Development & Tech
Can your evaluator tell when AI-optimized code is actually good enough?
Before launching an automated search, define the baseline, score, hard constraints, stopping rule, and human who owns the release decision.
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Evaluation
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Evaluation
This tag gathers mini classes around one specific topic. Start with the newest post, then use categories and related reading for context.
AI Trends & Industry
Can You Trust an AI Research Report Just Because It Has Citations?
Deep-research AI can cite sources, but citations are not evidence by themselves. Before using the output, separate official sources, research or media, community discussion, and unknown leads.
Workflow Automation
Before AI Answers Company Numbers, Fix the Source of Truth
Anthropic says Claude now handles most internal analytics questions, but the key is not simply a smarter model. Teams first need fixed data sources, metric definitions, query steps, and review rules.
AI Trends & Industry
Before AI Judges Age, Ask Who Can Overrule It
The UK facial age estimation case shows why high-risk AI needs human override, appeal, and pause rules before model accuracy becomes the focus.
AI Trends & Industry
When AI Adoption Feels Too Fast, Start with Three Backlash Signals
People can use AI and still worry it is moving too quickly. Before speeding up adoption, check control, personal-data risk, and recovery paths, then decide which tasks can advance and which should slow down first.
AI Tools & Apps
AI memory is not better just because it remembers more
AI memory can reduce repeated setup, but it can also bring stale context into new tasks. Use green, yellow, and red labels to decide what stays, what needs confirmation, and what should pause before important judgment.
Workflow Automation
When the AI Button Goes Gray, the Work Should Not Stop With It
An AI outage should slow a workflow, not erase its source material or strand the next person. Define the human handoff, pause point, and minimum deliverable before the button goes gray.
AI Trends & Industry
AI Content Labels Will Not Save Your Time; Your Entry Points Matter More
AI labels give readers clues, but they do not reduce attention cost by themselves. To see less low-quality AI content, clean up the entry points where sources, summaries, and recommendations enter your workflow.
Development & Tech
Before Feeding Bad Data to AI, Do Not Just Label It “False”
Bad examples, outdated policies, and counterexamples are not safe just because you add “do not believe this.” Decide the risk first, then add labels, filtering, tests, and output checks.