--- title: "Practitioner's Corner" canonical: "https://current.tinyfish.ai/issue/41/practitioners-corner" publication: "TinyFish" publisher: "TinyFish" language: "en-US" guide: "https://current.tinyfish.ai/llms.txt" permalink: "https://current.tinyfish.ai/issue/41/practitioners-corner" issue: 41 section: "practitioners-corner" description: "Lessons from the field—what we see building at scale" authors: ["Sable Whitford","Sevda Polat"] published: 2026-08-10 updated: 2026-08-06 articles: 13 --- # TinyFish > CURRENT is a journal about AI agents in production, for the engineering and product leaders who have to make them work. Drawing on experience building enterprise web agents, it explains why the demo succeeded and the deployment didn't, and what that means for choosing vendors, briefing the board, and avoiding mistakes others have already made. [Read on the website]() ## Issue 41 — Practitioner's Corner Lessons from the field—what we see building at scale ### Deliberate Constraint - [Nobody Ever Blamed the Rate Limiter]() — By [Sable Whitford]() · Published 2026-08-05 · Format: Deliberate Constraint Most agents in production stop somewhere around ten steps and hand the work to a person. Easy to read that as the models running out of road. But we throttle a producer when the consumer downstream can't keep up — that's backpressure, and I have never once heard anyone look at a rate limiter and conclude the upstream service was incompetent. Ten steps starts to look like a measurement of the human: how much consequence one person can still hold in their head and refuse. Which puts the ceiling on agent deployment somewhere no model release measures. ### Builder Profile - [Melissa Pan Changed Instruments Twice, and What She Could See Changed With Them]() — By [Sable Whitford]() · Published 2026-08-05 · Format: Builder Profile I carried a pager for years attached to monitoring that rolled everything into averages at write time. Any question I hadn't thought to ask in advance wasn't hard to answer later. It was dead. The number was thrown out at ingest. ### Reliability Owner - [The Person Who Decides How Many Steps Your Agent Gets]() — Published 2026-08-05 *Dag Halvorsen does not exist. He is a composite, assembled from peer-reviewed interview data, survey findings, and the observable patterns of how enterprise teams actually operate agent systems in production. The pressures he describes are real. The person is not. If you find yourself nodding along anyway, that's the point.* ### Orthogonal Metrics - [It Did the Job Perfectly and Leaked Anyway]() — By [Sable Whitford]() · Published 2026-08-05 Ask an agent to turn internal support tickets, a company wiki, and product docs into public help-center articles. In [a joint evaluation](https://arxiv.org/html/2606.17114v1) by the Korean and Singaporean AI safety institutes, one model scored 100% on correctness in that scenario and 58.3% on safety. Nobody attacked it; the request was ordinary. ### Reading List - **Characterizing Agents in Production** — [Source]() — Published 2026-08-05 Survey of 306 practitioners reveals production agents are deliberately kept short-leashed, most running ten steps or fewer before human review. Capability exists; trust doesn't. - **The 2025 AI Agent Index** — [Source]() — Published 2026-08-05 Audit of 30 deployed agents finds capability benchmarks reported far more often than safety evaluations. What gets measured publicly reflects marketing priorities, not operational risk. - **An Evaluation of Data Leakage Risks in Tool-Using LLM Agents in Realistic Scenarios** — [Source]() — Published 2026-08-05 Agents completed tasks correctly while mishandling every piece of sensitive data involved. Task-success metrics can report perfect scores on runs that would constitute compliance failures. - **Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity** — [Source]() — Published 2026-08-05 Randomized trial found AI tools slowed experienced developers by 19 percent, while those same developers believed they were faster. Perceived uplift and actual uplift moved in opposite directions. - **We Are Changing Our Developer Productivity Experiment Design** — [Source]() — Published 2026-08-05 METR's follow-up collapsed because developers refused to work without AI, making the control condition unmeasurable. Adoption has outpaced the ability to determine whether the tools help. ### Past Articles - [A Queue Is Not a Shelf]() — By [Sevda Polat]() · Published 2026-07-30 · Format: The Two Clocks Capacity planning rests on a claim nobody states out loud: that a queue is a shelf, and work comes off it weighing what it weighed going on. Often it doesn't. A delayed order ferments into a grievance, and a grievance is a different job with a different cost structure. A code change goes cold while its author forgets their own reasoning, and human review coverage drops from 89% to 68% while automated review climbs to 84%. - [Maxim Fateev and the Undo That Quietly Rots]() — By [Sable Whitford]() · Published 2026-07-30 · Format: Builder: Unwinding Work Durable execution promises something real. Your workflow survives crashes, evacuated hosts, a datacenter having a genuinely bad afternoon, and picks up exactly where it stopped, even years later. Now read that with an ops brain switched on. It covers your program. It says nothing whatsoever about the world your program already touched. - [Pierre Laperdrix and the Web That Learned to See]() — By [Sable Whitford]() · Published 2026-07-23 · Format: Builder Profile Your agent solved the CAPTCHA, bypassed the bot gate, completed the task. A CNRS research team just showed that none of it mattered. Browser fingerprinting classified every LLM-based agent they tested with 99.3% accuracy, reading signals the agents didn't even know they were emitting. Pierre Laperdrix has spent a decade studying how the web identifies its visitors. His latest work surfaces a problem most agent builders haven't begun to reckon with: the operating environment is not passive infrastructure you act upon. It is learning to see you. - [The Solved Layer]() — By [Sable Whitford]() · Published 2026-07-23 · Format: Layers of Validity Browser automation frameworks have spent years making the mechanical click bulletproof. Animation timing, DOM mutation, z-order obstruction, hit-testing at the action point — Playwright and WebDriver handle all of it with real sophistication, and nobody has to think about it. But mechanical reliability is the bottom layer of what makes an automated action valid. It is also the only layer anyone has actually built. Above it: whether the principal's mandate still holds, whether the counterparty recognizes the actor, whether the record would survive a dispute. Payment networks are building answers to those questions. Almost nobody else is. ## Other sections in Issue 41 - [Daily Brief]() - [Market Pulse]() - [Foundations]() - [Echoes]() - [Vision]() ## More - [Publication guide]() - [Issue archive]()