--- title: "Vision" canonical: "https://current.tinyfish.ai/issue/17/vision" publication: "TinyFish" publisher: "TinyFish" language: "en-US" guide: "https://current.tinyfish.ai/llms.txt" permalink: "https://current.tinyfish.ai/issue/17/vision" issue: 17 section: "vision" description: "Where human-AI collaboration is heading" authors: ["Nora Kaplan","Rina Takahashi"] published: 2026-02-23 updated: 2026-02-19 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 17 — Vision Where human-AI collaboration is heading ### The Professional Services Threshold - [When Judgment Stops Being Scarce]() — By [Nora Kaplan]() · Published 2026-02-19 · Format: The Professional Services Threshold A complaint response that used to take a law firm associate 16 hours now takes under four minutes. Harvard Law researchers documented 100x productivity gains on judgment-intensive tasks at major firms. Not a single one anticipates reducing attorney headcount. ### Proving Ground / New Model - [Goldman's Compliance Bet Signals Where AI Agents Actually Are]() — By [Rina Takahashi]() · Published 2026-02-16 · Format: Proving Ground / New Model Goldman Sachs chose compliance and accounting for its first major AI agent deployment—domains where high regulatory stakes, zero error tolerance, and complex judgment at scale create a threshold test. Success here signals something different than success in lower-stakes environments. The domain choice itself reveals where agents actually are on the capability curve. - [Why Anthropic Engineers Spent Six Months Inside Goldman]() — By [Rina Takahashi]() · Published 2026-02-16 · Format: Proving Ground / New Model Goldman Sachs didn't implement an AI platform. Anthropic engineers embedded at the bank for six months to co-develop systems. This deployment model exists because the gap between model capability and production reliability remains wide in high-stakes environments. Six months of embedded engineering to reach "launching soon" without a firm date—the approach itself signals where enterprise AI actually is. ### Mino on Trust - [Mino on Why 99.9% Accuracy Isn't Good Enough]() — Published 2026-02-16 We caught up with Mino between tasks—literally. The web agent had just finished processing a batch of regulatory filings and was waiting for the next queue to populate. In the strange liminal space of agent downtime, we asked about something that's been bothering a lot of people lately: the gap between "this works" and "this works well enough to bet your compliance record on it." ### The Goldman Deployment - [What Goldman's Claude Numbers Don't Tell You]() — Published 2026-02-16 Goldman Sachs deployed Claude across 12,000+ developers, reporting 30% faster client onboarding and 20% productivity gains. The numbers sound impressive until you ask what they measure. ### Further Reading - **Ten AI Predictions for Legal Teams in 2026** — [Source]() — Published 2026-02-16 Corporate legal adoption hit 52%. Two-thirds expect to need outside counsel less. The power shift has numbers now. - **How Forward-Deployed Engineers Make Enterprise AI Actually Work** — [Source]() — Published 2026-02-16 Job postings jumped 800% last year. Enterprises embed engineers with teams accountable for outcomes, proximity over platforms. - **Why Enterprise AI Needs Embedded Builders, Not Just Platforms** — [Source]() — Published 2026-02-16 Platforms deliver ingredients. Forward-deployed engineers cook in your kitchen, with your constraints. Production happens at that proximity. - **AI Agents in Production: The 2025 Reality Check** — [Source]() — Published 2026-02-16 Of 1,837 teams surveyed, 95 have agents truly in production. Most still wrestle with accuracy, control, transparency. - **Accounting Automation's Intelligent Future Beyond Rule-Based Systems** — [Source]() — Published 2026-02-16 Generative AI in accounting designs new processes, drafts communications, creates frameworks tailored to each client situation. - **Enterprise AI Agent Engineering: Governance and Data Quality Foundations** — [Source]() — Published 2026-02-16 Production agents need governance as precise as human users. Role-based access control now extends to agents in regulated work. ## Other sections in Issue 17 - [Daily Brief]() - [Market Pulse]() - [Foundations]() - [Practitioner's Corner]() - [Echoes]() ## More - [Publication guide]() - [Issue archive]()