Part Six

What to avoid.

Five failure modes account for most failed small-business AI projects:

1. Building a general-purpose assistant first. Pick one workflow, ship it, learn from it. General assistants take 6 months to work reliably; specific workflows take 3 weeks.

2. Skipping the cost cap. Every workflow gets a per-workflow monthly USD cap in LiteLLM. Skip this and you’ll wake up to a $2,000 API bill.

3. Trusting LLM output for classification. Use deterministic rules for classification wherever possible. Reserve the LLM for drafting and reasoning. This is the pattern behind Hedgi.

4. No human in the loop for consequential actions. Every workflow that writes to a client-facing system (email, invoice, contract) has a human sign-off before the write. The workflow drafts; the human approves.

5. Ignoring the audit trail. Every LLM call is logged in LangFuse. Every write is logged in your workflow log. If you can’t answer “what did the agent do at 3:07pm last Thursday” you cannot deploy this in a business.