# Appearing Productive in The Workplace — No One's Happy - Host: [nooneshappy.com](https://links.thingelstad.xyz/hosts/nooneshappy.com/) - Saved: May 7, 2026 (2026-05-08T03:22:58Z) - Record: https://links.thingelstad.xyz/links/dd6530fd3157/ - JSON: https://links.thingelstad.xyz/links/dd6530fd3157.json ## What Jamie wrote LLM capabilities are pouring into many professions and on the whole I'm bullish about this and think it will be transformational. However, there are disconnects that we need to become culturally attuned to. This article highlights one that we need to gain skill on first. > In any previous era, the quality of a piece of work was a more or less reliable signal of the competence of the person who produced it. A novice essay read like a novice essay; novice code crashed in novice ways. AI has severed that relationship. A novice now produces work that does not betray the novice, because the competence the work reflects is not the novice's competence at all. It is the system's. The person, in the transaction, becomes a kind of conduit, capable of routing the output to a recipient and incapable of evaluating it on the way through. As a recipient of information we need to now perceive that you can have expertise-signal with novice-capability. This was previously not possible. the signal actually looks a bit like a student cheating and giving someone else's work. That isn't the right framing though since it is common to do this while performing a job. People routinely engage with expertise without the domain details. But as a recipient of information we now need to ask two questions: is the information presented of the quality it deserves, and is the person or system providing that capable of the assertion. The article goes on to define how we can test that capability. > Generative AI does well on tasks where feedback is fast, where being approximately right is good enough, where the human remains the final arbiter. Drafting a memo, generating examples, summarizing material the reader could verify if they cared to. The University of Illinois Generative AI guidance [[7](https://nooneshappy.com/article/appearing-productive-in-the-workplace/#ref-7)] and the PLOS Computational Biology "Ten Simple Rules" paper on AI in research [[8](https://nooneshappy.com/article/appearing-productive-in-the-workplace/#ref-8)], among the more careful documents now circulating, list much of this explicitly: **brainstorming, copyediting, reformulating one's own ideas, pattern detection in data one already understands**. Read broadly I think it is critical that we know when we are "playing tennis without a net" as it were. If you are using AI for a task that is not testable, you need to treat that different than one that is testable. Testability of the assertion is key to knowing where you can get leverage. This is the magic unlock with software, because code is testable within limits. And the place where automatic programming still needs expert engineers is the untestable bits. How do you apply this testability to other domains? And then how do you calibrate expertise into the system? Ideally expertise determines ways to make things testable that appear not to be. That is the magic unlock that I find real leverage. The LLM itself can be used to make the untestable output testable. ## Facts - Kind: [Page](https://links.thingelstad.xyz/kinds/page/) ## Appears in - [WT347: Weekly Thing 347 / Scrum, FilamentHound, DO_NOT_TRACK](https://weekly.thingelstad.com/archive/347/), Notable ## Saved the same week - [Hand‑drawn QR codes — Seth Larson](https://links.thingelstad.xyz/links/ed828c2cc661/) (sethmlarson.dev, May 7, 2026) - [When everyone has AI and the company still learns nothing](https://links.thingelstad.xyz/links/9f8b436f5322/) (robert-glaser.de, May 7, 2026) - [Agentic Coding is a Trap | Lars Faye](https://links.thingelstad.xyz/links/2645f23ecf37/) (larsfaye.com, May 7, 2026) - [The Death of Scrum — An Interactive Essay](https://links.thingelstad.xyz/links/c2ea28e92403/) (death-of-scrum.net, May 7, 2026) - [The AWS MCP Server is now generally available | AWS News Blog](https://links.thingelstad.xyz/links/a39fd68faaff/) (aws.amazon.com, May 7, 2026) ## Elsewhere - Wayback Machine: https://web.archive.org/web/*/https://nooneshappy.com/article/appearing-productive-in-the-workplace/