261 | These Are Not ChatGPT: Why You Must Try Grok3, OpenAI Deep Research & Operator

In this Brainyacts:

From Tools to Teammates: What You Need to Know About Two New Types of Generative AI

If time-pressed?: Quick Take: The AI Shift You Cannot Ignore

GenAI is no longer just a tool—it’s a teammate. With the launch of Grok 3 and OpenAI’s Deep Research & Operator, AI is transitioning from simple assistants to reasoning models and autonomous agents that research, analyze, strategize, and execute legal tasks with minimal human input.

What’s Changed?

• Grok 3: A major competitor to OpenAI’s top models, excelling in reasoning and problem-solving.

• OpenAI Deep Research: Designed for complex legal analysis and iterative problem-solving.

• OpenAI Operator: An AI agent capable of handling real-world workflows, from research to document execution.

Why It Matters

• Reasoning Models act like junior associates—breaking down legal questions, analyzing precedent, and refining their own research.

• AI Agents function as full-time assistants—handling contract reviews, filings, and workflow automation.

The Legal AI Roadmap: Where We Are and Where We’re Going

• Now: AI can conduct multi-step legal analysis, automate contract reviews, and handle compliance tasks.

• Next: AI agents will generate legal strategies, predict case outcomes, and execute filings.

• Future: AI-first law firms, where lawyers focus on high-level strategy while AI handles execution.

The Deep Dive: From Tools to Teammates

Why Lawyers Cannot Ignore AI Current Evolution

There’s a moment in every major shift where things go from interesting to urgent—where something that once felt optional suddenly becomes non-negotiable.

For legal professionals, that moment is here.

Over the past two weeks, AI has fundamentally changed, and if you're still using it like it’s 2023, you're already behind.

Two major releases—GROK 3 from xAI and OpenAI’s Deep Research and Operator models—aren’t just minor upgrades. They represent a different category of AI altogether, one that’s smarter, more autonomous, and far more capable of reasoning through complex problems.

If you’re still using free-tier AI for the occasional case summary or contract review, you’re missing the real story. AI isn’t just a tool anymore. It’s becoming a teammate—one that can research, analyze, strategize, and execute tasks that would normally take hours of human effort.

The lawyers who figure this out now will be the ones who stay competitive. The ones who don’t? They’ll be outpaced by firms that are using AI as a force multiplier.

So let’s break it down.

The Breaking News: Grok3 and OpenAI’s Next-Gen Models

Let’s start with what’s new.

Just last night, xAI released GROK 3, and early tests suggest it’s one of the most powerful AI models on the market. Built by Elon Musk’s team, this model isn’t just competing with OpenAI’s best—it may be outperforming them in reasoning and problem-solving tasks.

Meanwhile, OpenAI has launched two models two weeks ago that legal professionals need to be paying attention to:

• Deep Research – An AI built specifically for complex reasoning, iterative research, and deep analysis. Unlike standard GPT models, which generate one-off responses, Deep Research is designed to think through problems, refine its own answers, and work dynamically through multi-step legal inquiries.

• Operator – A true AI agent that can interact with websites and systems autonomously—booking travel, filling out forms, even handling real-world workflows with minimal human intervention.

If you haven’t been keeping up, you might be thinking: Okay, but aren’t these just more advanced versions of what we already have?

No. They’re qualitatively different—and that matters.

Beyond GPT: The Shift to Reasoning and Agents Models

Most of your are likely stuck in GPT-mode—you open ChatGPT, type in a prompt, get a response, and move on. That’s fine, but it’s also a very limited way to use AI.

Here’s where AI is actually going:

1. Reasoning Models (The Thinkers)

Traditional GPT models are great at generating responses quickly, but they struggle with nuance, ambiguity, and multi-step reasoning.

Reasoning models—like OpenAI’s Deep Research and Grok3’s DeepSearch—are different. They:

• Break down complex problems step by step, without needing constant human input.

• Refine and iterate their own answers—meaning they don’t just generate text, they reason through legal inquiries.

• Handle ambiguity better, recognizing when an issue is unresolved rather than forcing an answer.

For lawyers, this is a major upgrade. A reasoning model isn’t just going to summarize case law—it’s gong to analyze legal precedent, identifying contradictions, and recommending the best course of action.

2. AI Agents (The Doers)

Then there’s the next step beyond reasoning models: AI agents.

An AI agent doesn’t just suggest something—it executes. It can:

• Run a multi-step research process autonomously

• Fill out paperwork and submit filings

• Review hundreds of documents, flag key clauses, and recommend changes

• Schedule meetings, draft emails, and interact with systems like a real assistant

This is what OpenAI’s Operator is aiming to do—automate workflows end to end, not just assist with small tasks.

So, where do these advancements fit into the bigger picture?

The 5 Levels of AI Agent Evolution

1. Generalist Chat Assistants (Where We Started)

• Basic chatbots (e.g., early ChatGPT) – limited contextual awareness, requiring constant human refinement.

2. Subject-Matter Experts

• AI agents trained on legal-specific data sets (e.g., EvenUp, Darrow).

• More domain-specific accuracy, less manual correction required.

3. Autonomous AI Agents (We Are Here)

• AI capable of multi-step problem-solving, executing structured legal workflows.

• Examples:

  • Contract analysis agents that review agreements and flag high-risk clauses.

  • Regulatory compliance agents that scan legal databases for new rulings.

4. AI Agent Innovators (Coming Soon)

• AI that goes beyond executing and starts developing new legal strategies.

• Example: AI generating new legal arguments based on precedent and statutory analysis.

5. AI-First Legal Organizations (The Future?)

• Law firms structured around AI-driven legal work, with human lawyers focusing solely on high-level strategy, ethics, and court representation.

This is the big shift that you need to understand:

AI isn’t just a tool anymore—it’s a teammate.

Right now, most lawyers think of AI like a better Google search—you type something in, it spits something back. But that’s already outdated thinking.

A reasoning model acts more like a junior associate—it can break down complex cases, refine its own research, and help build legal strategies.
An AI agent acts like a full-time legal assistant—handling research, drafting, and administrative tasks autonomously.

What Happens If You Don’t Adapt?

If you’re still using ChatGPT Free or only engaging with AI occasionally, here’s the reality:

• Other lawyers are already using premium reasoning models to draft stronger arguments and analyze case law faster than you can manually.

• Firms adopting AI agents are automating entire legal workflows, slashing costs, and outpacing competitors.

• The gap between “AI-literate lawyers” and those who ignore this shift is growing every day.

At some point, it’s not going to be “AI vs. No AI.” It’s going to be “AI-augmented lawyers vs. everyone else.”

And you already know which side will win.

What You Should Do Next

This isn’t about AI hype. It’s about practical steps to stay competitive.

1.    Start experimenting with reasoning models.

• If you haven’t used OpenAI’s Deep Research, you’re missing the next level of legal AI. Try it out, compare it to standard GPT models, and see the difference.

2.    Think beyond prompts—start using AI for workflows.

• Instead of asking ChatGPT for a case summary, use a reasoning model to analyze legal precedent and recommend next steps.

• Instead of drafting a contract manually, have an AI agent review 100 similar contracts and identify potential risks.

3.    Watch my breakdown of GROK 3, Deep Research, and AI agents.
I’ve recorded a walkthrough video showing exactly how these models work, what they do well, and where they struggle.

For the Cannabis market report I show in the video, you can access it here.

Reasoning Models:

1. OpenAI's o1 - Known for its capabilities in logical reasoning and problem-solving, particularly in tasks involving coding and mathematics. It's designed to show step-by-step reasoning which can be crucial in legal analysis.

2. OpenAI's o3 - An advancement over o1, this model excels in tasks requiring deeper deliberation and complex reasoning, making it suitable for legal scenarios where detailed analysis is needed.

3. DeepSeek-R1 - An open-source model that has shown promise in reasoning tasks, especially in areas like mathematics and coding, which can be applied to legal document analysis or contract drafting.

4. Gemini-Thinking - A model from Google's Gemini series, which performs well in abstract reasoning, useful for spotting legal issues or anticipating arguments in a case.

5. xAI’s Grok3 - detailed above

Agentic (or near-agentic) Models:

1. Anthropic's Computer Use - Powered by the Claude 3.5 Sonnet model, this capability allows the AI to interact with desktop environments by simulating human actions like clicking, typing, and navigating through interfaces. It's designed to perform tasks like managing documents or scheduling.

2. Google's Project Mariner - An AI agent that operates within Google's Chrome browser, capable of taking actions on behalf of the user, such as booking travel or managing online shopping tasks. It's part of Google's broader push towards more interactive and autonomous AI systems.

3. Microsoft's Recall - While more focused on personal computing, Recall uses screenshots to navigate and interact with a user's PC, much like Operator does with web interactions. It could potentially extend to professional tasks, enhancing productivity by automating routine computer-based tasks.

4. Apple Intelligence - Although specifics are less public, the direction is towards making devices more proactive and autonomous in task execution. Early features though are a bit silly - like custom emojis.

5. OpenAI’ Operator - detailed above

No-Code AI Agents

1. AgentGPT - Allows users to set a goal, after which the agent autonomously thinks of tasks, executes them, and learns from the outcomes. It's designed to work within a browser environment, providing an accessible entry point for non-coders to deploy AI agents.

2. Cognosys - Similar to AgentGPT, Cognosys focuses on goal setting where the AI generates and executes tasks.

3. AgentRunner - Specializes in web interaction, where it searches and browses the web to collect data. This can be particularly useful for research tasks or gathering information from the internet based on user directives without needing to write code.

4. GodMode - This agent proposes actions to achieve a set goal, provides reasoning behind these actions, and uniquely allows for user feedback in the loop.

5. MULTI·ON - Acts as an agent that can browse and interact with websites on behalf of the user. This can automate tasks like filling forms, extracting data, or managing online interactions, all without direct user intervention or coding knowledge.

Predictions on AI Reasoning and Agent Models in Law:

Lawyers and Law Firms:

• Task Automation: Lawyers will delegate routine tasks like legal research, document review, and due diligence to AI agents. This will significantly reduce time spent on these duties, allowing more focus on strategy, client interaction, and courtroom advocacy.

• Enhanced Legal Analysis: AI agents will analyze vast quantities of case law and legal documents to uncover precedents or patterns that might be overlooked by human analysts, leading to more robust legal arguments and strategies.

• Content Creation: Law firms will use AI agents for drafting initial legal documents (contracts, briefs, motions), client communications, and even marketing content. This will increase efficiency but also raise questions about originality and ethical considerations in legal document production.

• Client Intake and Management: AI agents will handle initial client interactions, gather preliminary information, and even provide basic legal advice or direct clients to the appropriate services within the firm.

• Prompt Engineering Irrelevance: As AI agents become more autonomous, the need for human-crafted prompts in legal applications will diminish. Agents will self-optimize their tasks based on feedback and results.

In-House Counsel:

• Corporate Compliance: AI agents will continuously monitor regulatory changes and compliance requirements, alerting counsel to issues or opportunities for proactive legal advice.

• Contract Management: They'll automate the review, negotiation, and management of contracts, reducing human oversight time and enhancing accuracy in contract terms.

• Risk Assessment: AI will assist in identifying potential legal risks by analyzing business operations, communications, and transactions in real-time.

Courts:

• Case Management: AI agents might assist in docket management, ensuring cases are scheduled efficiently and that all necessary documents are in order before court sessions.

• Evidence Analysis: They could help in parsing through digital evidence, identifying key pieces, and even suggesting how evidence might be presented or challenged in court.

• Judicial Decision Support: While not replacing judges, AI could provide decision-support tools by offering insights from similar past cases, potentially aiding in more consistent judicial decisions.

Litigants (Self-Represented and with Lawyers):

• Access to Legal Information: AI agents will democratize access to legal advice by providing self-represented litigants with basic guidance, document preparation, and understanding of legal processes.

• Personalized Legal Strategies: For those with legal representation, AI agents can help tailor strategies based on the opponent's past behaviors in court, predicted outcomes, and the litigant's specific circumstances.

• Reduction in Procedural Errors: AI can guide both represented and pro se litigants through court procedures, reducing the likelihood of procedural dismissals or errors.

Who is the author, Josh Kubicki?

I am a lawyer, entrepreneur, and teacher. Not a theorist, I am an applied researcher and former Chief Strategy Officer, recognized by Fast Company and Bloomberg Law for my work. Through this newsletter, I offer you pragmatic insights into leveraging AI to inform and improve your daily life in legal services.