SleekView Feedback for AI Engine
AI Engine stores conversations, prompts, and image generations inside WordPress. SleekView Feedback exposes those rows as a sortable, votable board so visitors flag bad answers, editors triage hallucinations, and prompt authors see which templates are actually working.
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From AI Engine logs to a community review board
AI Engine writes every chat, query, completion, and image generation to its own tables inside WordPress. The Discussions screen is helpful for one conversation at a time, but it does not give you a way to see which conversations were great, which ones quietly went off the rails, and which prompts your audience keeps coming back to. With hundreds of chats a day, this matters.
SleekView Feedback reads the meowapps_chats table or the conversations post type, depending on how you have AI Engine set up, and renders one card per conversation. You map the vote column, the status column, and the category column. The result is a board where editors and visitors upvote the answers worth keeping, flag the ones that hallucinated, and propose new prompts the chatbot should learn.
Because votes write back to the AI Engine row, the loop closes. Your prompt engineer can sort prompt templates by score, retire the ones nobody likes, and prioritise the ones earning real attention. The board becomes the public face of a quality program that, before, only lived in admin notes and bug tickets.
Workflow
Plug AI Engine into a feedback board
Pick the AI Engine table
Map vote, status, category
Embed on docs or community
Votes ship back to AI Engine
Sample board
Sample AI Engine conversation board
Comparison
AI Engine Discussions vs SleekView Feedback
AI Engine Discussions
- Discussions screen shows one chat at a time with no vote, no flag, no tagging
- Quality issues stay invisible until a customer emails you about a bad answer
- There is no shared way for editors to upvote the prompts that perform best
- Hallucination triage happens through bug trackers disconnected from the chat row
- Prompt engineers cannot see which templates the audience actually loves
SleekView Feedback
- Render one card per AI Engine conversation with votes, status, and tags
- Upvote writes back to the AI Engine row so prompts can be ranked by score
- Filter the board by bot name, model, page, or any meta key already in use
- Public visitors vote anonymously, editors moderate with their WordPress role
- Embed on docs, community pages, or staff dashboards with one shortcode
Features
What SleekView Feedback gives you for AI Engine
Conversation grade view
Every AI Engine chat row becomes a card. Visitors see the question, the bot, the status, and a vote count. Editors see which conversations are dragging the bot down and which ones are setting a great example, all in one sorted feed.
Hallucination flags inline
Add a Hallucination category and any visitor can flag a bad answer with one click. The flag attaches to the original AI Engine row, so your prompt engineer sees the full context next to the chat instead of in a screenshot.
Prompt suggestion queue
Let visitors propose new prompts or missing answers. They get a category tag, a vote count, and a status pill. Your prompt engineer adopts the top voted suggestions in the next release, and visitors get to see their idea shipped.
Audience
Where the AI Engine board earns its keep
Support chatbot quality
Support teams watch the board to spot conversations where the AI Engine bot quietly gave a wrong answer. Upvoted hallucination flags climb to the top, and the team fixes the underlying prompt before it costs the next refund.
Docs bot improvement
Docs teams use the board to find the questions readers are asking but the bot is missing. High vote prompt requests become the docs roadmap, and the bot improves alongside the underlying documentation pages.
Community prompt vote
Community sites expose the board so users can vote on which prompts they want the bot to learn next. The forum stops being a graveyard of one off questions and becomes a living signal of what the audience needs.
The bigger picture
Why AI Engine needs an open conversation board
AI Engine is one of the most flexible AI plugins on WordPress. It powers chatbots, content tools, image generators, and embeddings on tens of thousands of sites, and every conversation that runs through it is a tiny experiment. The problem is that those experiments are invisible to almost everyone on the team.
The site owner sees a Discussions screen. The prompt engineer sees a config. The visitor sees a chat that either delights or quietly disappoints.
Nobody has a shared view of how the bot is actually doing. A feedback board changes that. It puts AI Engine conversations in front of an audience, lets them vote, and surfaces the conversations that drag the bot down so they can be fixed.
It also surfaces the conversations that go beautifully, so the prompt that produced them can be repeated. Hallucinations stop being a vague worry and become a sorted backlog. Prompt requests stop being scattered comments and become a ranked roadmap.
The bot gets better because the people who use it have a place to say what they want, and the prompt engineer has data to act on. Because the data lives in AI Engine, none of this requires migrating to a new tool. The board is just a clearer window onto information you were already collecting.
Questions
Common questions about SleekView Feedback for AI Engine
Real time. SleekView queries the AI Engine table or post type directly on each page load, so any conversation that AI Engine wrote a moment ago is visible immediately. There is no cron job, no separate database, and no risk of the board falling out of sync with the chat history.
 Yes. Each board is configured per page or per block, so you can filter by bot ID, model, or category and serve different boards on different pages. Support, sales, and docs can each have their own dedicated board on top of the same AI Engine instance.
 SleekView supports upvotes only by default, so there is no downvote button to spam. Combined with per cookie, per user, and per IP rate limits, the board stays honest. You can also restrict voting to logged in users or to a specific WordPress role if you need stricter moderation.
 Use the status column you mapped into the board. Statuses like reviewed, flagged, and resolved write back to the AI Engine row whenever an editor changes them from the board. AI Engine reports and admin filters can use the same column without any custom code.
 Yes. You can wire two views on the same page, one pointed at the AI Engine prompts post type and one pointed at the conversations table. Each board has its own vote and status mapping, and they can share filters such as bot, category, or campaign.
 That is your call. The board only shows rows you authorise, and you can scope it to anonymised excerpts or summary fields rather than full conversation transcripts. Many teams expose only the user question and the bot status, which is enough for voting without leaking personal data.
 Yes. Because the vote count lives in the column you mapped on the AI Engine row, anything that can query that column can use it. AI Engine reports, custom dashboards, and SQL queries all see the same number, so prioritisation is one ORDER BY away.
 No. The view paginates server side and only renders the current page of rows. Cached counts and indexed columns keep queries fast even with hundreds of thousands of conversations. Heavy traffic on AI Engine has no measurable effect on board render time.
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