Last updated: June 6, 2025

Truth Series Part 1: Agentic AI & Accounting - How Dokugent Brings Traceability, Sign-Offs, and Certs to the Future of CPA Work¶

Agentic AI is no longer a fringe idea — it's becoming central to how professionals work across regulated industries. A recent article by the Journal of Accountancy (June 2025)¹ spotlighted how Certified Public Accountants (CPAs) are expected to collaborate with AI agents in the near future. These agents won’t just automate tasks. They’ll participate in workflows, reason through decisions, and assist in audits, tax classification, and financial reviews.

But this raises urgent questions:

How do you know what your AI agent actually did?
Who approved the plan it executed?
Can you prove that it followed professional standards and constraints?

Dokugent CLI: An Audit-Grade Trust Layer for AI Workflows¶

This is where Dokugent CLI comes in.

Dokugent is a documentation-first CLI framework for structuring, certifying, and tracing agentic AI behavior. It’s designed for accountable AI workflows — where plans are authored, reviewed, signed, simulated, and validated before an agent runs. Think of it as Git, but for agent plans with embedded receipts and role-based trust.

Let’s walk through how Dokugent supports CPAs using AI agents in practice — both from a practitioner’s perspective and from a developer’s point of view.

For the CPA, Dokugent provides confidence that AI behavior is constrained, reviewed, and provable. For the developer implementing these agents, Dokugent offers structured commands that scaffold, validate, and certify each step of the agent's lifecycle.

From plan to trace, the following steps ensure both human oversight and programmatic enforcement.

Planning Agent Behavior: Using `dokugent plan`¶

Before any AI agent can be run in a CPA workflow, its intent must be authored as a plan.

dokugent plan

Sample output:

{
  "plan": [
    {
      "id": "classify_transactions",
      "goal": "Classify 300+ bank transactions by tax category",
      "tools": ["openai-chat"],
      "constraints": [
        "Must not hallucinate categories",
        "Must cite source rules like BIR RMO 23-2018 or IRS Pub 463"
      ]
    },
    {
      "id": "generate_tax_report",
      "goal": "Format classified data into a summary report",
      "tools": ["markdown-formatter"],
      "constraints": [
        "Report must use standard tax reporting format",
        "Output must be human-readable and signed"
      ]
    }
  ]
}

📎 This ensures transparency before execution. No surprises.

See more about dokugent plan

Previewing and Reviewing: Ensuring Human Oversight¶

Before any agent is cleared to run, its plan is previewed and validated—typically by a trusted peer, senior team member, or designated reviewer.

This isn’t a blocker—it’s a safeguard. It ensures the agent’s intent matches organizational standards and professional expectations.

dokugent preview

This outputs:

"previewer": {
  "previewerName": "chatgpt",
  "email": "chatgpt@openai.com",
  "publicKey": "-----BEGIN PUBLIC KEY-----\nMCowBQYDK2VwAyEA0b1d91NtftCNhIzJ9yhH+U2cCMOrU9w4gWTzbf5dLzI=\n-----END PUBLIC KEY-----\n",
  "fingerprint": "e0b4a91e60d83ef164fa4d9ad69594969fe394359879ab3b88a4fbcd206cd1f6",
  "previewKeyVersion": "latest"
}

✅ Peer review is now part of the AI workflow.

See more about dokugent preview

Certifying the Plan: Using `dokugent certify`¶

Once a plan is reviewed, it must be cryptographically signed by an authorized certifier—often a compliance officer, partner, or delegated reviewer in the firm.

dokugent certify

Output:

"certifier": {
  "certifierName": "carmelyne_m_thompson",
  "email": "carmelyne@dokugent.com",
  "publicKey": "-----BEGIN PUBLIC KEY-----\nMCowBQYDK2VwAyEATtdnW+qkoYb2SAUaBM+TgjmzBKJjRRlSdKz8NTLnrMg=\n-----END PUBLIC KEY-----\n",
  "fingerprint": "099604b663f7e6f240534a26b8322d27b4f2db5162193b78aeb3df31550076eb"
}

✅ The agent certificate json file embeds: the owner, previewer, certifier, and compiler. This is real-world traceability — not AI theater.

See more about dokugent certify

Dryrun Before Deployment: Using `dokugent dryrun`¶

A critical step in audit-safe AI workflows is validating before execution:

dokugent dryrun

Dryrun checks:

Constraints are respected
All signer keys are valid
Source files are referenced
Estimated tokens within budget
Plan is compatible with previewed LLM scope

See more about dokugent dryrun

Simulate Agent Output: Using `dokugent simulate`¶

Once dryrun passes, the firm may simulate the agent’s behavior without affecting data:

dokugent simulate --llm=claude

Simulated output:

{
  "input": "2023_BDO_Transactions.csv",
  "outputPreview": {
    "Travel Expenses": 14,
    "Meals & Entertainment": 32,
    "Office Supplies": 9
  },
  "explanation": "Categories derived using BIR RMO 23-2018 and IRS Pub 463"
}

🔧 If you want the simulated output to be structured as machine-readable JSON instead of natural language or markdown, simply add this as a constraint inside your agent plan:

{
  "id": "generate_audit_report",
  "goal": "Produce a machine-readable audit output",
  "tools": ["openai-chat"],
  "constraints": [
    "Output must be in valid JSON format",
    "Include top-level keys: input, output, explanation"
  ]
}

This lets Dokugent simulate results that can be parsed, stored, or validated — not just inspected.

This is essential for regulatory-facing professions. It allows internal validation of what the AI is about to do.

And from a developer’s perspective, this is the stack: each command scaffolds one layer of agent control—plan, preview, certify, dryrun, simulate, trace. It doesn’t mean the accountant has to do it. But it means the team has a shared language of delegation and validation. Today, this tooling may sit with developers. In time, it will make sense to everyone working with agentic AI.

See more about simulate

Tracing Decisions Over Time: Using `dokugent trace`¶

After deployment, every agent plan can be traced by its persistent identifier:

dokugent trace doku://taxbot@2025-06-02_09-41-05

Trace reveals:

The original plan
Who authored and signed off
Token cost
Decision rationale
LLM used and constraints

🔎 This makes agent behavior auditable across time and teams.

See more about dokugent trace

Why This Matters for CPAs¶

As accounting firms begin to adopt AI agents for work like:

Transaction classification
Tax preparation
Forecasting
Expense verification

…it’s no longer enough to say "AI handled that."

CPAs aren’t expected to become developers—but they are expected to work with AI systems in ways that hold up to audit, review, and client accountability.

Dokugent doesn’t push that burden onto the practitioner. It creates a shared structure where developers build with audit in mind, and professionals operate within a system that documents who approved what, under what constraints, and when.

You must be able to:

Prove who authorized the behavior
Show the constraints it followed
Explain the LLM’s source logic
Produce receipts on demand

Dokugent doesn’t just make this possible — it makes it structured.

External Links and Sources¶

Explore Other Use Cases¶

🚧 Project Status: Active Development Phase¶

Dokugent is currently in active development. While many of its core features — including agent planning, certification, traceability, and simulation — are already functional, we are still refining workflows, validating real-world use cases, and improving developer UX.

This blog post reflects an internal test case built using the current CLI features. Outputs are simulated to match JSON schemas but may differ depending on your agent setup or tool configuration. And right off the bat, we have our system ready for you to bring your own JSON via our dokugent byo.

We welcome feedback and contributions — but this isn’t a v1 stable release just yet. Think of this as a working notebook from the field.

Final Thoughts¶

Agentic AI is here, and regulated industries are waking up to the need for audit trails, identity, and traceable behavior. Dokugent was built to meet this exact moment.

CPAs won’t trust AI until it gives receipts. Now it can.

Try Dokugent CLI today and bring trust back into AI workflows.

This article is part of our Trustworthy AI Series. Subscribe to stay updated on real-world AI infrastructure you can actually deploy.

Categories¶

Journal of Accountancy, “Agentic AI Poised to Change the Way CPAs Work,” June 2025. https://www.journalofaccountancy.com/issues/2025/jun/agentic-ai-poised-to-change-the-way-cpas-work/ ↩