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This episode of The Geek in Review podcast provides an in-depth look at how the AI assistant Paxton, created by Tanguy Chau and Mike Ulin, is transforming legal work. The hosts speak with the founders of Paxton to explore the pain points their technology aims to solve and how generative AI can enhance lawyers’ capabilities.

Tanguy and Mike discuss their backgrounds in AI, regulatory compliance, venture capital, and management consulting. This diverse experience informed their vision for Paxton as an AI assistant specifically built for legal and compliance professionals. They explain that Paxton is trained on millions of legal documents and regulations, allowing it to search this vast knowledge and retrieve highly relevant information rapidly. A key feature they highlight is Paxton’s accuracy in citing sources, with every sentence linked back to the original text.

One of the key features of Paxton is that it can automate repetitive, low-value legal work to make lawyers more efficient. Tanguy notes that tasks like reviewing thousands of sales contracts clause-by-clause or compiling 50-state surveys that once took weeks can now be done by Paxton in minutes. Mike discusses Paxton’s advanced document comparison capabilities that go beyond keyword matching to understand meaning and intent. This allows quick, substantive analysis of contracts, marketing materials, and more.

Exploring the future, Mike predicts that like software developers, lawyers who embrace AI will become much more productive. But higher-level strategic thinking will remain uniquely human. Tanguy shares an analogy of a human on a bicycle outpacing a condor, the most efficient animal. He believes combining human creativity with AI tools like Paxton will enable radically new levels of efficiency and capability.

Paxton.AI’s Tanguy and Mike make a compelling case that AI-powered tools such as Paxton will fundamentally transform legal work. By automating repetitive tasks, AI will free lawyers to focus on high-value, client-facing work. Overall, this episode provides great insights into how generative AI may soon become indispensable for legal professionals seeking to improve their productivity and capabilities.

As a special treat, we wrap up the interview with a demonstration of Paxton.AI’s capabilities. (YouTube only)

Links:

• ⁠Paxton AI (try the Beta for free)⁠

• ⁠Forbes Article: Unlocking The 10x Lawyer: How Generative AI Can Transform The Legal Landscape⁠

• ⁠Using Generative AI to analyze the 45 page Trump Indictment using Paxton AI⁠

• ⁠Unveiling Paxton AI’s Newest Features: Boolean Composer and Document Compare⁠

• ⁠Instantly Analyzing the Congressional UFO Hearing with Generative AI powered by Paxton AI⁠

Transcript:Continue Reading Paxton.AI’s Tanguy Chau & Michael Ulin: How AI Allows Legal Work to Soar to New Heights (TGIR Ep. 220)

On this episode of The Geek in Review podcast, hosts Marlene Gebauer and Greg Lambert interview Kris Martin, Executive Vice President at Harbor, to discuss innovation, AI, and the future of technology in the legal industry.

They open the show by talking about Harbor’s upcoming LINKS conference and its keynote focused on exploring human potential in the age of AI. Kris provides background on how the conference originated from an annual survey Harbor conducts to take the pulse of the legal community. He explains Harbor’s goal is to support legal organizations through insights, research, and events like the LINKS conference.

The discussion moves to AI trends and Jean O’Grady and Harbor’s strategic Start/Stop Survey results. The survey reveals 93% of firms are actively exploring AI tools, with top vendors being Casetext and Thomson Reuters. Kris emphasizes law librarians play a crucial role in evaluating new AI technologies and guiding procurement decisions as firms adopt these tools.

However, with tight budgets at most firms, Kris Martin points out it’s also important to audit usage data of existing resources. This helps inform negotiations with vendors to find cost savings on research contracts. He notes legal research tools will inevitably integrate more tightly into lawyers’ daily workflows in the future. To facilitate this, Kris introduces the concept of “citizen coders” – enabling lawyers to articulate their needs and processes in technology and code terms rather than just legal terms.

Shifting gears, Kris elaborates on Harbor’s recent rebranding from HBR Consulting, which brought six previously merged companies together under one unified brand and mission. He explains that true integration requires deep alignment across the merged organizations on culture, vision, and values. This allows Harbor to provide end-to-end solutions for legal organizations.

Looking to the future, Kris predicts legal research will become even more embedded into lawyer workflows over the next 2-5 years, rather than a separate step. He sees law libraries’ roles evolving as AI capabilities increasingly integrate into legal processes and tools. Rather than going to a separate platform for research, lawyers will access these AI-enhanced tools in their daily workflows.

Overall, the wide-ranging discussion provides insights into Harbor’s efforts to support the legal community through conferences, research, and integrating emerging technologies. Kris highlights the importance of law librarians evaluating and implementing new AI tools while also managing costs through audits. He leaves listeners with an optimistic vision for the future where legal research and lawyers’ needs are more tightly connected through technology.

Links:

Listen on mobile platforms:  ⁠Apple Podcasts⁠ |  ⁠Spotify⁠ | YouTube (NEW!)
Contact Us:
Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert⁠⁠⁠⁠⁠
Threads: @glambertpod or @gebauerm66
Voicemail: 713-487-7821
Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠
Transcript

Continue Reading LINKS, Citizen Coders & Auditing Shelfware: Insights from Harbor’s Kris Martin

This week we are joined by Brandon Wiebe, General Counsel and Head of Privacy at Transcend. Brandon discusses the company’s mission to develop privacy and AI solutions. He outlines the evolution from manual governance to technical solutions integrated into data systems. Transcend saw a need for more technical privacy and AI governance as data processing advanced across organizations.

Wiebe provides examples of AI governance challenges, such as engineering teams using GitHub Copilot and sales/marketing teams using tools like Jasper. He created a lightweight AI Code of Conduct at Transcend to give guidance on responsible AI adoption. He believes technical enforcement like cataloging AI systems will also be key.

On ESG governance changes, Wiebe sees parallels to privacy regulation evolving from voluntary principles to specific technical requirements. He expects AI governance will follow a similar path but much faster, requiring legal teams to become technical experts. Engaging early and lightweight in development is key.

Transcend’s new Pathfinder tool provides observability into AI systems to enable governance. It acts as an intermediary layer between internal tools and foundation models like OpenAI. Pathfinder aims to provide oversight and auditability into these AI systems.

Looking ahead, Wiebe believes GCs must develop deep expertise in AI technology, either themselves or by building internal teams. Understanding the technology will allow counsels to provide practical and discrete advice as adoption accelerates. Technical literacy will be critical.

Listen on mobile platforms:  ⁠Apple Podcasts⁠ |  ⁠Spotify⁠ | YouTube (NEW!)

Contact Us:

Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert⁠⁠⁠⁠⁠
Threads: @glambertpod or @gebauerm66
Voicemail: 713-487-7821
Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠

Transcript

Continue Reading Observing the Black Box: Transcend’s Brandon Wiebe’s Insights into Governing Emerging AI Systems (TGIR Ep. 218)

In this episode of The Geek in Review, hosts Greg Lambert and Marlene Gebauer interview three guests from UK law firm Travers Smith about their work on AI: Chief Technology Officer Oliver Bethell, Director of Legal Technology Shawn Curran, and AI Manager Sam Lansley. They discuss Travers Smith’s approach to testing and applying AI tools like generative models.

A key focus is finding ways to safely leverage AI while mitigating risks like copyright issues and hallucination. Travers Smith built an internal chatbot called YCNbot to experiment with generative AI through secure enterprise APIs. They are being cautious on the generative side but see more revolutionary impact from reasoning applications like analyzing documents.

Travers Smith has open sourced tools like YCNbot to spur responsible AI adoption. Collaboration with 273 Ventures helped build in multi-model support. The team is working on reducing dependence on manual prompting and increasing document analysis capabilities. They aim to be model-agnostic to hedge against reliance on a single vendor.

On model safety, Travers Smith emphasizes training data legitimacy, multi-model flexibility, and probing hallucination risks. They co-authored a paper on subtle errors in legal AI. Dedicated roles like prompt engineers are emerging to interface between law and technology. Travers Smith is exploring AI for tasks like contract review but not yet for work product.

When asked about the crystal ball for legal AI, the guests predicted the need for equitable distribution of benefits, growth in reasoning applications vs. generative ones, and movement toward more autonomous agents over manual prompting. Info providers may gain power over intermediaries applying their data.

This wide-ranging discussion provides an inside look at how one forward-thinking firm is advancing legal AI in a prudent and ethical manner. With an open source mindset, Travers Smith is exploring boundaries and sharing solutions to propel the responsible use of emerging technologies in law.

Links:

Listen on mobile platforms:  ⁠Apple Podcasts⁠ |  ⁠Spotify⁠ | YouTube (NEW!)

Contact Us:

Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert⁠⁠⁠⁠⁠
Threads: @glambertpod or @gebauerm66
Voicemail: 713-487-7821 Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠

⁠⁠⁠TranscriptContinue Reading Deploying Cutting-Edge Legal AI: Travers Smith’s Cautious, But Open-source Approach. (TGIR Ep. 216)

This is part 3 in a 3 part series.  Part 1 questions Goldman’s Sachs data showing that 44% of of legal tasks could be replaced by Generative AI.  In Part 2, we find some better data and estimate an upper limit of 23.5% of revenue that could be reduced by Generative AI. All of our assertions and assumptions will be discussed in further detail in a free LVN Webinar on August 15th.
The Big Idea:  We apply reductions in hours due to Generative AI to a few matters to determine Generative AI’s potential effect on profitability.
Key Points:
  • We establish a baseline sample matter and compare changes to that sample matter when Generative AI is applied
  • We explore how leverage is affected by Generative AI and how those changes may affect profitability in unexpected ways

Determining Generative AI’s effect on law firm profitability requires a bit more than a “back of the napkin” calculation with rough percentages based on keywords in time entries, as we did when roughly calculating the effect on revenue.

As Toby pointed out at the end of the last post, Generative AI is unlikely to hit all timekeepers equally.

We begin with this assertion.

Generative AI will disproportionately impact non-partner hours.

We are comfortable making this assertion for two reasons:

  1. Generative AI, in its current state, is most likely to replace or shorten the time to complete lower complexity and lesser specialized tasks that should be performed at the associate or paralegal level.
  2. Any time legal work hours are reduced, Partners tend to protect their own hours.

With that in mind, Toby began a profitability analysis, beginning with a baseline sample matter that does not factor in any use of Generative AI. We will use this baseline to compare against our AI adjusted matters.

Baseline M&A Sample Matter Data

Our baseline sample matter is loosely modeled on an M&A transaction and includes 5 timekeepers:

  • an Equity Partner
  • a 17th year service partner
  • 10th, 7th and 3rd year associates
TK Hours Rate Realization Revenue Expense Profit
EP 80 $1,000 88% $70,400 $15,200 $55,200
SP17 100 $895 88% $78,760 $48,500 $30,260
10yr 125 $735 88% $80,850 $48,750 $32,100
7yr 90 $660 88% $52,272 $32,400 $19,872
3yr 55 $595 88% $28,798 $18,150 $10,648

Estimated Annual Profit Per Equity Partner (PPEP) – $1,851 X 1400 hrs = $2,591,400

Leverage – 60% Non-Partner Hours

There are, of course, a number of assumptions in this baseline data that could greatly change from firm to firm, including the billable rates, the realization rate, and the expense for each timekeeper. However, we will keep this baseline data consistent across all of our examples in order to make a fair comparison. With different rates, realization, and expenses you will get different results. We strongly encourage every firm to perform a similar calculation for themselves.

Baseline Matter Analysis

The total hours billed are 450. The total revenue is $311k and the total profit in dollars is $163k.

Our model then translates the profit on this one matter into an estimated PPEP number for the firm. This is so we can determine profit margin impact separate from profit dollars.

In this baseline model, the PPEP number is ~$2.6m; meaning that if all work at this firm were staffed and billed like this one matter, the firm average PPEP would be about $2.6m.

Leverage

There’s an old adage in economic circles: “Workers Work. Owners Benefit.”
Continue Reading AI-Pocalypse: The Shocking Impact on Law Firm Profitability

by 3 Geeks (Ryan McClead, Greg Lambert, and Toby Brown)

This is part 2 in a 3 part series. The first part is here. Part 3 is here.

The Big Idea: We found a much better dataset, though still small, from which to extrapolate actual effects of Generative AI on the legal industry.

Key takeaways:

  • We got anonymized and summarized data for 10 corporate legal departments from LexisNexis CounselLink
  • The data showed that almost 40% of time entries, representing 47% of billings, could potentially use Generative AI.
  • We estimate that a realistic initial upper limit for Generative AI would be to reduce that work by half, or 20% of time entries and 23.5% of revenue

In the previous post, Ryan got tired of hearing the Goldman Sachs “44% of Legal is going away” stat being quoted uncritically and decided to actually look into the underlying data used in their report. Ryan’s exploration of the data is an interesting story in and of itself, but the bottom line is that the data is fuzzy at best, the sample size is laughable, and the breathlessly unquestioning reporting on Goldman’s study has been remarkably sloppy.

After writing up his findings, Ryan shared that post with Greg and Toby, and the question quickly arose, “can we find some actual, useful data to better understand the effect that Generative AI might actually have on law firms?” Gregreached out to Kris Satkunas from LexisNexis CounselLink, a recent interviewee on the Geek in Review, to see if CounselLink could share some anonymized benchmark data for us to analyze.

LexisNexis CounselLink Data

As a reminder the Goldman data was using survey questions about how important certain “work tasks” were for their jobs. Those tasks included things like “Getting Information”, “Identifying Objects, Actions, and Events”, and “Scheduling Work and Activities”. These are quite vague and wide open to interpretation.

In an attempt to find more useful data for our purposes, we asked Kris for the percentages of all time entries that included the keywords “Draft” or “Review” in the description. Our assumption is that those two terms will capture a large percentage of actual time entries in which lawyers are likely to use Generative AI. We fully recognize that this simple heuristic will not produce a clean data set from which to extrapolate definitive results, but as a first pass at some real data, we believe this gives us a nice estimate of tasks that could potentially be ripe for automation with Generative AI.
Continue Reading Generative AI Could Reduce Law Firm Revenue by 23.5%

This is the first in a 3-part blog post, it first appeared on The Sente Playbook.  The other 2 posts are co-authored by Toby Brown and Greg Lambert and will follow later this week. Apologies for the length of this post, but I was channeling my inner Casey Flaherty.
The Big Idea:  The data that Goldman used is insufficient to make the claims about Generative AI’s effect on legal that their report did.
Key Take-Aways:
  • Reporting about this report is sloppy
  • Reporting within this report is sloppy
  • The underlying data doesn’t tell us much meaningful
  • 3 Geeks attempts to find meaningful data
On March 26th, 2023 Goldman Sachs sent shockwaves through the legal industry by publishing a report claiming that 44% of “something” in the Legal Industry was going to be replaced by Generative AI.  I didn’t question that stat at the time, because it sounded about right to me.  I suspect that was true for most people who know the legal industry.  As I’ve heard this stat repeated by multiple AI purveyors actively scaring lawyers into buying their products or services, I eventually started to question its validity.
I started by looking into the press coverage of that 44% number and was immediately confused.  (All emphasis below added by me.)

Law.com  – March 29, 2023
Generative AI Could Automate Almost Half of All Legal Tasks, Goldman Sachs Estimates
“Goldman Sachs estimated that generative AI could automate 44% of legal tasks in the U.S. “

Observer – March 30, 2023
Two-Thirds of Jobs Are at Risk: Goldman Sachs A.I. Study
“The investment bank’s economists estimate that 46% of administrative positions, 44% of legal positions, and 37% of engineering jobs could be replaced by artificial intelligence.

NY Times – April 10, 2023
A.I. Is Coming for Lawyers, Again
“Another research report, by economists at Goldman Sachs, estimated that 44 percent of legal work could be automated.”

Okay, so which is it?  Generative AI is going to replace 44% of legal tasks, positions, or work?
Because those are 3 very different things; each of which would have extremely different impacts on the industry if they came to pass.  Lest you think I cherry-picked three outlying articles, go ahead and Google “AI Replace 44% Legal Goldman Sachs” and see what you get.  Those 3 articles are in my top 5 results.
My top result as of this writing is a news article from IBL News, writing last Tuesday that Goldman says,  “AI could automate 46% of tasks in administrative jobs, 44% of legal jobs, and 37% of architecture and engineering professions.”
We should probably just go back to what the Goldman Sachs report actually said and then we can chalk this up to lazy tech journalism.  Well, not so fast.  Because while the Goldman researchers clearly say “current work tasks” (see below) even that begins to fall apart once you dig into the underlying data.

What Goldman Sachs actually said in the report

Continue Reading 44% of Investment Bankers Think They Can Make Lots of Money Off of Attorney Insecurity (AI)

Tony Thai and Ashley Carlisle of HyperDraft, return to The Geek in Review podcast to provide an update on the state of generative AI in the legal industry. It has been 6 months since their last appearance, when the AI Hype Cycle was on the rise. We wanted to get them back on the show to see where we are on that hype cycle at the moment.

While hype around tools like ChatGPT has started to level off, Tony and Ashley note there is still a lot of misinformation and unrealistic expectations about what this technology can currently achieve. Over the past few months, HyperDraft has received an influx of requests from law firms and legal departments for education and consulting on how to practically apply AI like large language models. Many organizations feel pressure from management to “do something” with AI, but lack a clear understanding of the concrete problems they aim to solve. This results in a solution in search of a problem situation.

Tony and Ashley provide several key lessons learned regarding limitations of generative AI. It is not a magic bullet or panacea – you still have to put in the work to standardize processes before automating them. The technology excels at research, data extraction and summarization, but struggles to create final, high-quality legal work product. If the issue being addressed is about standardizing processes or topics, then having the ability to create 50 different ways to answer the issue doesn’t create standards, it creates chaos.

Current useful applications center on legal research, brainstorming, administrative tasks – not mission-critical legal analysis. The hype around generative AI could dampen innovation in process automation using robotic process automation and expert systems. Casetext’s acquisition by Thomson Reuters illustrates the present-day limitations of large language models trained primarily on case law.

Looking to the near future, Tony and Ashley predict the AI hype cycle will continue to fizzle out as focus shifts to education and literacy around all forms of AI. More legal tech products will likely combine specialized AI tools with large language models. And law firms may finally move towards flat rate billing models in order to meet client expectations around efficiency gains from AI.

Listen on mobile platforms:  Apple Podcasts |  Spotify

Contact Us:

Twitter: ⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠, or ⁠⁠⁠⁠@glambert⁠⁠⁠⁠
Voicemail: 713-487-7821
Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠

⁠⁠TranscriptContinue Reading You Still Need to Put in the Work: Hyperdraft’s Ashley Carlisle and Tony Thai on the AI Hype Cycle (TGIR Ep. 213)

The Geek in Review podcast welcomed Kriti Sharma, Chief Product Officer of Legal Tech at Thomson Reuters, to discuss AI and ethics in the legal industry. Kriti talks to us about the importance of diversity at Thomson Reuters and how it impacts product development. She explained TR’s approach to developing AI focused on augmenting human skills rather than full automation. Kriti also discusses the need for more regulation around AI and the shift towards human skills as AI takes on more technical work.

A major theme was the responsible development and adoption of AI tools like ChatGPT. She discusses the risks of bias but shared TR’s commitment to building trusted and ethical AI grounded in proven legal content. Through this “grounding” of the information, the AI produces reliable answers lawyers can confidently use and reduce the hallucinations that are prevalent in publicly commercial Gen AI tools.

Kriti shares her passion for ensuring people from diverse backgrounds help advance AI in law. She argues representation is critical in who develops the tech and what data trains it to reduce bias. Kriti explains that diversity of experiences and knowledge amongst AI creators is key to building inclusive products that serve everyone’s needs. She emphasizes Thomsons Reuters’ diversity across leadership, which informs development of thoughtful AI. Kriti states that as AI learns from its creators and data like humans do, we must be intentional about diverse participation. Having broad involvement in shaping AI will lead to technology that is ethical and avoids propagating systemic biases. Kriti makes a compelling case that inclusive AI creation is imperative for both building trust and realizing the full potential of the technology to help underserved communities.

Kriti Sharma highlights the potential for AI to help solve major societal challenges through her non-profit AI for Good. For example, democratizing access to helpful legal and mental health information. She spoke about how big companies like TR can turn this potential into actual services benefiting underserved groups. Kriti advocated for collaboration between industry, government and civil society to develop beneficial applications of AI.

Kriti founded the non-profit AI for Good to harness the power of artificial intelligence to help solve pressing societal challenges. Through AI for Good, Kriti has led the development of AI applications focused on expanding access to justice, mental healthcare, and support services for vulnerable groups. For example, the organization created the chatbot tool rAInbow to provide information and resources to those experiencing domestic violence. By partnering frontline organizations with technologists, AI for Good aims to democratize access to helpful services and trusted information. Kriti sees huge potential for carefully constructed AI to have real positive impact in areas like legal services for underserved communities.

Looking ahead, Kriti says coordinated AI regulations are needed globally. She calls for policymakers, companies and society to work together to establish frameworks that enable adoption while addressing risks. With the right balance, AI can transform legal services for the better.

Links:

Listen on mobile platforms:  Apple Podcasts |  Spotify

Contact Us:

Twitter: ⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠, or ⁠⁠⁠⁠@glambert⁠⁠⁠⁠
Voicemail: 713-487-7821
Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠

⁠⁠Transcript

Continue Reading Thomson Reuters’ Kriti Sharma on Responsible AI: The Path to Trusted Tech in Law

In this episode of The Geek in Review podcast, host Marlene Gebauer and co-host Greg Lambert discuss cybersecurity challenges with guests ⁠Jordan Ellington⁠, founder of ⁠SessionGuardian⁠, ⁠Oren Leib⁠, Vice President of Growth and Partnership at SessionGuardian, and ⁠Trisha Sircar⁠, partner and chief privacy officer at Katten Muchin Rosenman LLP.

Ellington explains that the impetus for creating SessionGuardian came from working with a law firm to secure their work with eDiscovery vendors and contract attorney staffing agencies. The goal was to standardize security practices across vendors. Ellington realized the technology could provide secure access to sensitive information from anywhere. SessionGuardian uses facial recognition to verify a user’s identity remotely.

Leib discusses some alarming cybersecurity statistics, including a 7% weekly increase in global cyber attacks and the fact that law firms and insurance companies face over 1,200 attacks per week on average. Leib notes SessionGuardian’s solution addresses risks beyond eDiscovery and source code review, including data breach response, M&A due diligence, and outsourced call centers. Recently, a major North American bank told Leib that 10 of their last breach incidents were caused by unauthorized photography of sensitive data.

Sircar says law firms’ top challenges are employee issues, data retention problems, physical security risks, and insider threats. Regulations address real-world issues but can be difficult for global firms to navigate. Certifications show a firm’s commitment to security but continuous monitoring and updating of practices is key. When negotiating with vendors, Sircar recommends considering cyber liability insurance, audit rights, data breach responsibility, and limitations of liability.

Looking ahead, Sircar sees employee education as an ongoing priority, along with the ethical use of AI. Ellington expects AI will be used for increasingly sophisticated phishing and impersonation attacks, requiring better verification of individuals’ identities. Leib says attorneys must take responsibility for cyber defenses, not just rely on engineers. He announces SessionGuardian will offer free CLE courses on cybersecurity awareness and compliance.

The episode highlights how employee errors and AI threats are intensifying even as remote and hybrid work become standard. Firms should look beyond check-the-box compliance to make privacy and security central in their culture. Technology like facial recognition and continuous monitoring helps address risks, but people of all roles must develop competence and vigilance. Overall, keeping client data secure requires an integrated and ever-evolving approach across departments and service providers. Strong terms in vendor agreements and verifying partners’ practices are also key.

Listen on mobile platforms:  ⁠Apple Podcasts⁠ |  ⁠Spotify⁠

Contact Us:

Twitter: ⁠⁠⁠⁠⁠@gebauerm⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠@glambert⁠⁠⁠⁠⁠
Voicemail: 713-487-7821
Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠

⁠⁠⁠Transcript

⁠
Continue Reading Cybersecurity in the Remote Work Era: AI, Employees and an Integrated Defense – With SessionGuardian’s Jordan Ellington and Oren Leib, and Katten’s Trisha Sircar (TGIR Ep. 211)