Practical writing on AI, systems, and the real work of running a legal practice.
Intake is the first thing a potential client experiences with your firm. It is also frequently the most disorganized part of the practice. The conversation is good but the process around it is not.
High-stakes meetings require preparation. The kind of preparation that takes significant time: pulling together the relevant information, anticipating the questions, structuring the argument.
AI tools can produce serviceable contract language quickly. That is genuinely useful in specific situations and genuinely dangerous in others. The difference comes down to what type of contract work you are doing.
General AI legal research is not jurisdiction-aware by default. When you ask about a legal standard, you get the general rule. Whether that rule applies in your circuit, or has been modified by local precedent, is a different question.
Claude Projects let you define a persistent set of instructions and background context that shapes every conversation in that project. For legal professionals, this is one of the most practical AI configurations available.
Cloud AI tools send your input to a server somewhere. For most tasks that is fine. For work involving client information, that architecture creates an exposure that a lot of practices have not fully thought through.
Perplexity has become a useful part of the research workflow for some legal professionals. It also has specific failure modes that matter in a legal context. Both things are worth understanding before relying on it.
Non-attorney document preparers operate in one of the tightest compliance environments in the legal services space. The line between authorized document preparation and unauthorized practice of law is specific and consequential.
If your practice is going to use public AI tools for any work that touches client files, the redacted document method is the baseline minimum for managing the privacy risk.
Legal professionals are using public AI tools with client information in them. Some are doing it deliberately, after considering the risk. Many are doing it without thinking about it at all.
Most AI coverage in the legal space runs toward the theoretical. What is possible, what might be disrupted, what attorneys should be prepared for. This is about what is actually happening in small firm practices today.
There is a practical argument for AI in a lot of legal operations contexts. There is also a set of situations where reaching for an AI tool is a mistake, and being clear about the difference matters.
The question is not whether your firm should use AI. It is whether your firm has the underlying structure to make AI work. The answer to that question changes the conversation entirely.
An operational audit is not a checklist. It is not a survey you fill out before a consulting call. It is a structured process for finding the actual distance between how a firm runs and how it thinks it runs.
Most firms that come to us have already purchased the software. They bought the case management system, set up the client portal, maybe added a scheduling tool. The problems are still there.