flow against the Consumer Protection (E-Commerce) Rules 2020, the 2026 amendment in force from 1 January 2027 and the CCPA's dark patterns guidelines. Produce a referenced findings report and redrafted policies. This is a training exercise, not legal advice.

    You hand in

    • Checklist of 20–25 items, each referenced to a rule or guideline and marked as applying now or from 1 January 2027
    • Findings table for each policy and checkout screen with severity and proposed fix
    • Redrafted returns, refund and cancellation policy in plain language with tracked changes
    • A prioritised action plan for the brand with the 2027 deadline items flagged
    • Verification note listing every rule reference checked against the notified text

    Data: Synthetic D2C brand policies and eight checkout screenshots from the Saarthi sandbox; notified rules from the official gazette and the Department of Consumer Affairs.. Reviewed by Saarthi against a published rubric, signed off by a mentor.

05Practise out loud

In voice mock interviews and client calls, Saarthi plays: Farah, the fictional head of legal operations at a Bengaluru D2C beauty brand that sells on its own site and on marketplaces, hands you a contract and a two-day deadline. She asks which three clauses matter most, what you would accept to close the deal, and how you know the AI review missed nothing, and she pushes back whenever risk is described without a business consequence.

On plans that include mock interviews. You get written feedback after every call.

06Enrol

Pick a plan for Contract Lifecycle & Legal Ops.

One payment. The access deadline for each plan is shown before you pay.

  • Foundation

    01

    Learn the AI your field now runs on.

    ₹2,999

    One payment. GST included.

    • Access for 120 days (about 4 months) from the day you pay
    • No 1:1 mentor sessions
    • The common AI core and your domain course
    • Saarthi, your AI coach, any hour
    • Hands-on labs on free tools
    • Verifiable certificate
    Enrol on Foundation

  • Professional

    02

    Prove it on real work.

    ₹7,999

    One payment. GST included.

    • Access for 180 days (about 6 months) from the day you pay
    • One 1:1 session with a mentor
    • Everything in Foundation
    • Two live projects, reviewed by Saarthi and a mentor
    • Public portfolio page of verified work
    • Voice mock interviews
    • One 1:1 coaching session
    Enrol on Professional

  • Career

    03

    Work alongside our team.

    ₹14,999

    One payment. GST included.

    • Access for 240 days (about 8 months) from the day you pay
    • Four 1:1 sessions with a mentor
    • One 1:1 call with an industry expert
    • Everything in Professional
    • Four-week supervised practicum with the Saarthi team
    • Four 1:1 coaching sessions with your mentor
    • An exclusive 1:1 call with an industry expert in your field
    • CV and LinkedIn review
    • Priority mentor replies
    Enrol on Career

Your access period starts the day you pay and is shown before you pay. One exam pause per enrolment, for up to 15 days. When access ends the course locks, and your portfolio page and certificate stay live. Full refund within 7 days, pro-rata after that, and an automatic refund for any practicum, 1:1 mentor or expert session we do not deliver. Refund policy