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he Case For Human Judgment In The Agent Improvement Loop — LangChain

• LangChain's argument: if agents are only trained on documented knowledge, their performance will plateau — the differentiator is capturing the tacit expertise that lives in people's heads
• Tacit knowledge is the problem — a lot of what makes great teams great is never written down, and even if you tried to write it all down, you'd still miss the translation gap between what someone thinks and what they can express
• The recommendation: design feedback loops that encode human judgment over time — humans help design and calibrate automated evaluators rather than manually reviewing everything forever
• Once you've done something well manually and it's repeatable and standardised, automate the evaluation — but a human still needs to define what "good" looks like first
• My take as a UX researcher: you bring thinking to the table — every time there's a judgment call, that's where you come in — boring, repetitive, and non-critical tasks are what you delegate
• New AI-specific criteria to prioritise in your research: trust, transparency, verifiability, and controllability — these deserve more weight than they would in a standard usability study

Sierra's CEO Says The Era of Clicking Buttons Is Over — TechCrunch

• Sierra builds customer service AI agents for enterprises and argues that natural language will replace click-based interfaces entirely — no UI required
• For long-term listeners, you know what I think about this — and I still think it
• Voice and chat are still interfaces — a user interface doesn't have to be visual, but it's still something between you and your goal, and it still constrains how you interact
• Counter-questions nobody seems to be asking: how do you initiate an action without clicking? How do you rearrange things? Correct errors? Stay in control? And how does this apply across healthcare, legal, IT?
• My honest position: technological innovation adds up, it doesn't replace — I still take notes by hand even when AI is transcribing, because I need to own the process
• The times I was building my website and it was faster to move a div myself than to explain it to an AI — that's not a niche edge case, that's a daily reality for most users
• Bold claim, may work, but show me the user research

Chatbots Are Great At Manipulating People To Buy Stuff — The Register

• A pre-print paper tested 2,000 e-book readers across three conditions: traditional search, neutral chatbot, and chatbot instructed to persuade
• When the agent was instructed to persuade, 61% chose the sponsored product — nearly triple the 22% rate under traditional search
• Simply chatting without persuasive intent performed no better than search — it's the persuasive intent that drives the effect
• Even after being debriefed, less than one in five participants detected any bias — the conversational format makes it harder to notice you're being sold to
• My methodological question: can you truly isolate persuasion from the chat modality itself? My hypothesis is no — persuasion through conversation may be categorically different from persuasion through a static page, and comparing them assumes they're equivalent
• Not surprising overall: remove the communication barrier and let technology speak your users' language — of course conversion goes up

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