It turns out the problem wasn't the AI.
On day 2 of our Vibe Accounting in Public project, we put our new AI agent to its first test: creating a basic revenue recognition automation rule. I recorded the raw, unedited first run, and as you'll see in the video, its first output was incomplete.
But the reason why is the most important lesson for anyone working with AI. It wasn't an "AI failure." The agent correctly and logically processed the ambiguous prompt I gave it.
This highlights a new dynamic: AI doesn't always guess or fill in gaps like a human might. My initial prompt was intentionally general, and the AI returned a logical, general result. But when I provided one sentence of specific context, it delivered the perfect automation instantly.
This proves the bottleneck for AI accuracy isn't the model's intelligence - it's the clarity of the human expert directing it. The future of accounting isn't about finding an AI that can read our minds. It's about training accountants to become precise, expert directors of AI agents.
(A quick note on the setup: We're interfacing directly with the agent's code output for now. Our focus for now is on nailing the core logic, not the UI.)
So yes, this was a massive success. It proved our agent is incredibly responsive to expert direction. The real question is: are we ready to be that precise?
Next, we'll raise the stakes with much more complex revenue recognition.
Read our other Vibe Accounting in Public posts:
Day 19 - Complete Stripe Order-to-Cash and Revenue Recognition Workflow in 5 Minutes
Day 18 - Determining When FX Calculations Should Occur
Day 17 - Instantly Customizing a Revenue Report For a 4-4-5 Retail Calendar
Day 15 - The Difference Between a Cool AI Demo and a System You Can Bet Your Audit On
Day 14 - When AI Finds a Stripe Data Problem We Didn't Even Ask It To Look For
Day 13 - From Reading a Chart of Accounts to Deciphering Financial Philosophy
Day 12 - ROI Analysis: AI vs Manual Revenue Recognition
Day 11 - An ASC 606 Compliance Review in 60 Seconds
Day 10 - Shattering the Accounting Software Language Barrier
Day 9 - Can Our AI Actually Reconcile Accounts Receivable?
Day 8 - Translating Complex Automation Code Into a Clear, Visual Workflow
Day 7 - Tokenomics: the Hidden Line Item in Your AI Strategy
Day 6 - Our AI Accounting Agent Leveled Up From a Tool to a Teammate 🤝
Day 5 - When the AI Accountant Starts to Act Like an Annoying Intern
Day 4 - Generating a Perfect Deferred Revenue Waterfall Report
Day 3 - Our AI Accountant Just Became Its Own Technical Writer
Day 2 - Creating a Basic Revenue Recognition Automation Rule:
Day 1 - Can AI Be Trusted With Automating Complex Accounting?
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