--- title: "Vision" canonical: "https://current.tinyfish.ai/issue/26/vision" publication: "TinyFish" publisher: "TinyFish" language: "en-US" guide: "https://current.tinyfish.ai/llms.txt" permalink: "https://current.tinyfish.ai/issue/26/vision" issue: 26 section: "vision" description: "Where human-AI collaboration is heading" authors: ["Nora Kaplan"] published: 2026-04-27 updated: 2026-04-23 articles: 11 --- # 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 26 — Vision Where human-AI collaboration is heading ### The Core Parallel - [The Consequences Nobody Designed For]() — By [Nora Kaplan]() · Published 2026-04-22 · Format: The Core Parallel In the fall of 1913, Ford's engineers divided chassis assembly into 45 separate operations and watched throughput soar. They hadn't even settled on a name for what they'd built. What they also hadn't anticipated: a set of consequences that would take decades to fully surface. What happens to craft, to quality, to accountability itself when no single person can see the finished product? ### Two Implications - [The Foreman Problem]() — By [Nora Kaplan]() · Published 2026-04-22 · Format: Two Implications Engineers at top companies have stopped writing code. Their new job is supervising agents that write it for them, a role that borrows from people management, tool configuration, and air traffic control without mapping cleanly to any of them. We've spent centuries building institutional scaffolding for managing humans. For governing entities you own but don't fully control, we have almost nothing. The role doesn't even have a name yet. It probably needs one. - [How to Divide What You Haven't Done]() — By [Nora Kaplan]() · Published 2026-04-22 · Format: Two Implications Before you can supervise an agent team, someone has to decide how to split the work. This decomposition — scoping tasks so autonomous agents don't collide, duplicate, or silently corrupt each other's output — is the invisible skill that separates spectacular multi-agent performance from spectacular multi-agent failure. It demands deep familiarity with the work being divided. And agents are starting to make that familiarity unnecessary. ### The Orchestrator - [The Engineer Who Escaped QA and Ended Up Right Back in It]() — Published 2026-04-22 *Tomás Ferreira is not a real person. He's a composite, assembled from practitioner interviews, employment data, and the lived details that surface when you read enough first-person accounts of engineers navigating the agent transition. We gave him a name, a backstory, and a coffee order (cortado, oat milk, no sugar) because structural shifts are easier to think about when they have a face. Everything he describes is grounded in documented trends. The opinions are his own, insofar as a fictional person can have opinions.* ### The Speed Signal - [Knowledge Work Is Being Decomposed Faster Than Anyone Expected. That's the Good News and the Warning.]() — Published 2026-04-22 Multi-agent architectures on the Databricks platform grew 327% in under four months. The dominant pattern: a supervisor agent breaking goals into sub-tasks for specialized workers. Organizations already knew how to decompose knowledge work. They were just waiting for the primitive. ### Further Reading - **Inside the AI Index: 12 Takeaways from the 2026 Report** — [Source]() — Published 2026-04-22 The authoritative annual snapshot. This year, capability leaps and workforce displacement data finally landed in the same report. - **Agent Orchestration: 10 Things That Matter in AI Right Now** — [Source]() — Published 2026-04-22 MIT Tech Review frames multi-agent coordination as the assembly line for white-collar work. The analogy is more precise than it first sounds. - **The Emerging Agentic Enterprise** — [Source]() — Published 2026-04-22 MIT Sloan and BCG land on a governance framing worth sitting with: agents are "owned but not controlled." No existing management model handles that cleanly. - **Redefining the Future of Software Engineering** — [Source]() — Published 2026-04-22 A survey of 300 engineering executives maps the gap between agentic AI ambition and actual adoption. Engineering is the canary here; the restructuring won't stop at code. - **Chinese Tech Workers Are Starting to Train Their AI Doubles — and Pushing Back** — [Source]() — Published 2026-04-22 What happens when workers are asked to decompose their own expertise into replicable skills. The sabotage tools that went viral tell you something the productivity metrics won't. - **The Agentic Web** — [Source]() — Published 2026-04-22 A practitioner traces the protocol shift redesigning the web for agent traffic first, human browsers second. Quietly one of the most consequential architectural questions in play. ## Other sections in Issue 26 - [Daily Brief]() - [Market Pulse]() - [Foundations]() - [Practitioner's Corner]() - [Echoes]() ## More - [Publication guide]() - [Issue archive]()