Chat to converse and design what you want to see. Code to build exactly what you want. Cowork to be your multi-task assistant. (Vol. 4)

The question is — where is the data coming from?

More often than not you’re manually downloading it. Exporting a CSV. Copying a table. Pasting it in. Every single time.

You’re leaving time saved on the table. You’re leaving automation on the table.

That’s where MCP comes in.

What is MCP?

MCP stands for Model Context Protocol. Forget the name — here’s what it actually means for an accountant.

It’s a bridge between Claude and your actual systems. Instead of exporting data, copying a table, or manually typing numbers into a prompt — Claude connects directly to your tools and pulls the data itself. Live data. No copy paste. No export. No manual step in between.

Think about what that means in practice. The flux analysis from Vol. 5 — pulling chart of accounts, pulling period balances, comparing periods, generating commentary — none of that required a single manual data export. MCP pulled it directly from the system.

That’s the shift. Chat, Code, and Cowork design what you want Claude to do. MCP gives it the data to do it with.

Where does MCP connect?

This is where it gets practical for accountants. There are three categories worth knowing.

Your ERP

Most modern ERPs have built MCP connections. NetSuite, Rillet, and Campfire all have MCP — which means instead of exporting a report, Claude can reach directly into your chart of accounts, pull period balances, and work with live data. No file. No download. No manual step.

If your ERP has an MCP connection, this is where you start.

Spend Management

Same story on the spend side. Ramp and Brex both have native MCP connections. Claude can pull transaction data, card activity, and spend by category directly — without you touching a CSV. Ask Claude to analyze last month’s spend by vendor, flag anything over a threshold, or compare to prior period. It goes and gets the data itself.

Admin and workflow tools

Beyond the financial systems there’s a growing library of MCP connectors for the tools accountants use every day.

• Slack — Claude can pull messages, threads, and context from conversations your team has already had.

• Email — surface relevant threads without switching windows.

• Google Drive — pull documents and spreadsheets directly into the conversation.

Calendar tools, project management systems, and more are being added constantly. The pattern across all of them is the same. Connect once. Claude pulls what it needs when it needs it.

What this looks like in practice

Here’s the clearest way to understand the difference MCP makes.

Without MCP: Open ERP. Export data. Save file. Upload to Claude. Describe the format. Ask Claude to run the analysis.

With MCP: Tell Claude what you need. It connects, pulls the data, runs the analysis.

Same output. Fraction of the friction.

How to get started

Getting connected is simpler than it sounds.

Step 1 — Open Claude desktop and go to Settings. Find the Connectors section.

Step 2 — Browse the available connectors. Look for the tools you already use — your ERP, your spend management platform, your admin tools.

Step 3 — Connect and authorize. Claude will ask for the permissions it needs. It only sees what your account is allowed to see — the same permissions you already have.

Step 4 — Test it. Open a conversation and ask Claude something that requires data from that system. See what it pulls back.

Step 5 — Build from there. Once you’ve seen it work once, you’ll immediately start thinking about every other workflow where you’re manually moving data that MCP could handle automatically.

The bigger picture

MCP is what turns Claude from a chat tool into an accounting system.

Everything from Vol. 1 through Vol. 5 gets more powerful with MCP underneath it. Better prompts on live data. Projects that pull real numbers. Cowork workflows that run without manual steps in between.

The accountants connecting their tools right now are operating at a completely different level than the ones still copying and pasting. Not because they’re more technical. Because they took the time to connect once and let the system do the rest.

Vol. 7 is next. Keep building.

Here’s my question to you:

What system would you most want Claude to connect to directly? Drop it in the comments — I read every one.

Leave a comment

The purpose of New Age Accounting is simple: to empower accountants — at every level — to become builders, not bookkeepers. Whether you’re a staff accountant, a controller, or a CFO, there’s something here for you. Some topics will be high level, others will come with step-by-step guides, and some will include the exact prompts and tools you need to start building today.

If you’ve made it this far, you’re already thinking differently about this profession. Subscribe and come build with us.

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They build a great workflow. Get a great output. Close the tab. Next month they open a brand new chat and start from scratch — same context, same instructions, same examples, rebuilt from zero.

Every. Single. Month.

This issue is about fixing that. There are two ways to do it. Both work. Pick the one that fits how you work.

The problem with starting fresh

Every time you open a new chat, Claude doesn’t know anything about you. It doesn’t know your chart of accounts. It doesn’t know your format. It doesn’t know your CFO’s communication style or what threshold you use for material variances.

So you paste it all in. Again. Or you skip it and get generic output. Again.

The goal is to build the context once and reuse it every month. Here are the two ways to do that.

Option 1 — The saved Cowork chat

This is the simpler path and it works.

Cowork is Claude working through a multi-step task autonomously within a single conversation (Vol. 4). The key insight most people miss — you don’t have to start a new chat every month. You can go back into the same conversation and Claude already has the full history. The context is there. The workflow is there. You pick up where you left off.

Here’s what that looks like in practice with a real workflow.

Every month I run a flux analysis. Using Claude’s MCP connection I pull chart of account names directly from our system. Then by period I pull the balances for each account. Claude compares current period to prior period — calculating dollar and percentage change for every line. Then it pulls the data together and generates commentary explaining the material movements.

One workflow. Chart of accounts pulled. Balances compared. Variance calculated. Commentary written.

The first time I set this up I built the context — my role, my company, my format, my materiality threshold. Now every month I go back into that same chat. Claude already knows all of it. I connect via MCP, pull the current data, and the workflow runs.

Best for: Individual workflows you own yourself. Recurring monthly tasks where you’re the only one using it. Getting started quickly without a lot of setup.

The one limitation: If you accidentally close the chat, start a new one, or want someone else on your team to run the same workflow — you’re rebuilding from scratch. The context lives in the conversation history, not above it.

Option 2 — Claude Projects

Projects is the more structured path. Same goal — build once, use every month — but the context lives at the workspace level, not inside a conversation.

A Project is a persistent workspace where you write standing instructions and upload reference documents once. Every conversation you open inside that Project — whether it’s your first or your fiftieth, whether it’s you or someone on your team — starts with all of that already loaded. Claude already knows everything before you type a single word.

Three things go inside a Project:

Instructions — who Claude is, what context it has, how it should behave (Vol. 3). Your persistent CO-STAR framework baked in permanently (Vol. 2). For a flux analysis Project this might include your role, your company’s industry, your materiality threshold, your CFO’s preferred tone, and how you want variances presented.

Knowledge — documents you upload once and reference forever. Your chart of accounts. A prior month’s flux as a format template. Any standing context that would otherwise take five minutes to paste in every conversation.

Conversations — every chat inside the Project starts from the same foundation. New conversation, same context. The history doesn’t have to carry it — the Project does.

Best for: Workflows you want to share with a team. Workflows that rely on uploaded reference documents. Building a clean organized library of named workspaces instead of hunting through chat history. Scaling beyond yourself.

Which one should you use?

Honestly — it depends.

If you’re a solo accountant running your own monthly workflows and you’re comfortable going back into the same chat every month — the saved Cowork approach works. It’s simpler to set up and gets you the same result.

If you want something more organized, more shareable, more reliable regardless of what happens to any individual conversation — build a Project. The setup takes longer upfront but the infrastructure is cleaner and scales better.

Both beat starting from scratch every month. That’s the point.

How to build your first Project

Step 1 — Open Claude desktop and find the Projects section in the left sidebar.

Step 2 — Create a new Project and name it for the job it does. “Monthly Flux Analysis.” “Close Commentary.” “Cash Analysis.”

Step 3 — Write your instructions. Start simple: who Claude is, what company context it needs, what standard it holds, how you want the output formatted. Refine over time.

Step 4 — Upload your knowledge. At minimum: your chart of accounts and one prior output as a format template.

Step 5 — Open your first conversation inside the Project. Test it. Refine the instructions based on what’s missing. It gets better every time you use it.

The compounding effect

Whether you go with a saved Cowork chat or a Project — the principle is the same.

Build the context once. Every month after that you’re not starting from scratch. You’re building on something that already works.

The first month takes the most effort. The second month is faster. The third month faster still. By month six you have a workflow that produces consistent structured output faster than anything you’ve ever done manually.

That’s the compounding effect of building once instead of rebuilding every month.

Pick your most repetitive monthly workflow. The one where you spend the first ten minutes re-explaining context that hasn’t changed. Set it up — as a saved Cowork chat or a Project. Run it once. See what the second month feels like.

Vol. 6 is next. Keep building.

Here’s my question to you:

What’s the first workflow you’re going to stop rebuilding every month? Drop it in the comments — I read every one.

Leave a comment

The purpose of New Age Accounting is simple: to empower accountants — at every level — to become builders, not bookkeepers. Whether you’re a staff accountant, a controller, or a CFO, there’s something here for you. Some topics will be high level, others will come with step-by-step guides, and some will include the exact prompts and tools you need to start building today.

If you’ve made it this far, you’re already thinking differently about this profession. Subscribe and come build with us.

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But that’s like buying a Swiss Army knife and only ever using the bottle opener.

The same AI you’ve been using for chat can write and run code, build tools, and execute multi-step workflows — all without a computer science degree, a developer on staff, or an enterprise budget.

This is where the Accounting Engineer starts to take shape. Not just someone who uses AI — someone who knows which tool to use and when.

Today we’re covering three modes: Chat, Cowork, and Code. Same AI. Completely different capabilities. By the end of this issue you’ll know what each one is, when to use it, and what it looks like in an accounting workflow.

Let’s go.

Chat

Chat is where everyone starts — and for good reason. You type, it responds. Back and forth, in real time, like a conversation with someone who has read everything.

What it is: the conversational interface. You bring the question, the task, or the problem. Claude brings the knowledge, the drafting ability, and the patience to work through it with you.

When to use it: anything that benefits from a back-and-forth exchange. Drafting variance commentary. Summarizing a contract. Explaining a complex accounting standard in plain language. Preparing talking points for a board meeting. Writing the close narrative your CFO actually wants to read.

Here’s what a Chat prompt looks like in practice:

That’s Chat at its best. Specific context, clear task, defined audience. The output comes back ready to use or one refinement away from being sent.

The thing most accountants don’t realize: Chat isn’t just for one-off tasks. The conversation is the tool. The longer and more specific the thread, the better the output gets. Vol. 3’s framing techniques — establishing a role, providing an example, asking to be asked — all live here. If you’re not using those yet, go back and give it a read.

Chat is the foundation. But it’s not the ceiling.

Cowork

Chat is a conversation. Cowork is something else entirely.

Cowork is Claude working alongside you on a multi-step task — not just responding to one prompt but executing a workflow. You hand it a complex job. It breaks it down, works through the steps, and comes back with something you couldn’t have produced as fast on your own.

This is where AI stops feeling like a tool and starts feeling like a team member.

What it is: Claude operating autonomously across multiple steps within a single task. Think of it like handing a project to a highly capable colleague and saying "here's what I need" — and coming back to a finished product instead of a blank page.

When to use it: complex tasks that would normally require moving between multiple tools and sources. Anything where the output has multiple parts. Anything where you’d normally spend an hour pulling pieces together before you could even start the real work.

Here’s what a Cowork task looks like in practice:

You’re about to renew a vendor contract. Instead of spending two hours reading through the agreement, cross-referencing terms, and drafting a memo from scratch, you hand it to Claude:

One prompt. Three deliverables. What used to take a morning now takes minutes.

The thing most accountants don’t realize: most people never get here because they stop at Chat. Cowork requires you to think differently about how you assign work — not “what do I need to ask” but “what outcome do I need and what would it take to get there.”

Code

This is where most accountants stop reading. Don’t.

You don’t need to know how to code to use Claude’s code capabilities. You need to know the problem well enough to describe it. That’s the accountant’s advantage — you understand the close, the reconciliation, the report better than any developer ever will. Claude handles the syntax. You handle the problem definition.

What it is: Claude writing, running, and debugging code on your behalf. You describe what you need in plain language. Claude builds it.

When to use it: building things that don’t exist yet. A close checklist that lives in a system instead of someone’s head. A dashboard that pulls your key metrics together in one place. An automation that flags reconciling items over a set threshold and surfaces them without you having to hunt for them. A tool that reformats a messy data export into a clean, board-ready table in seconds instead of an hour.

Here’s what a Code prompt looks like in practice:

You didn’t write a single line of code. You described the problem. Claude built the solution.

The thing most accountants don’t realize: the first build doesn’t have to be perfect. It doesn’t have to be scalable on day one. It just has to work better than what you had before. Start with one process that frustrates you every month. Describe it to Claude. See what it builds. Refine from there.

Bringing it all together

Three modes. One decision framework.

Ask yourself: what am I actually trying to do?

If you need to draft, summarize, explain, or refine something — Chat.

If you need to hand off a complex multi-step task and get a complete output back — Cowork.

If you need to build something that doesn’t exist yet — a tool, an automation, a dashboard — Code.

They’re not mutually exclusive either. The best workflows use all three. You might Chat to define the problem, use Code to build the automation, and then hand the output to Cowork to summarize and package for the CFO.

That’s the full toolkit. That’s what it looks like when an accountant stops using 10% of what’s available to them.

Pick one task from your current workflow and deliberately use a mode you haven’t tried before. If you’ve only ever used Chat — describe a process to Claude and ask it to build you something. If you’ve never tried Cowork — hand it a multi-step task and see what comes back.

The gap between where most accountants are and where they could be isn’t talent. It isn’t access. It’s awareness.

Keep building.

Here’s my question to you:

Which of the three modes are you most excited to try — and what’s the first task you’re going to use it on? Drop it in the comments — I read every one.

Leave a comment

The purpose of New Age Accounting is simple: to empower accountants — at every level — to become builders, not bookkeepers. Whether you’re a staff accountant, a controller, or a CFO, there’s something here for you. Some topics will be high level, others will come with step-by-step guides, and some will include the exact prompts and tools you need to start building today.

If you’ve made it this far, you’re already thinking differently about this profession. Subscribe and come build with us.

Subscribe now

Quick recap: Vol. 1 covered AI & LLMs — what they are, which ones exist, and how to choose one. Vol. 2 introduced prompting and the CO-STAR framework — the foundation of getting outputs that are actually usable. If you missed either, go back and start there (using links provided) as this series builds week by week.

Now, before we go any further — did you use the CO-STAR framework to enhance your prompting? Because if you did, one of two things likely happened. Either it worked better than expected, and you’re starting to see what all the hype around AI is. Or, it worked okay, the output was close, but you had to rewrite more than anticipated.

If it’s the latter, that’s perfect — that’s exactly what Vol. 3 is for.

Why good prompts still fall short.

Here’s something I’ve noticed working with these tools daily: even a well-written prompt can fall short if the LLM doesn’t have the right frame for the task.

What does that even mean?

Think about how you’d provide context to a first year associate or new accountant on the team. You wouldn’t just hand them a task and walk away. You’d walk them through their specific role in the process, what standard you’d like set, what a great outcome looks like, and potentially provide examples of something in the past (SALY, if you know, you know).

That context — or the frame around the task — is really what separates a good output from a great one.

Good outputs come from people giving the LLM the task. Great outputs come from giving the LLM both the task and the frame.

Let’s get into the meat of it. Here are four techniques to creating a strong frame to immediately improve your outputs. None of them are complex but all of them provide real value to your prompting skills.

Technique 1 : Establish a role

This is going to sound strange. But, before you describe a task, tell the LLM who it is. Weird, I know. However, when you set the stage for the LLM, it activates a specific body of knowledge and strives to achieve in line with that specific standard.

Here’s an example without a role:

Here’s an example with a role:

Same task. However, the second prompt will produce an output that is materially more useful because the LLM is approaching it from a specific lens, instead of a general one. This works for controllers, auditors, analysts, and more.

Try it on your next prompt. The difference will be immediate.

Technique 2 : Provide an example

Just like a first year or someone new to the company, if you want a specific output format, provide an example to the LLM.

Instead of describing the format you’d like to see — which is much more difficult than it sounds — just provide an example of something similar for it to work from. It’s as simple as uploading the file and saying, “use the uploaded document as a template”.

Here’s what that looks like in practice. Say you want the LLM to write a board-ready variance commentary. Instead of writing “format it like a board report with bullet points and an executive summary” — just upload last month’s commentary and say “match this format exactly.“ The LLM picks up the tone, the structure, the level of detail, and the language all at once.

Once provided, the LLM then has a template, tone, task and more to work from. The output will match your format far more closely than if you tried to describe it from scratch.

An important thing to note, once you’ve created this task, make sure you save the prompt with the example baked in. I typically rename my chats and pin them, if I’m going to be using them later on. If you do this, you will be able to use the same chat every month and it saves more time and tokens because you aren’t reprocessing the prompt end to end.

Technique 3 : Ask to be asked

Hands down, this is one of the most underused techniques. Before you write a complex prompt, try this:

Simple, right?

Two things happen when you do this.

First, the LLM finds gaps and weak points in your prompt you likely didn’t know were there. It’ll ask about your audience, your format preference, the context behind the numbers, the tone, and more. It takes the CO-STAR framework to the next level. Most of which, are things you would have forgotten to include.

Second, it teaches you how to prompt better over time. The questions AI asks you are the exact things you should be thinking about and including in your prompts by default. After a few rounds of this, you’ll start anticipating these questions automatically.

Any time I’m prompting something new for the first time, I do this. It almost always produces a better first output than going straight to the task.

Technique 4 : Refine, don’t restart

This one is a mindset shift as much as a technique.

When the output isn’t quite right, most people start over. New prompt, from scratch, trying to get it right in one shot.

Don’t do that.

Remember what Vol. 1 said: you’re not Googling. You’re having a conversation. That means you can — and should — push back, redirect, and refine within the same conversation.

Here’s what that looks like:

First output comes back. It’s okay but too formal for your CFO’s style.

Instead of starting over, say:

Each refinement builds on the last. By the third or fourth exchange, you have something significantly better than anything a single prompt would have produced.

The conversation is the tool. Use it.

Bringing it all together

Alright. We’ve gone through a lot in the last few weeks. Here’s what a fully loaded prompt looks like using everything from Vol. 2 and Vol. 3 combined:

That prompt has a role, an example, real context, and an instruction to clarify before it starts. That’s about as strong as a prompt gets.

Try it this week on something from your actual close. See what comes back. Refine once. Save it.

The accountants putting these into practice right now are producing work that would have taken hours in a fraction of the time — and they’re getting better at it every week. That’s the compounding effect of learning this properly. Vol. 4 is next. Keep building.

Here are my questions to you:

Which of these four techniques are you most excited to try — and which one surprised you most? Click below and tell me. I read every response.

Leave a comment

The purpose of New Age Accounting is simple: to empower accountants — at every level — to become builders, not bookkeepers. Whether you’re a staff accountant, a controller, or a CFO, there’s something here for you. Some topics will be high level, others will come with step-by-step guides, and some will include the exact prompts and tools you need to start building today.

If you’ve made it this far, you’re already thinking differently about this profession. Subscribe and come build with us.

Subscribe now

1/ More often than not, the issue isn’t the tool — it’s the prompt.

2/ If the only AI you’ve used is the chat feature, you haven’t even scratched the surface. But we’ll save that for another day!

The art of prompting

What is prompting? Simple answer: the questions, comments, and/or instructions you provide to an LLM. It can be one word or a paragraph, a question or a command, simple or detailed. Whatever you put into the little box (see image below) is considered a prompt.

General tip: the more specific the prompt, the more effective the output. For example, if you type “help me with this reconciliation” — but fail to add additional context — the LLM has no idea what reconciliation you’re referencing, what account, what steps you’ve already taken, the format of the output, etc. It will provide something very generic because that is all it has to work with.

The fix is simple: be more specific. So what does ‘more specific’ actually look like? That’s where CO-STAR comes in. There are several prompting frameworks out there. CO-STAR is the one I keep coming back to, and the one I believe translates best to accounting workflows.

Reference to image.

Context: The background information related to the situation, project or topic. Example: “We are a mid-sized manufacturing company closing out the Q4 books.”

Objective: The specific goal or task you want to be accomplished. Example: “Reconcile accounts payable and flag any discrepancies over $500.”

Style: The writing style you want. Example: “Present this in a formal, financial reporting style.”

Tone: The emotional feel of the output. Example: “Keep the tone professional, conservative, and audit-ready.”

Audience: Who the output is for. Example: “This report is intended for the CFO and the external auditors.”

Response: The format and length you expect. Example: “Provide the journal entry as a CSV file.”

Here’s what that looks like in practice. An example of a weak prompt would be:

An example of a strong prompt would be:

Same desired output, completely different results. The first may produce a template or a rough outline. The second gets you something you could actually send to the intended audience. The more specific, the better.

Start with one prompt this week. Use CO-STAR. See what comes back. Next issue, we’ll dive deeper into the trenches. But prompting is the foundation — get it right first.

Here’s my question to you:

What’s a task you do every week that you haven’t tried prompting yet? Why not? Click the button below and tell me. I read every response.

Leave a comment

The purpose of New Age Accounting is simple: to empower accountants — at every level — to become builders, not bookkeepers. Whether you’re a staff accountant, a controller, or a CFO, there’s something here for you. Some topics will be high level, others will come with step-by-step guides, and some will include the exact prompts and tools you need to start building today.

If you’ve made it this far, you’re already thinking differently about this profession. Subscribe and come build with us.

Subscribe now

Whether you are just starting out or are a seasoned veteran, one of the first ways to get into AI within accounting is through an LLM (large language model). An LLM is simply a type of AI that is trained to read, write, and reason using language. The most notable are Claude, ChatGPT, Copilot, and Gemini. If you’ve ever typed a question into one of those, you’ve already used one.

Each of these models has their own strengths and weaknesses. Claude, made by Anthropic, is known for its strong writing, deep analysis, and complex reasoning. ChatGPT, made by OpenAI, is widely recognizable in the space and is known for its broad capabilities, ease of use, and large user community.

As an example, I once dropped the same request into both Claude and ChatGPT: “Summarize the key risks in this contract.“ Claude returned a structured breakdown with specific flags; ChatGPT gave a cleaner, more readable summary but lacked depth. Neither was wrong. They just approached the response differently. Try the same thing for yourself. Same prompt, two tools. You’ll learn more in five minutes than reading any comparison article.

One thing worth understanding early on is that these tools are not search engines. You’re not Googling a keyword and scanning results. You’re having a conversation. The better you become at explaining what you need (prompting), the better the output.

Here’s what that looks like in practice:

• Weak prompt: “Help me with this reconciliation.”

• Strong prompt: “I’m reconciling our credit card statement to the GL for October. There are 14 unmatched transactions under $500. What are the most common reasons these mismatches happen? Where should I check first and how should I approach this task?”

Same task, completely different results. The more specific, conversational, and detailed you are, the better. The first one is vague. The second provides context — and context is everything.

Once you’ve picked a tool, here’s what to expect on pricing. Each of these LLMs has various tiers beginning at $0 (with limited usage) and scales to $200+ per month (depending on usage and other factors). It’s worth noting that most of the features that will impact your day-to-day only begin to take shape in paid versions.

Like most people, I personally started out using ChatGPT and I still find it to be a great tool. But over time, Claude has become my default of choice. Like many accountants I’ve spoken with, what won me over was the quality of analysis and its ability to handle dense, complex work — which we do daily. This has become more apparent as I’ve moved to higher tiers.

All things considered, when it comes to which is best, it depends on what you’re trying to accomplish and who you ask. There are many opinions. Focus on what you’re trying to accomplish, pick the one you prefer, and get after it.

If you don’t know where to start, here’s a prompt to try (replace words as needed):

I’m an accountant who wants to start using AI in my day-to-day work, but I’m not sure where to begin. Can you give me a simple, beginner-friendly roadmap? Start with the most practical first steps — things I can try today — and explain how AI can help with common accounting tasks like reconciliations, reporting, data analysis, or client communication.

Believe it or not, that is how it started for me. I knew this was the future, it was inevitable, however, I had no idea how to even begin. Now, through countless hours of trial and error, I still find myself asking Claude how to get more out of these tools.

Don’t overthink the prompt either — it doesn’t need to be perfect. One of the biggest misconceptions is that you need to know exactly what to say to get value out of these tools. You don’t. Just start prompting, see the result, and refine from there.

Start small. Keep refining. Sooner or later it’ll make sense and you’ll surprise yourself with what you’re capable of.

The accountants who will thrive in the next decade won’t necessarily be the ones who know the most technical details about how AI works behind the scenes. The accountants I’ve seen get the most out of these tools are the ones who identified a bottleneck, opened a tool, tried to build the solution, and kept going. Stay curious. Keep learning.

It’s worth noting that the same tool a beginner uses to draft an email to a client is the same one advanced users are connecting to live data, automating workflows, and running full flux analysis and scenario forecasting. That’s where this series goes. But it starts here.

Now that you know what these tools are, the next question is: how do you actually talk to them?

That’s where most people get stuck — and that’s exactly what we’re covering next.

Here are my questions to you:

Which LLM do you currently use? Do you have a strong preference to a specific LLM? Click the button below and tell me. I read every response.

Leave a comment

The purpose of New Age Accounting is simple: to empower accountants — at every level — to become builders, not bookkeepers. Whether you’re a staff accountant, a controller, or a CFO, there’s something here for you. Some topics will be high level, others will come with step-by-step guides, and some will include the exact prompts and tools you need to start building today.

If you’ve made it this far, you’re already thinking differently about this profession. Subscribe and come build with us.

Subscribe now