The Lawyer of (Not the Future, but) Now (Part I)

Table of Contents

• An Expensive, Intentional Shift

• Beginner’s Mind

• Experience → Proficiency with AI Tooling

• Mapping the Workday’s Atomic Units; Systems Thinking

This is Part I of a multi-part article, with the additional part(s) to be published in the near future.

An Expensive, Intentional Shift

How does the lawyer of the future - which is to say, the future that has arrived right now - differentiate themselves?  AI, by taking some of the more rote tasks off of lawyers’ plates, has promised lawyers the time and opportunity to deploy their knowledge into more “strategic”, “high-value” and “judgement” based work.  But whatever those terms mean, that shift is not free, and it won’t come to all lawyers equally.  Instead, lawyers must actively re-assess their approaches and view every piece of their day critically if they are to change their practices to meet this moment and thrive going forward.

What are early ways for a lawyer to begin to make this shift?  Below are several humbly proposed starting points.

Beginner’s Mind 

This is a time unlike any other for lawyers in at least a decade-plus, but more probably unlike any time ever in the practice of law.  The law is a profession grounded in expertise and leverage that builds in one direction (up) during the typical lawyer’s life, based primarily on accumulated judgement, ever-increasing technical-proficiency, expanded teams and entrenched relationships.

And now, AI has thrown a wrench into this paradigm - it is an equalizer of a huge amount of knowledge and a virtual headcount multiplier.  While it for now leaves some portion of accumulated judgement and human relationships untouched, it heavily shifts what it means to be technically proficient as a lawyer (i.e., being a strong drafter is now a differentiated skill only at the margins and at the highest echelons of the profession) or to benefit from associate leverage (i.e., a large human team could actually be a liability if not properly skilled).  That is, the tried and true path to, and signifiers of, continued success throughout one’s legal career have changed dramatically.  

This means that, other than those few lawyers close enough to retirement (is that 24 months? 12 months?) for it to not impact them, it is critical for lawyers to quickly accept the permanence of these shifts and humbly begin to learn new ways of doing things.  There is simply too high a possibility of being passed by to not consciously try to keep up, which means admitting what you don’t know and then learning it, continuously.

Experience → Proficiency with AI Tooling

Practically, how does one act on this approach?  One starting point is to gain proficiency with workflow tooling like Claude Cowork, and even coding tools like Claude Code or OpenAI’s Codex.  Why?  There is a language, a cadence and a style of interaction that is unique to these tools.  Nothing in a lawyer’s professional life prior to the past 12-24 months can really serve as preparation for the experience of having a machine “understand” them, ask them clarifying questions, and then produce something nearly as well as they could have, in approximately 5% of the time.  

One also has to get used to the process of talking to the AI tool like a human, inasmuch as one is not executing search queries in Google but instead providing task-based instructions, while still having to be extremely prescriptive and not rely on the recipient’s ability to “read between the lines” or pick up on other subtle queues within instructions.

That is “phase one”, and most lawyers have worked through this initial “shock and awe” portion of gaining some level of AI exposure/fluency.  But there is much more to do.  The real benefit of exposure to this tooling comes when experience turns into some level of proficiency (combined with a deliberate re-examination of the lawyer’s existing work, as discussed in the next section), because this begins massive unlocks, such as:

• The product counsel who can build a working prototype imbued with their own lawyer-persona context in a way an engineer or product manager or designer may not be able to (allowing a product idea to begin to take shape before it gets mired in either over-architecting or in being so aggressive that the lawyer, brought in after the fact, will have to slash at it to make it “compliant”).

• The firm associate who can spin up three versions of an indemnification clause, with explanations as to their real-world impact based on worked (by AI) examples of how each version would play out in the context of a real-life third-party claim, before choosing which version to add to an agreement.

• The lawyer in a highly-regulated industry that can turn the law firm and SEC alerts they subscribe to into reminders for manual work to be done or triggers for agentic tasks.

This is where real AI-driven value begins to accrue, but it’s difficult to imagine any lawyer reaching these (still relatively low-hanging fruit) opportunities without first experimenting with LLMs, almost playfully and without an immediate payoff, and then also taking a microscope to their existing work.

Mapping the Workday’s Atomic Units; Systems Thinking

After this exposure/familiarity phase, how does the lawyer use that proverbial microscope to determine what to deploy AI against?  Not every entire workflow can be usefully (i.e., without creating more review work than time saved) end-to-end automated; not every workday can be run by agents.  Instead, the lawyer must be able to decompose the workday - to understand what he or she spends time on, what the constituent parts of a project, and then of the tasks within that project, are.   

Once that is mapped, low-hanging fruit can begin to be targeted for automation, on the theory that it is easier to automate a small, simple task than a large, complex one to start.  In pursuing this approach, the lawyer can accumulate quick wins, mini-validations of AI as part of their work.  And then those can be strung together, all while the lawyer is learning more about how to effectively deploy AI.  So there is a compounding effect as tasks are automated one by one, all while the human’s skill at deploying AI accumulates.

But this starts with breaking down the practice of law, business development, other non-billable work and internal administrative tasks into atomic units.  And this takes a discipline, a deliberate set-aside time during which the lawyer will not bill or work on urgent matters, and instead will actually think through and write down: 

• What tasks comprise each day (which inform which tasks exist as potential targets for automation). 

• How they are performed by a human (which informs the direction an AI agent must be given to perform the task).

• The knowledge repositories, databases and/or documents from which the tasks draw information (which inform the information sources to which the agent must be given access).

• Where in the tasks there is human judgement, idiosyncrasy, lack of structure/templatization and context-specificity (which informs where processes must have gates that pause the flow and seek human input). 

And there is a mindset predisposition that helps to drive this exercise, too: systems thinking, or the inclination to break down problems into component parts, then think through and process-engineer how to solve those problems by addressing those parts in a leveraged, intentional way that can also be deployed against analogous future situations.  Adopting this approach is part of injecting the lawyer’s legal expertise into solutions that actually scale for their team or firm.

This Part I has focused mostly on mindset shifting in light of, and learning to apply and set the table for success in deploying, AI.  Part II will continue the discussion of the lawyer of the future/now by thinking through what skills and organizational structures can be useful in the new environment that has evolved due in part to AI (that environment consisting of, among other things, multi-hyphenate professionals empowered to function cross-disciplinarily by AI, putting the right expertise into the system at the right junctures in a world where work patterns are changing, and an evolution in which human skills matter).

Ten Manor Advisory LLC is not affiliated with, controlled by or in control of any other business or entity.