How Lawyers Are Using Vibe Coding to Automate Contract Work
Something interesting is happening in legal departments right now.
Lawyers are building their own tools. Not by learning to code. Not by hiring developers. They are describing what they need to an AI, and the AI builds it.
It is called vibe coding, and it is changing how legal teams think about the gap between "I need a tool for this" and "I have a tool for this."
This article covers specific, real-world examples of what legal professionals are actually building. Not theory. Not hype. Just what is working right now.
The Pattern: Contracts Have Too Many Manual Steps
Before we look at examples, let us talk about why contract work is uniquely suited to vibe coding.
Contracts follow rules. They have structured data. They involve repetitive steps. They depend on deadlines and conditions.
That is exactly the kind of work that AI-generated code handles well.
The average B2B contract touches 5 to 8 people across 3 to 4 weeks. Most of that time is not negotiation or legal analysis. It is moving information between systems, chasing approvals, reformatting documents, and manually tracking status.
These are the tasks lawyers are automating. Not the judgment calls. The plumbing.
Example 1: Contract Intake That Actually Works
The problem: A mid-size company's legal team gets contract requests via email, Slack, and hallway conversations. Half the requests are missing critical information. The legal team spends hours just figuring out what is being asked.
What they built: A web form that collects the exact fields the legal team needs before any work starts. Counterparty name, contract type, deal value, desired terms, internal owner, and deadline.
The form routes requests to the right person based on contract type and value. High-value deals go to senior counsel. Standard NDAs go to a junior team member. Everything over a certain threshold triggers a notification to the general counsel.
How they built it: One legal ops manager spent two evenings in Cursor describing the workflow. The AI generated a form, a routing logic, and an email notification system. Total cost: $20/month for the tool.
The result: Request intake time dropped from 2 days (back-and-forth emails) to 15 minutes. Legal stopped being surprised by urgent requests that someone forgot to mention until the last day.
Example 2: Expiration and Renewal Tracker
The problem: Contract renewals kept sneaking up on people. The "spreadsheet of truth" was always slightly out of date. Auto-renewals would trigger for contracts the company wanted to renegotiate or terminate.
What they built: A script that reads through the company's contract repository, extracts key dates (start, end, auto-renewal triggers, notice periods), and sends weekly email digests.
The digest tells you which contracts expire in the next 30, 60, and 90 days. It flags which ones auto-renew (and when the opt-out deadline is). It highlights any contracts past their expiration date that are still active.
How they built it: An in-house lawyer described the logic to Claude, got a Python script, and set it up to run every Monday morning. Took one Saturday afternoon.
The result: Zero missed renewals in six months. Two auto-renewals caught and renegotiated that would have cost $180K combined.
This is a good example of where vibe coding fills a gap. A full CLM tool like Bind handles this natively with automated reminders and contract dashboards. But for teams not ready for a platform switch, a vibe-coded script is infinitely better than a neglected spreadsheet.
Example 3: Clause Library Search
The problem: An in-house team has years of negotiated contracts with carefully crafted clauses. When they need a specific clause (say, a data protection addendum for a UK counterparty), they dig through old contracts manually. Sometimes they find what they need. Sometimes they rewrite it from scratch.
What they built: A search tool that indexes every clause from their past contracts. You type "data protection UK" and get every data protection clause they have ever used, ranked by recency and contract type.
How they built it: A legal ops analyst used Replit to build a simple web interface. The AI wrote the indexing logic and search algorithm. The hardest part was not the code. It was converting their contracts from PDF to searchable text, which the AI also helped with.
The result: Finding the right clause went from 30 minutes of digging to 10 seconds of searching. New contracts started faster because the team could pull proven language instead of drafting from zero.
Example 4: Obligation Extraction
The problem: After signing a contract, someone needs to read through it and pull out all the obligations. Who needs to do what, by when. This usually happens in a rush, with key obligations buried in dense paragraphs.
What they built: A script that takes a signed contract (PDF or Word), reads through it, and outputs a structured list of obligations. Each entry includes: who is obligated, what they must do, the deadline, and the contract clause reference.
The output goes into a simple table that the project team can use as their compliance checklist.
How they built it: An in-house lawyer used ChatGPT to write the extraction logic, tested it on 10 past contracts to validate accuracy, and iteratively improved the prompts until the extraction was reliable for their standard contract types.
The result: Post-signature obligation mapping went from a 2-hour manual read-through to a 5-minute automated extraction plus a 15-minute human review. The human review is still necessary because AI misses nuance sometimes. But the heavy lifting is done.
Example 5: Contract Status Dashboard
The problem: Leadership asks "how many contracts are in negotiation right now?" and nobody can answer confidently without checking three different systems.
What they built: A dashboard that pulls contract status from their email (sent/received), their signing tool (pending/signed), and their file system (executed/filed). It shows a real-time view: how many contracts are in draft, in review, in negotiation, pending signature, and executed.
How they built it: This one was more complex. A legal ops lead spent about two weeks, iterating with Cursor. The email integration was the hardest part. But the result is a single page that answers the "where are we?" question instantly.
The result: Monthly reporting went from a painful all-hands data-gathering exercise to a live dashboard that updates itself.
What These Examples Have in Common
Notice a pattern in all five examples.
None of them replace legal judgment. Nobody vibe-coded a tool that decides whether to accept a redline or assesses litigation risk. The AI built tools that move information, track deadlines, search documents, and format data.
All of them solve "plumbing" problems. The legal thinking was never the bottleneck. The bottleneck was always the manual work around the legal thinking.
Most of them took days, not months. The longest project was two weeks. Most were done in a weekend. Compare that to a typical IT project request that takes 3 to 6 months just to get prioritized.
None of them are perfect. Every one of these tools has rough edges. The UI is not beautiful. The error handling is basic. But they work well enough to save real time, and they can be improved iteratively.
The Honest Limitations
We would not be doing our job if we did not talk about what does not work.
Complex multi-system integrations are hard. If you need to connect to your ERP, CRM, email, and signing tool simultaneously, vibe coding gets messy fast. This is where purpose-built platforms earn their keep.
Security is your responsibility. AI-generated code does not automatically follow security best practices. If your tool touches client data or confidential information, you need to be careful. At minimum, keep it internal and do not expose it to the internet.
Maintenance is real. A vibe-coded tool that nobody maintains becomes a liability. APIs change. Systems update. Data formats shift. If you build it, budget time to maintain it.
AI is not infallible at extraction. The obligation extraction example works well for standard contract types. Throw a heavily negotiated, 80-page enterprise agreement at it and accuracy drops. Always verify AI-extracted data against the source document.
For more on what works and what does not, see our honest assessment: Vibe Coding for Legal Ops: What Works, What Doesn't.
When to Vibe Code vs. When to Buy
This is the practical question every legal team should ask.
Vibe code when:
- The problem is unique to your organization
- The solution is simple (one input, one output, clear logic)
- You need it fast and the budget for a vendor solution is not there
- It is an internal tool with limited users
- You want to prototype before committing to a purchase
Buy a dedicated tool when:
- The workflow is complex with many stakeholders
- Security and compliance requirements are high
- You need reliability and uptime guarantees
- Multiple teams will use it daily
- The vendor has already solved the hard problems
Contract lifecycle management is a good example of the "buy" category. Drafting, negotiation, signing, and storage involve enough complexity, security requirements, and daily usage that a purpose-built platform makes more sense than building from scratch.
But the smaller tools around that platform? The custom intake forms, the specific reports, the niche automations? That is where vibe coding shines.
- Problem is unique to your organization
- Solution is simple with clear logic
- Budget for a vendor solution is not there
- Internal tool with limited users
- Prototyping before committing to a purchase
- Workflow is complex with many stakeholders
- Security and compliance requirements are high
- Reliability and uptime guarantees are needed
- Multiple teams will use it daily
- The vendor has already solved the hard problems
Getting Started
If these examples resonated, here is the path forward.
Start small. Pick one manual task that annoys you. Not the biggest problem. The most repetitive one.
Timebox it. Give yourself 4 hours. If you cannot get a working prototype in 4 hours, the problem might be too complex for vibe coding. That is useful information too.
Do not worry about perfection. A tool that works 80% of the time and saves you 2 hours per week is worth more than a perfect tool that never gets built.
For a practical step-by-step walkthrough, read How to Try Vibe Coding for Legal Work.
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