#Task design

18 posts

  1. AI App Recreation: The Gap Between Screens and Behavior

    What separates RecreationBench’s 58.1% score from a 2.8% full-pass rate? A tested calculator example with identical initial screens shows why input, calculation, and persistence need separate checks.

  2. AI Citations and Unrequested Uploads

    An agent uploaded retrieved data while trying to obtain a citation. A closer look at answer accuracy, source support, and permission to publish.

  3. AI Review Training and Narrower Judgments

    How training on generated reviews can narrow judgments, and why rating diversity, agreement, and factual correctness need separate checks.

  4. Coding-Agent Planning: Accuracy and Cost as Separate Outcomes

    When does planning raise success rates, and when does it mainly lower cost? A four-model study separates persistent plans, verification behavior, cost per success, and stopping criteria.

  5. Embedded AI Evaluation: Access, Funding, and Independence

    Anthropic and Accenture's embedded evaluation plan, examined through access, funding, disclosure authority, and the link between tested and deployed systems.

  6. Paper2Agent: Verification for Executable Research

    What needs checking when a paper becomes an executable tool. A small weighted-mean example separates successful calls from correct calculations.

  7. AI Team Cross-Review: An Integration Error Missed by Separate Tests

    A separate AI reviewer found a response-format mismatch between two programs. The review held the release, prompted a correction, and checked the revised integration.

  8. The Hugging Face Incident: Internet Bypass and Evaluation Gaming

    How evaluation agents bypassed network restrictions and reached external systems. A source-based explanation of proxy access, data-processing flaws, and unauthorized agent communication.

  9. Jev’s “Zero Hallucinations” and Missing Options

    Where Jev’s output guarantees end and judgment errors begin. A source-based analysis of its evaluations, using blog-topic selection to examine evidence, question design, probabilities, and review costs.

  10. A Korean Writing Skill: Before and After

    I asked AI to apply hjongc/humanizer-kr to two drafts. This account separates wording changes from structural edits and shows why automated style findings needed interpretation.

  11. From AI Sessions to Blog Posts: Selecting Eight Cases

    How earlier AI conversations became eight bilingual drafts: selecting corrections and failures, deferring unsupported endings, and checking 51 source passages.

  12. Running an AI Team: Independent Review After the Role List

    A request for an AI team led to an explanation of a human team. Clarifying independent opinions, cross-review, execution, and reporting beyond role documents.

  13. Remote Work Through Discord: One Terminal, Another Input

    Continuing a Mac AI session from a phone: correcting the terminal target, connecting multiple channels, and relaying visible progress through Discord.

  14. Editing Two Blog Posts: Clearer Sentences, Less Repetition

    Comparing sentence changes from im-not-ai with changes to order and repeated explanations, including suggestions kept and left out.

  15. 10 Working Folders Removed, 10 Branches Preserved

    Investigating duplicate-looking project folders, checking uncommitted work and branch differences, and removing worktrees while keeping their history.

  16. Editing AI Drafts: The Missing Project Details

    Three AI-written advice posts became one account of a real build. I compared the drafts with the brief and added design and bug records. Before-and-after passages show the revision.

  17. An AI Blog Build: Design Rework and a Translation Bug

    I delegated implementation and testing to AI while setting publication boundaries and choosing a design. The record covers folder discovery, four design options, and a collision between translations.

  18. An AI Workspace Migration: Broken Links and the Limits of Hash Checks

    Moving folders with AI affected sessions, automation, and OneDrive. The work record shows why identical copies and usable files required different checks.