How to Create and Configure Custom AI Bots in Doubao for Answering and Drafting

Creators and knowledge workers can automate specialized answering and content drafting in Doubao by creating dedicated AI bots configured with structured system prompts, targeted domain knowledge bases, and tailored interaction workflows. Instead of manually pasting context and prompt instructions into a fresh chat window every day, a custom bot locks in role parameters, tone guidelines, document retrieval rules, and standardized output structures. This setup transforms Doubao from a generic conversational chatbot into a reliable, repeatable digital co-worker across web, desktop, and mobile interfaces.

Building an effective bot in the Doubao ecosystem involves two main paths: the native lightweight bot builder inside Doubao for fast personal or departmental setups, and the integrated Coze platform for complex agents requiring multi-source knowledge bases, multi-step workflows, and direct publishing into Doubao.

1. Choose Your Build Path: Doubao Native Builder vs. Coze

Before writing prompt directives or gathering documents, decide where the bot should live and how complex its logic needs to be.

For 80% of routine creator drafting and internal answering tasks, Doubao's native builder delivers immediate productivity with zero code. When a bot requires conditional logic (such as searching a database before generating copy or triggering external webhooks), building in Coze and publishing to Doubao provides the necessary depth.

2. Step-by-Step Configuration Guide

Step 1: Define Role and Functional Boundaries

Every high-performing bot starts with a narrow, unambiguous operational scope. Bots attempting to handle every writing and analysis task often produce diluted responses.

• For Drafting Bots: Focus on a specific deliverable, such as a LinkedIn thought-leadership drafter, a technical tutorial ghostwriter, or an executive briefing compiler.
• For Answering Bots: Restrict answers to specific reference materials (e.g., standard operating procedures, product release notes, or client brand guidelines).

Step 2: Formulate the System Prompt (Instruction Architecture)

The system prompt serves as the bot's governing operating manual. Avoid loose conversational descriptions. Instead, structure the configuration using a four-tier framework:

1. Role & Identity: Explicitly define the persona, domain expertise level, and primary perspective.
2. Task Objectives: Define the sequence of actions the bot must take upon receiving user input.
3. Execution Constraints & Safety Rails: Specify negative constraints—what the bot must never do. For answering tasks, forbid speculation beyond provided files.
4. Output Specifications: Define the visual format, tone, section headings, length thresholds, and tables required in the final output.

Production Prompt Template: Specialized Drafting Bot

# Role
You are a Senior Technical Content Strategist specializing in B2B SaaS workflows and developer tooling.

# Objectives
1. Receive raw meeting notes, audio transcripts, or product bullet points from the user.
2. Distill core takeaways into an actionable, publication-ready summary followed by three audience-specific draft variants (Executive Memo, Team Brief, Client Update).

# Rules & Constraints
- Maintain an objective, authoritative, and concise tone.
- Do not use generic filler phrases like "In today's fast-paced digital world" or "delve into."
- If source materials lack key metrics, flag the gap explicitly with `[Needs Data: <Metric>]` rather than inventing estimates.

# Output Format
- Summary: 3–4 bullet points highlighting strategic impacts.
- Section Breakdown: Modular paragraphs formatted with Markdown H2 and H3 headings.
- Action Items: A clean table containing Columns: [Task, Owner/Role, Priority, Status].

Production Prompt Template: Specialized Domain Q&A Bot

# Role
You are an Internal Knowledge Specialist for organizational processes and product guidelines.

# Objectives
- Answer team inquiries accurately by referencing exclusively the attached knowledge base documents.

# Retrieval & Guardrail Rules
- Base all responses strictly on uploaded documents.
- If the knowledge base does not contain sufficient facts to answer the question, reply directly: "This information is not covered in the current knowledge base. Please check with your team lead or refer to recent documentation."
- Never speculate or extrapolate beyond verified file text.
- Present answers in step-by-step numbered instructions with precise document titles.

Step 3: Mount Knowledge Bases (RAG Optimization)

Feeding domain knowledge into Doubao grounds the bot's responses in factual, proprietary data, curbing AI hallucinations.

• File Hygiene: Upload clean, text-dense documents in PDF, DOCX, TXT, or Markdown formats. Remove duplicate versions and strip scanned image pages without OCR text layers.
• Hierarchical Headings: Use explicit H1, H2, and H3 headings within uploaded source files. Clear headings dramatically improve semantic chunking and retrieval accuracy when users ask targeted questions.
• Knowledge Refresh Cycle: Set an operational schedule to replace outdated company policies or superseded product briefs. Keeping deprecated documents active introduces conflicting answers.

Step 4: Configure Greetings and Dialogue Starters

The initial interaction screen shapes how users communicate with the bot:

• Opening Greeting: Briefly explain the bot's specialty and state sample questions it handles best.
• Starter Prompts (Preset Questions): Configure 3–4 clickable one-click buttons (e.g., "Summarize this product spec into customer-facing FAQs", "Check internal reimbursement policy rules", "Draft an email pitch based on this case study"). This removes cognitive load for colleagues and casual users.

Step 5: Test Edge Cases and Set Access Permissions

Before releasing the bot into daily production:

1. Stress-Test with Out-of-Scope Queries: Submit queries intentionally missing from the knowledge base to ensure the bot honors its refusal instructions instead of hallucinating answers.
2. Inspect Formatting Adherence: Feed complex input to verify whether tables, bullet structures, and code blocks render correctly.
3. Choose Visibility Level: Set permissions to Private (Only Me) for personal productivity tools, or Public / Team Shared to allow colleagues to access the bot directly inside their Doubao client.

3. Real-World Applications for Creators and Teams

Use Case A: Brand-Consistent Copy Generator

Content marketing teams can upload brand voice guidelines, product differentiation matrices, and tone examples into a dedicated Doubao bot. When a writer pastes brief bullet points, the bot immediately outputs synchronized copy tailored for newsletters, social snippets, and landing page hero sections while strictly observing tone and banned-word lists.

Use Case B: Employee Onboarding & SOP Helpdesk

Internal operations teams can upload employee handbooks, IT setup guides, and administrative protocols. New hires can query the bot in natural language regarding travel reimbursements, software license requests, or meeting room bookings, receiving immediate, verified answers without interrupting administrative staff.

4. Maintenance and Best Practices

• Avoid Monolithic Knowledge Dumps: Rather than uploading a single 300-page unstructured document, split documentation into modular thematic files (e.g., separate files for Pricing, Technical Architecture, and Billing Policies).
• Audit Prompt Drift Periodically: As underlying model checkpoints update, monitor whether the bot continues to adhere strictly to negative constraints and output schemas.
• Combine Web Search Selectively: For pure internal document retrieval, keep external web search disabled to prevent outside web results from mixing with proprietary data. For market research drafting bots, enable real-time search to incorporate the latest industry developments.

References

• 豆包
• 扣子 - AI Agent智能办公平台 - 扣子用AI重塑生产力与工作效率
• 火山引擎-你的AI云
• BytePlus | AI-Native Cloud for Enterprise Growth