Summary of "Assistente do SEI IA e Engenharia de Prompts"

The video titled "Assistente do SEI IA e Engenharia de Prompts" is a comprehensive workshop focused on the use, development, and best practices of an AI assistant integrated with the SEI (Electronic Information System) used at Anatel, a Brazilian regulatory agency. The main technological concepts, product features, and Prompt Engineering techniques covered include:

Key Technological Concepts and Product Features

CIA (Assistente do SEI IA):
- An AI assistant integrated within SEI to facilitate interaction with documents and processes, respecting business rules and access controls.
- Uses GPT-4.1 and a "reflection" model (O4 mini) for more precise, context-aware responses.
- Does not search the web online yet; a web search feature and personalized GPT agents are planned for future releases.
- Designed for corporate and secure use, avoiding internet-based AI tools for sensitive or restricted content to prevent data leaks and unauthorized use of proprietary data.
User Interface and Features:
- Assistant located at the bottom right corner of the SEI editor.
- Includes chat interface, icebreakers (predefined simple prompts), favorites, prompt galleries (shared and personal), and topic management (archiving/unarchiving).
- Supports citation of documents and processes with context limits (up to 1 million tokens).
- Incorporates vector search technology (HAG - coarse search sieve) to locate relevant document excerpts before AI processing.
Security and Compliance:
- Emphasizes strict data privacy and contractual protections.
- Warns against using free internet AI tools for corporate content due to data usage policies and security risks.

Prompt Engineering and Usage Guidelines

Prompt Definition and Importance:
- A prompt is any input message to the AI, from simple greetings to complex instructions.
- Effective Prompt Engineering is crucial to get accurate, relevant, and safe AI outputs.
Prompt Types and Techniques:
- Zero-shot: Asking questions without examples.
- One-shot: Providing one example to guide the AI.
- Few-shot: Providing multiple examples.
- Chain of Thought: Asking AI to think step-by-step or reason through a problem explicitly.
- Persona-based prompts: Assigning a role or expertise to the AI to tailor responses (e.g., productivity coach, tax lawyer).
- Task decomposition: Breaking complex tasks into smaller subtasks to improve accuracy.
- Self-reflection/self-criticism: Asking AI to evaluate its own responses for quality and correctness.
- Hypothetical search: Creating fictitious references or theses to guide research in official databases.
Prompt Writing Best Practices:
- Start simple and evolve prompts gradually based on feedback.
- Assign a clear persona with role, expertise, and context.
- Provide detailed context, target audience, and clear objectives.
- Specify restrictions explicitly (e.g., "do not invent," "base exclusively on referenced documents").
- Use imperative or infinitive verbs for clarity and directness.
- Include positive and negative examples to optimize AI responses.
- Specify response format, length, tone, and style (Markdown formatting recommended).
- Avoid ambiguity by using synonyms and clear terms (e.g., distinguish between listing and transcribing).
- Use Markdown and XML-like delimiters to structure outputs clearly, especially for complex prompts.
- Regularly test and refine prompts based on results.
Advanced Prompt Templates:
- Provided in the manual and ready-made gallery, including complex legal and administrative document analysis.
- Examples include detailed administrative appeal analysis with explicit instructions on format, content, and style.
- Use of tables, bold/italic formatting, and structured sections to improve readability and precision.

Practical Applications and Examples

Summarizing texts with topic limits and emojis for social media sharing.
Translating texts into multiple languages (French, English, Spanish).
Programming assistance (Python, SQL, Excel formulas).
Legal document analysis, including citation and cross-referencing of reports and decisions.
Risk analysis from news clippings, associating news items with institutional risks, generating tables with justifications.
Persona-driven debates simulating opposing roles (e.g., lawyer vs. prosecutor) to refine arguments and responses.

Challenges and Limitations

AI is literal and probabilistic, not truly understanding content; it can hallucinate or produce nonsense if prompts are unclear or incomplete.
The AI assistant cannot telepathically guess user intent; specificity is required.
Document size and token limits require breaking large documents into smaller parts.
Managing access rights and ensuring the AI only processes information accessible to the user’s unit.
Avoiding data leaks and ensuring compliance.