Arifa Dev Diary -- AI Issue Reporting, Accessibility, and Contextual Actions

title

date

2026-05-26

author

pmutua

The Hook

In this update, we've introduced significant enhancements to Arifa, focusing on user experience, accessibility, and contextual intelligence. Notably, we've added an AI issue reporting system, established a core accessibility baseline, and introduced contextual actions to enhance user engagement.

Context

Arifa is an AI-powered news aggregation, analysis, and distribution platform designed for Kenya and global tech & science news. Our mission is to provide a comprehensive, accessible, and engaging news experience. This update is part of our ongoing effort to improve the platform's usability and value proposition for our users.

What Changed

AI Issue Reporting

We've added a feature for users to report issues with AI-generated content. This includes inaccuracies, misleading information, inappropriate content, outdated information, or other issues. The reporting mechanism is accessible from each piece of AI-generated content and allows users to provide details about the issue they're reporting.

export async function insertAiReport(
  db: DrizzleD1Database<typeof schema>,
  data: {
    contentType: string;
    contentId?: string | null;
    category: string;
    details?: string | null;
    userId?: string | null;
    ip?: string | null;
  },
) {
  // Implementation details for inserting an AI report into the database
}

Accessibility Baseline

To ensure Arifa is usable by everyone, we've established a core accessibility baseline. This includes semantic HTML for proper document structure, keyboard navigation support, and adherence to WCAG 2.2 AA guidelines. We've also integrated eslint-plugin-jsx-a11y to enforce accessibility rules in our codebase.

module.exports = {
  // ... other configurations ...
  plugins: {
    '@typescript-eslint': tsPlugin,
    'jsx-a11y': jsxA11y,
  },
  // ... other configurations ...
};

Contextual Actions

We've introduced contextual actions to provide users with relevant next steps based on the content they're interacting with. This includes asking AI about an article, viewing more articles on a topic, or exploring connections between stories.

export function renderArticleActions(config: ArticleActionConfig): string {
  const actions: string[] = [];

  // Ask AI about this article
  actions.push(
    actionButton(
      `/dashboard/chat?context=article&id=${encodeURIComponent(config.articleId)}`,
      'M8 10h.01M12 10h.01M16 10h.01M9 16H5a2 2 0 01-2-2V6a2 2 0 012-2h14a2 2 0 012 2v8a2 2 0 01-2 2h-5l-5 5v-5z',
      'Ask AI about this',
      { ariaLabel: 'Ask AI about this article' },
    ),
  );

  // ... other action implementations ...
}

Challenges

One of the challenges we faced was ensuring that our accessibility features were comprehensive and effective. This involved extensive testing and iteration to meet the WCAG 2.2 AA standards. Additionally, integrating the AI issue reporting system required careful consideration of user privacy and data handling practices.

What I Learned

Accessibility is foundational: Ensuring accessibility is not just about compliance; it's about providing a better experience for all users.
Contextual actions enhance engagement: By providing relevant next steps, we can increase user engagement and make the platform more valuable to our users.
AI issue reporting is crucial for trust: Allowing users to report issues with AI-generated content helps build trust in the platform and improves the overall quality of the content.

What's Next

Our next steps include further enhancing the accessibility features, expanding the contextual actions to more areas of the platform, and refining the AI issue reporting system based on user feedback. We're committed to continuously improving Arifa to make it the best possible experience for our users.

sequenceDiagram
    participant User as "End User"
    participant Arifa as "Arifa Platform"
    participant AI as "AI Engine"

    Note over User,Arifa: User interacts with AI-generated content
    User->>Arifa: Reports issue with AI content
    Arifa->>AI: Sends report to AI engine for review
    AI->>Arifa: Processes report and updates content accordingly
    Arifa->>User: Notifies user of changes or actions taken

    Note over User,Arifa: User engages with contextual actions
    User->>Arifa: Requests more information or actions related to content
    Arifa->>AI: Requests relevant data or insights from AI engine
    AI->>Arifa: Provides data or insights
    Arifa->>User: Presents user with contextual actions or information

This update marks a significant step forward for Arifa, enhancing both the user experience and the platform's commitment to accessibility and transparency. As we continue to evolve and improve, we remain focused on our mission to provide the best possible news experience for our users.

Git Provenance

All commits are SSH-signed (Ed25519) and show a Verified badge on GitHub. The source repository is private — commit URLs are not publicly accessible.

Commit	Date	Message	Verified
`df031ba`	2026-05-25 21:22 +03:00	feat(api): add AI issue reporting and correction workflow (closes #51)	✓
`2c3c85e`	2026-05-25 21:29 +03:00	feat(web): establish core-journey accessibility baseline (closes #53)	✓
`be490bb`	2026-05-25 21:42 +03:00	feat(web): add responsive split-view article inspector (closes #55)	✓
`76f075f`	2026-05-25 21:49 +03:00	feat(web): add contextual intelligence actions and trust copy (closes #56)	✓
`a5ffd4c`	2026-05-25 21:56 +03:00	fix(web): add explanatory comments to all empty catch blocks (closes #45)	✓

pmutua/2026-05-26-arifa-dev-diary-ai-issue-reporting-accessibility-and-context-a5ffd4c.md

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