Abdi Shayesteh and Jeanine Conley Daves on AI, Deliberate Practice, and the Future of Legal Training

Why It Matters

AI‑powered deliberate practice bridges the training gap, boosting associate effectiveness while giving firms data‑driven insight into skill development, a critical edge in a competitive legal market.

Key Takeaways

• European law firms seek AI maturity benchmarks versus U.S. peers.
• AltClaro’s “Depo Sim” uses AI to mimic hostile witnesses.
• Deliberate practice, not automation, is the core promise of legal AI.
• Associates gain real‑time feedback, closing law‑school to courtroom gap.
• Early adopters report higher confidence and targeted training efficiency.

Summary

The podcast episode spotlights two parallel developments reshaping legal practice: a new European survey measuring AI adoption across law firms, and AltClaro’s AI‑driven deposition simulator that brings deliberate practice to associates. Nikki Shaver explains how the survey, conducted with Lexo, will benchmark European firms against U.S. counterparts, revealing divergent tool usage and maturity levels. Meanwhile, CEOs Abdi Shayesteh and trial lawyer Janine Connley Daves discuss AltClaro’s evolution from a written‑work feedback platform to a full‑scale “flight simulator” for depositions, leveraging structured AI rubrics to deliver instant, objective performance scores.

Key insights include the shift from passive CLE hours to active, feedback‑rich training, the importance of assignment diversity for skill growth, and the tangible benefits observed during a pilot with six firms that logged 160 hours of testing. Participants praised the realism of AI‑generated hostile witnesses, opposing counsel, and court reporters, noting that the tool helps them rehearse on‑the‑fly adjustments and refine questioning strategies. The platform’s success earned an ALM Legal Week award and rapid adoption by over 100 AmLaw 200 firms.

Notable quotes illustrate the philosophy: Shayesteh likens the model to pilot training—“you put in hours, get feedback, then you fly”—while Connley emphasizes the value of realistic scenarios for building confidence. The discussion also references Anders Ericsson’s deliberate‑practice research, arguing that law firms must move beyond checklist CLE to iterative, data‑driven skill development.

Implications are clear: firms that integrate AI‑enabled simulators can accelerate associate competence, reduce time spent on low‑value drafting, and create measurable training pipelines. The European AI maturity survey will further pressure firms to adopt structured technology strategies, making AI‑enhanced deliberate practice a competitive differentiator in talent development and client service.

Original Description

This week on The Geek in Review, we talk with Abdi Shayesteh, CEO of AltaClaro, and Jeanine Conley Daves, Littler’s New York office managing shareholder, about a different question in the legal AI conversation. Instead of asking whether AI will write the brief, summarize the contract, or replace the junior associate, they focus on whether AI might help lawyers learn how to practice law. Their recent work around AltaClaro’s DepoSim points toward a model of legal training built less on passive observation and more on structured repetition, feedback, and skill development.

Shayesteh traces the origin of AltaClaro back to his own early years at King & Spalding, where he benefited from proximity to a mentor willing to explain the work. That experience also showed him the unevenness of the old apprenticeship model. Access to assignments, feedback, and sponsorship often depended on luck, relationships, and office geography. For Shayesteh, the idea of a “flight simulator for lawyers” grew out of the realization that pilots, athletes, and musicians all practice in structured environments before performance, while lawyers too often learn in front of clients, courts, and opposing counsel.

DepoSim applies this flight simulator concept to one of litigation’s highest-pressure skills: taking and defending depositions. The platform gives attorneys a simulated witness, opposing counsel, court reporter, and feedback system, with options to vary the difficulty and personalities involved. Conley Daves explains why this kind of realism matters. In a real deposition, a lawyer might face an evasive witness, a hostile witness, an aggressive opposing counsel, or a combination of all three. The simulator lets lawyers practice those moments repeatedly, receive targeted feedback, and return to specific skills such as exhibit handling, follow-up questions, or managing objections.

The conversation also connects AI training to equity in professional development. Conley Daves notes that access to high-quality assignments and sponsorship has not always been distributed evenly across firms. A standardized, rubric-based feedback system gives more lawyers a chance to build core skills without waiting to be selected by the right partner or assigned to the right matter. Shayesteh adds that firms seeing the strongest results are not treating training as an after-hours side quest. They are creating protected time for deliberate practice, pairing AI feedback with human mentorship, and using simulation as a bridge rather than a substitute for coaching.

Looking ahead, Shayesteh and Conley Daves see simulation moving well beyond depositions. Oral argument, cross-examination, meet-and-confer sessions, negotiations, client interviews, and even Supreme Court preparation all fit within this training model. The larger shift is not automation for its own sake. It is the use of AI to help lawyers build judgment before the stakes are real. For law firms, that means better preparation, more consistent training, stronger associate development, and a clearer path toward delivering value to clients. For the profession, it suggests a future where competence is practiced deliberately, measured thoughtfully, and taught more fairly.

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[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]

⁠⁠⁠⁠⁠Email: [e-mail]

Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

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