Let’s jump on the bandwagon about DeepSeek R1 and how it’s got the legal tech world buzzing. I know what you’re thinking, “Another AI model hits the saturated market? Great…” But hold on a second, this one might be different. It’s an open-source large language model (LLM) from DeepSeek, a Chinese AI research company, and it’s got some serious potential to shake things up, especially when we’re talking about running it securely inside our own law firms and corporate legal departments.

We’re not talking about some cloud-based, black box solution here. One of the big selling points of DeepSeek R1 is its ability to be deployed locally. That means we get to keep our sensitive client data within our own network. This is huge for those of us who are constantly worried about data security and compliance. I know many of you, like me, have some interesting discussions and use cases by with cloud vendors, so the idea of doing this ourselves may be incredibly attractive.

So, What Can DeepSeek R1 Actually Do For Us?
This isn’t just some fancy toy. DeepSeek R1 has some genuine use cases that could change the way we do things. Let’s break it down:

  • Contract Analysis and Review: Think about the hours we spend poring over contracts. DeepSeek R1 can analyze these documents, extract key clauses, identify potential risks, and even suggest improvements to language and structure. This isn’t just about saving time, it’s about making sure we are negotiating better deals and complying with all the relevant regulations.
  • Predictive Policing of Internal Communications: This one might raise some eyebrows, but DeepSeek R1 can analyze internal communications, such as emails and chat logs, to identify potential compliance risks and prevent data breaches. It can help ensure that our firm adheres to ethical guidelines and legal standards, which is crucial. Keeping this analysis within our own network is a significant win.
  • Litigation Analysis and Strategy: AI can analyze litigation data, predict case outcomes, and provide insights into judges, opposing counsel, and legal strategies. This can help us make better decisions, develop stronger arguments, and get better outcomes for our clients. Tools like Lex Machina and LegalMation are already being used to enhance litigation strategy and automate document preparation, so why not DeepSeek R1?
  • Document Automation: From pleadings to contracts to discovery requests, DeepSeek R1 can automate the drafting of these standardized legal documents, saving time, reducing errors, and ensuring consistency.
  • E-Discovery: AI can assist in e-discovery by analyzing large volumes of electronically stored information (ESI) to identify relevant documents, categorize them, and even redact sensitive information. This can significantly reduce the time and cost associated with e-discovery.
  • Improved Client Service: AI-powered chatbots and virtual assistants can provide instant responses to common client queries, schedule appointments, and even offer basic legal guidance, improving client satisfaction and freeing up lawyers for more complex matters.
  • On-Demand Document Summarization: This one is my personal favorite. Let’s face it, we’re drowning in documents. DeepSeek R1 can provide on-demand summarization of various legal documents, including email chains, contracts, case law, legal research articles, and depositions. We could set up an email-based system where lawyers send documents to a dedicated email address and receive summaries in their inbox, or, create an internal web portal with more features. Make it super easy on the users to get benefits from a secure AI model without having to become a prompt expert.

What About the Tech?
You’re probably wondering about the tech stack needed for all this. We’re talking about running DeepSeek R1 locally, on our own systems. That means we need some beefy servers with powerful CPUs and plenty of RAM, as well as multiple high-end GPUs. You’ll also need Docker with NVIDIA support, Ollama (to simplify running the model locally), and monitoring tools like Prometheus and Grafana to keep an eye on everything. And of course, robust security measures are a must. You might need an Azure VPN Gateway to connect your local network to Azure cloud resources, and Azure Blob Storage for your documents and data. Quite frankly, this part is way outside my expertise, so I actually asked one of the AI models to give me a list of hardware/software options that would be necessary to run it locally. (It pointed me here.)

Is it worth the effort?
I’m not saying this is going to be easy. It will require skilled IT personnel with expertise in AI, Docker, and cloud technologies. There are also potential risks and unforeseen consequences to consider. We have to keep an eye on accuracy and bias, as well as ethical considerations. But, the potential benefits of this thing, like reduced costs, increased efficiency, and better accuracy, can’t be ignored.

The Open-Source Advantage
The open-source nature of DeepSeek R1 is also a big deal. It means we have more transparency, the potential for community contributions, and customization options. That’s important because we are moving away from relying on closed, proprietary systems. Plus, DeepSeek R1 is rumored to be more cost-effective than some of its US counterparts. That’s always a nice bonus.

The Elephant in the Room
Of course, we can’t ignore that DeepSeek R1 has Chinese origins, and that might raise some concerns for some of us. We’ve seen the Tik Tok legal and political battles. There are worries about potential biases, censorship mechanisms, and the risk of misuse. The US Navy even banned DeepSeek AI over national security and ethical concerns. DeepSeek has also faced malicious attacks, and there are investigations into whether a DeepSeek-linked group improperly obtained OpenAI data. This requires us to be cautious and diligent.

Final Thoughts
DeepSeek R1 is a fascinating development in the legal tech world. It is not a magic bullet, and you need to be aware of the potential risks. However, the potential for secure, on-premises AI in law firms and corporate legal departments is real. It’s up to us, the legal tech professionals, to figure out how to make the most of it.

What do you think? Is DeepSeek R1 a game-changer, or just another flash in the pan?

This week, we are joined by Atena Reyhani, Chief Product Officer at ContractPodAi, for an engaging discussion on the intersection of AI innovation and the legal industry. Atena brings her deep expertise in AI-driven product development and shares insights into the trends shaping legal technology and how ContractPodAI is at the forefront of this transformation.

The conversation kicks off with a focus on the prevalence of conversational user interfaces (CUIs) in modern legal tech tools. Atena explains that CUIs, inspired by platforms like ChatGPT, are intuitive and reduce the cognitive load for users, making adoption easier. “Conversational user experience is now one of the ways of interacting with super intelligence,” she notes, highlighting how this design helps bridge the gap between human communication and AI capabilities. Atena also predicts a future shift towards deeper human-AI collaboration, moving beyond simple interactions to robust tools that integrate seamlessly with user workflows.

When asked about the challenge of brand differentiation in a landscape where many tools appear similar, Atena emphasizes the importance of moving from basic chatbots to comprehensive, end-to-end solutions. She points to the rise of agentic AI, where multiple AI agents work together to provide dynamic, actionable insights. According to Atena, “AI can now analyze information, outsource tasks, and dynamically engage multiple AI agents to perform end-to-end operations,” paving the way for truly intelligent legal platforms.

Atena delves into how ContractPodAi leverages AI to address real-world challenges in legal operations. With its Lea AI solution, the company has expanded beyond contract lifecycle management (CLM) to broader enterprise applications such as compliance and obligation management. Atena reveals an exciting new initiative, the Lea Marketplace, which she describes as “a one-stop shop for enterprise legal GenAI,” likening it to the Salesforce or Microsoft Marketplace. This platform will enable partners and subject matter experts to accelerate innovation through collaborative, industry-specific solutions.

Reflecting on her career in AI and her recognition as an award-winning innovator, Atena speaks passionately about the tangible impact of AI on businesses and individuals. She also underscores the importance of diversity in technology development, stating, “Women bring a diverse perspective that is crucial for innovation.” Atena encourages more women to step into leadership roles and shape the future of AI and legal tech.

The episode concludes with Atena’s predictions for the legal tech industry. She identifies key challenges, including aligning AI capabilities with organizational needs and ensuring effective user adoption. “It’s one thing to have the technology and another to use it to its full potential,” she observes, stressing the importance of strategic deployment, training, and change management. Atena’s optimistic vision underscores the vast opportunities for AI to revolutionize legal operations.

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Blue Sky: ⁠⁠@glambertpod⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

Continue Reading The Evolution of AI in Legal Tech: A Conversation with ContractPodAi’s Atena Reyhani

LinkedIn, the platform where professional networking and self-promotion collide, now finds itself in the crosshairs of a major class action lawsuit. The allegation? That LinkedIn has been secretly using Premium users’ private InMail messages to feed AI training models without their knowledge or consent. For a platform that markets itself as a bastion of professional trust, this is a serious breach of both expectations and contracts. As a side-note, while I am not a premium LinkedIn user, I frequent LinkedIn because it’s one of the few (mostly) apolitical social media platforms out there. And while many of us may scoff at the idea that LinkedIn would train AI models on the public content we post, the collecting of InMail content is quite disturbing, if proven true.

[Case: De La Torre v LinkedIn Corp, U.S. District Court, Northern District of California, No. 25-00709]

The lawsuit, filed in California federal court, claims that LinkedIn violated not only the privacy of its users but also their trust. Premium subscribers, who shell out extra for the promise of enhanced privacy protections, allegedly had their sensitive communications, think job negotiations, intellectual property discussions, and salary talks, used to train generative AI models. To make matters worse, LinkedIn reportedly attempted to sweep this under the rug by quietly updating its privacy policy after being called out.

Consider the type of content often found in LinkedIn InMail messages. These aren’t just generic notes asking to “connect” or “grab coffee sometime.” They often include deeply personal and highly sensitive information, such as salary negotiations, business strategies, discussions of intellectual property, and even private details about career moves or startup funding. The exposure of such content through unauthorized AI training would be more than just a privacy violation; it could have life-altering consequences for the individuals involved, from damaged professional reputations to lost business opportunities.

Note: Monthly InMail Cost for Premium Users

Here’s the kicker: the lawsuit doesn’t just allege privacy violations. It claims breaches of federal laws, contractual promises, and California’s Unfair Competition Law. The plaintiff seeks damages, injunctive relief, and even “algorithmic disgorgement”, essentially demanding that LinkedIn delete AI models trained on the improperly used data. Is that even possible??

And then there’s the Microsoft connection. LinkedIn’s parent company stands accused of possibly integrating this data into its broader ecosystem, raising questions about where this sensitive information could resurface. Could confidential LinkedIn messages one day power a Microsoft Teams suggestion or autocomplete a Word document? The implications are staggering.

LinkedIn, for its part, denies the allegations, calling them “false claims with no merit.” But as the details of this case unfold, the broader tech industry faces a critical moment. At a time when generative AI is reshaping how companies innovate, this case underscores the urgent need for transparency and consent in data usage.

For legal professionals, privacy advocates, and anyone who’s ever sent an InMail, this story is more than just a cautionary tale—it’s a wake-up call. Many of us joked a few weeks ago when we thought they were only scraping publically available post, where most AI results would start with “I am excited to announce I have joined ____ company this week…”. But this is a much more serious allegation. If LinkedIn, a platform built on professional integrity, can allegedly fumble its privacy commitments, what does that say about the wider industry?

This week we welcome Bobby Puglia, Chief Product Officer at Bloomberg Industry Group, to discuss Bloomberg Law’s latest generative AI-powered tools: Bloomberg Law Answers and Bloomberg Law AI Assistant. Bobby provides an insightful look into how these tools are designed to revolutionize legal research by making it faster, more intuitive, and seamlessly integrated into users’ workflows. The conversation begins with a discussion about the challenges of capturing the attention of legal professionals and the strategies that can bridge the gap between innovation and adoption.

Addressing “Tool Fatigue” and Driving Innovation Adoption

Bobby delves into the strategies behind overcoming “tool fatigue,” a common challenge in the legal industry. He highlights the importance of understanding specific user pain points and delivering targeted solutions. Marlene shares how peer advocates within law firms can champion the adoption of new tools, while Greg emphasizes the need for tailoring communication to align with the unique needs of different legal professionals. These insights reveal Bloomberg’s thoughtful approach to encouraging the adoption of its cutting-edge tools.

Inside Bloomberg Law Answers and AI Assistant

Bobby explains how Bloomberg Law Answers uses generative AI to provide concise, transparent answers directly in search results. With citations and detailed attributions, the tool seamlessly integrates into existing workflows. Meanwhile, the AI Assistant offers a groundbreaking way to interact with legal documents—allowing users to summarize, interrogate, and ask specific questions confined to the document’s “four corners.” These tools are designed to save time and enhance productivity for attorneys and legal researchers.

User-Centric Design and Quality Assurance

The discussion highlights Bloomberg’s user-focused development process, including its Innovation Studio, which uses pre-beta testing to refine tools based on user feedback. Bobby outlines how this iterative approach improves content sourcing, interface design, and overall functionality. Robust benchmarking, guardrails, and human-in-the-loop testing ensure that Bloomberg’s AI tools maintain the highest standards of accuracy and reliability.

The Future of AI in Legal Workflows

Looking ahead, Bobby shares his vision for generative AI’s role in reshaping the legal industry. He predicts a future of integrated, customizable workflows that reduce time spent on routine tasks, allowing legal professionals to focus on high-value work. The conversation also explores how Bloomberg plans to expand its AI Assistant to tackle broader research tasks, streamline navigation, and enable seamless integration with platforms like Microsoft.

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Blue Sky: ⁠⁠@glambertpod⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

TRANSCRIPT

Continue Reading From Workflow to Innovation: Bloomberg Law Answers and AI Assistant with Bobby Puglia

This week, we kick off the new year with ⁠Patrick Ip⁠, co-founder and CEO of ⁠Theo AI⁠. Patrick joins the podcast to discuss his journey from Google to entrepreneurship and how his company is leveraging AI to transform legal workflows. As the legal industry begins to embrace AI, Patrick shares his unique perspective on opportunities, challenges, and the ethical considerations surrounding these groundbreaking technologies.

The conversation begins with a fascinating discussion about a recent pro se lawsuit where AI tools like OpenAI’s GPT-4 and others played a pivotal role in drafting a complex complaint. Patrick and the hosts delve into the implications of this case for legal professionals, highlighting the advancements in AI’s capabilities and the need for caution when non-experts wield these tools. The discussion provides a critical lens on the ethics, risks, and reliability of integrating AI into the legal process.

Patrick shares the inspiring backstory of Theo AI, rooted in his rich professional journey, which spans work at the United Nations, launching startups, and being part of a Nobel Peace Prize-nominated project at Google. At Theo AI, Patrick has combined his entrepreneurial spirit with his legal expertise to develop tools that make legal predictions more accessible and reliable. From managing client expectations to transforming litigation funding, Theo AI’s innovative use of synthetic and firm-level data is driving efficiencies and fostering better decision-making across the legal landscape.

The discussion also ventures into the practical applications of Theo AI, particularly for litigation funders and law firms. Patrick explains how Theo AI compresses case review time from weeks to mere minutes, offering predictive insights that help legal professionals assess case viability, manage risk, and optimize workflows. He emphasizes the role of trust and transparency in AI development, ensuring the technology is both robust and aligned with ethical practices.

As the episode concludes, Patrick reflects on the future of AI in the legal industry, forecasting that the most transformative advancements will seamlessly integrate into existing tools like Microsoft Word and Outlook. He also shares his broader philosophy of balancing work with personal passions, drawing inspiration from his experiences as an entrepreneur, coffee aficionado, and triathlete. This engaging conversation is a must-listen for anyone interested in the evolving role of AI in legal technology and beyond.

Links:

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Blue Sky: ⁠⁠@glambertpod⁠⁠ ⁠⁠@marlgeb⁠⁠
⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

TRANSCRIPT

Continue Reading Patrick Ip: How Theo AI is Redefining Legal Predictions

This week, Greg Lambert sits down with Tom Dunlop, CEO and founder of Summize, and Laura Proctor, Chief Marketing Officer, to explore the evolution and impact of Summize in the contract lifecycle management (CLM) space. From its innovative beginnings to its strategic positioning in a competitive market, this discussion unveils the strategies, challenges, and future trends shaping legal technology.

Tom Dunlop shares the frustrations that sparked the idea for Summize, recounting his days as an in-house lawyer overwhelmed by the manual review of locked PDF contracts during due diligence. “It was painstaking,” Tom recalls, “I knew there had to be a better way.” Teaming up with a software engineer, he sought to create a tool that could generate instant, usable summaries of contracts. Thus, Summize was born, tackling not only legal pain points but also bridging communication gaps between legal teams and broader business units.

Laura Proctor highlights Summize’s unique approach to embedding its tools within widely used platforms like Microsoft Word, Slack, and Teams. This strategy ensures lawyers and business users can collaborate seamlessly without leaving their existing workflows. “Why ask lawyers to leave Word when they already love working there?” Laura explains, emphasizing Summize’s commitment to user-centric design. This integration not only enhances efficiency but also shifts the perception of legal teams from bottlenecks to enablers.

Central to Summize’s implementation is their “Hero Framework,” a three-step process designed to reduce legal bottlenecks, enhance efficiency, and track progress with actionable analytics. Tom explains, “We focus on reducing low-value, high-volume tasks, enabling self-service for the business, and then optimizing legal workflows.” This framework has even led to unexpected benefits, such as elevating the “personal brand” of legal teams within organizations.

Laura delves into the differences between US and UK markets, noting that US buyers often have prior experience with CLM tools, while UK customers may be making their first purchase. This distinction shapes Summize’s marketing and implementation strategies, with a focus on ensuring rapid time-to-value and addressing previous pain points. “In the US, it’s about reassurance and quick wins,” she explains, highlighting the importance of tailoring approaches to meet varying customer needs.

Looking ahead, Tom envisions a future where AI moves beyond single tasks to orchestrate complex workflows, potentially disrupting the billable hour model and democratizing access to legal knowledge. “If we can monetize legal knowledge rather than time, we could 10x the market,” he predicts. Laura adds that Summize will continue leaning into creativity and differentiation in an increasingly crowded market, ensuring their solutions remain bold and memorable.

This episode is a deep dive into the innovative strategies that are redefining CLM and the broader legal tech landscape. From the practical application of AI to enhancing legal collaboration, Summize offers a glimpse into the transformative potential of technology in the legal world.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠

Blue Sky: @glambertpod @marlgeb
⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠

TRANSCRIPT

Continue Reading Summarizing Success with Summize’s Tom Dunlop and Laura Proctor

In this special year-end episode of The Geek in Review, Greg Lambert takes listeners on a unique journey through the past year’s 50 episodes, all with the help of Google’s NotebookLM audio overview tool. Inspired by Josh Kubicki of the Brainyiacs Newsletter, Greg experiments with this cutting-edge AI tool to synthesize and discuss the key themes, guests, and topics covered throughout 2024. The result is an innovative meta-conversation between Greg and AI-generated co-hosts, offering insights into the future of law and legal technology.

Key Themes from 2024:
The episodes this year highlighted critical shifts in the legal landscape, from the integration of generative AI to the rise of client-centric practices. Technology’s impact on efficiency, mental health, and the evolving role of lawyers emerged as recurrent topics. Discussions also included the push for ethical AI adoption, flat-fee models, and the importance of balancing professional and personal lives, particularly in the “Love and Legal Tech” series. NotebookLM reflected on these trends, offering a synthesized perspective on how the legal industry is adapting to innovation.

Generative AI and Legal Tech:
Generative AI dominated discussions, with guests exploring its transformative potential and the skills needed to leverage it effectively. While some feared job displacement, most viewed AI as an augmentation tool, enabling lawyers to focus on higher-value tasks. Leaders like Dr. Megan Ma and Conrad Everhard shared groundbreaking projects, such as an M&A negotiation simulator, exemplifying AI’s capabilities. The conversation underscored the necessity for prompt engineering skills and ethical considerations in AI deployment.

Data Management, Security, and Transparency:
The importance of robust data management and security was a consistent theme, with experts like Kelly Griswold emphasizing it as a foundational business function. Conversations also explored “garbage in, garbage out” scenarios, the need for explainable AI, and maintaining client trust through transparency. These discussions highlighted how firms must prioritize governance to ensure responsible and effective AI use.

Collaboration, Social Impact, and Access to Justice:
The legal tech community’s collaborative spirit shone through in initiatives like Baker Donelson’s Legal Design Lab and Tom Martin’s LawDroid, which aim to make legal services more accessible. Guests celebrated the social impact of innovative tools designed to reduce barriers to justice and foster inclusivity. These efforts reflect a broader commitment to using technology to address systemic inequities in the legal system.

Looking Ahead:
Wrapping up the year, Greg revisits the podcast’s hallmark “Crystal Ball” question, noting common predictions for the next two to five years. From AI’s continued evolution to shifts in pricing models and the rise of emotional intelligence in leadership, the future of law promises to be dynamic. This episode not only recaps a transformative year but also sets the stage for the challenges and opportunities ahead.

Tune in to this engaging recap as Greg Lambert merges legal innovation with AI technology to reflect on an extraordinary year for The Geek in Review. Happy Holidays and Happy New Year!

 

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Blue Sky: @glambertpod @marlgeb
⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠

TRANSCRIPT

Continue Reading 50 Episodes of Legal Innovation and a Chat with Google NotebookLM

In this year-end episode of The Geek in Review, hosts Marlene Gebauer and Greg Lambert are joined by legal tech experts Niki Black, Principal Legal Insight Strategist at AffiniPay, and Sarah Glassmeyer, Director of Data Curation at Legal Technology Hub, to recap the top stories of 2024. From the evolution of generative AI in legal tech to groundbreaking acquisitions, the conversation delves into the successes and challenges that shaped the year in the legal industry.

The discussion kicks off with a look at AI’s growing role in legal research and practice management. Greg recalls the controversial Stanford report that questioned the reliability of AI tools marketed as hallucination-free. The guests explore the importance of unbiased evaluations, the complexity of defining legal research, and the rapid pace of AI development that often outpaces regulatory and academic studies. Sarah highlights the need for peer-reviewed analysis to guide the effective use of these tools, while Niki emphasizes the user-friendly interfaces that generative AI brings to legal software.

Marlene shifts the conversation toward the challenges of integrating AI into law firms’ existing frameworks. The hosts and guests discuss the hesitancy of document management systems to adopt generative AI due to trust and security concerns. Niki and Sarah examine how firms are adapting to AI by organizing data more effectively and addressing client expectations. They also reflect on the potential of AI to bridge access-to-justice gaps, with tools that empower self-represented litigants and underserved communities.

The episode takes a closer look at notable mergers and acquisitions in 2024, such as Bloomberg’s acquisition of Dashboard Legal and Thomson Reuters’ purchase of SafeSign Technologies. Sarah raises concerns about the consolidation of the legal tech market, warning of diminished innovation and competition. Niki observes how cloud-based technologies have facilitated these integrations, making it easier for companies to offer comprehensive solutions that touch multiple aspects of legal practice.

Wrapping up, the group forecasts trends for 2025, including regulatory developments around AI and shifting priorities within law firms regarding tech adoption. While some predictions are cautious, like Sarah’s concern over the impact of external political factors on the tech workforce, others remain optimistic about the growing sophistication of legal tech. The episode concludes with reflections on how the industry can better prepare junior lawyers and law students to navigate an increasingly AI-driven landscape.

Join Marlene, Greg, Niki, and Sarah for this insightful look back at 2024 and an exciting glimpse into the year ahead. As always, we thank our listeners for tuning in, and we encourage you to share this episode with colleagues and connect with us on LinkedIn or Blue Sky!

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠

Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert
⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠

TRANSCRIPT

Continue Reading Sarah Glassmeyer and Niki Black on Legal Tech in 2024 – Highlights, Hiccups, and Hopes for 2025

This week on The Geek in Review, we sit down with Mark Doble, Co-Founder and CEO of Alexi, to discuss the state of AI-driven tools in the legal industry and how they are evolving to meet the needs of modern litigation practices. The conversation begins with a timely debate on measuring productivity in remote work settings. Doble, coming from a background in both law and software engineering, draws intriguing parallels between how legal services and software development measure output and efficiency.

Moving on to Alexi’s core offering, Doble delves into how the platform is currently being used by litigators. He explains that Alexi’s AI technology not only handles the tedious work of research and memo drafting but also provides opportunities for lawyers to explore creative, strategic approaches to cases. By automating routine tasks, Alexi empowers attorneys to focus on high-level legal reasoning and client goals, rather than sifting through mountains of documents.

A key aspect of the discussion centers on the ways in which AI tools, like Alexi, can transform junior associate work. Instead of solely performing rote research or document review, younger lawyers can now leverage these tools as teaching aids, accelerating their path to deeper legal understanding. Doble emphasizes that as automation becomes more sophisticated, the human lawyer’s role in guiding strategy and exercising judgment grows ever more critical.

Doble then addresses concerns around data security and confidentiality. He reiterates that while the underlying technology is evolving, core principles of security remain the same—encrypting data, controlling access, and ensuring that information is never inadvertently trained into the model’s outputs. He acknowledges emerging questions around work product and privilege but sees them as part of the natural adaptation cycle in adopting new technology.

Finally, looking ahead, Doble hints at a significant upcoming announcement from Alexi early next year. He suggests that this new release will push beyond current capabilities, bridging the gap between mere information retrieval and genuine “legal reasoning” support. While keeping details under wraps, Doble leaves listeners with a vision of AI as a true partner in litigation, promising exponential improvements that will redefine how attorneys practice law.

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TRANSCRIPT

Continue Reading Harnessing AI for Litigation: Mark Doble on Alexi’s Next Evolution

If you’ve been around the legal tech block a time or two, you’ve probably noticed a familiar pattern: We deploy technology to better understand and streamline the law as we know it. Legal analytics platforms sift through case law, AI-driven tools tackle contract review and due diligence, and blockchain-driven “smart contracts” hold the promise of self-executing agreements. But here’s a shift you might not have considered: It’s not just about making sense of the legal texts we already have. It’s about the laws themselves evolving to fit the tools we’re building.

Most of us think of legal technology as something that reacts to what Congress and courts produce. But what if tomorrow’s legislative drafters start structuring statutes—right from the get-go—in a code-like, machine-friendly manner? Over time, lawmakers might take their cues from how AI and automated reasoning systems process text. They could craft statutes with hyper-structured logic, standardized definitions, and reduced interpretive leeway. This would be more than just a stylistic choice: it could fundamentally reshape the balance of power among the branches of government and the role of agencies.

Courts and the Waning Ambiguity
Traditionally, the courts have a big job: interpret ambiguous statutes, reconcile conflicting provisions, and apply legal canons to unpack what Congress might have meant. If laws read more like neatly organized code—complete with precisely defined triggers, conditions, and outcomes—the courts’ interpretive heavy lifting could be significantly reduced. Judges would still have their constitutional role: to say what the law is and to apply it to specific facts. But if there’s less wiggle room, their work might look more like verifying whether the facts meet the clearly stated criteria, rather than engaging in lengthy interpretive gymnastics. While that doesn’t strip the courts of their authority, it does streamline their function. They become less about discovering meaning and more about confirming that a given scenario fits the predetermined parameters.

Agencies and the Loss of Regulatory Latitude
This shift could also ripple through the administrative state. Right now, agencies benefit from statutory ambiguity to interpret and fill in the gaps. They set rules and policy through their regulatory authority, often receiving deference from courts in recognition of their expertise. But if statutes are drafted with fewer interpretive grey areas—each statutory provision carefully defined and logically consistent—agencies may find themselves with less room to maneuver. The “we’ll fill in the details” model of agency rulemaking loses steam when Congress provides the details up front. Continue Reading When Law and Legal Tech Start Writing Each Other’s Code