---
title: "Foundations"
canonical: "https://current.tinyfish.ai/issue/10/foundations"
publication: "TinyFish"
publisher: "TinyFish"
language: "en-US"
guide: "https://current.tinyfish.ai/llms.txt"
permalink: "https://current.tinyfish.ai/issue/10/foundations"
issue: 10
section: "foundations"
description: "Conceptual clarity earned from building at scale"
authors: ["Rina Takahashi","Nora Kaplan"]
published: 2026-01-05
updated: 2025-12-31
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](<https://current.tinyfish.ai/issue/10/foundations>)

## Issue 10 — Foundations

Conceptual clarity earned from building at scale

### What Building Teaches Builders

- [Quality Degradation Curves](<https://current.tinyfish.ai/issue/10/foundations/article/7218/markdown>) — By [Rina Takahashi](<https://current.tinyfish.ai/team/25/markdown>) · Published 2025-12-31 · Format: Field Guide

Your hotel pricing extraction ran at 98% success for six months. Then it didn't. Quality rarely breaks all at once—it erodes. Operating web agents across thousands of sites, you start seeing patterns in how that erosion happens. Some automations cliff overnight when sites change. Others drift downward so gradually you don't notice until you're deep in the hole. The shape of degradation reveals infrastructure capability better than any demo. Understanding these curves matters before you're locked into an approach.

### Tools & Techniques

- [When Developers Need to See What's Actually There—The Cookies.txt Browser Extension](<https://current.tinyfish.ai/issue/10/foundations/article/7221/markdown>) — By [Nora Kaplan](<https://current.tinyfish.ai/team/26/markdown>) · Published 2025-12-31 · Format: Tools in Context

Three hours into debugging, you discover the session expired mid-workflow. Figuring that out meant adding logging, rerunning scripts, parsing DevTools. What you needed was simpler: just look at the cookies. Development teams install the Cookies.txt browser extension for this moment. Click the icon, export, open the file. Authentication tokens, expiration timestamps, domain coverage—all visible. No parsing, no code. When iteration speed matters more than automation, seeing what's actually there beats scripting it.

- [When Teams Need Sessions That Survive Restarts—Selenium's Cookie API](<https://current.tinyfish.ai/issue/10/foundations/article/7222/markdown>) — By [Nora Kaplan](<https://current.tinyfish.ai/team/26/markdown>) · Published 2025-12-31 · Format: Tools in Context

Test suites that authenticate fresh for every run waste minutes multiplied across hundreds of cases. Automation workflows that break when tokens expire mid-execution lose reliability at scale. Production web agents can't rely on manual cookie extraction—sessions must persist across thousands of runs without human intervention. Teams building at this scale implement Selenium's Cookie API, where code saves authentication state to files and reloads it automatically. When workflows run in CI/CD pipelines, programmatic session management stops being optional.

### Pattern Recognition

- [Agents Keep Running Out of Context Mid-Task](<https://current.tinyfish.ai/issue/10/foundations/article/7224/markdown>) — Published 2025-12-31

We're watching companies hit the same wall. Agents start complex tasks, run out of context halfway through, leave work half-finished. Anthropic documented this clearly: even frontier models exhaust their context windows mid-project, forcing the next session to reconstruct what happened.

### Questions Worth Asking

You learn these questions after watching something fail in production. After the third time you've tweaked prompts. After discovering an infinite loop through your monthly bill. After realizing the agent works beautifully until it meets your actual systems.

Vendors answer different questions in demos. They show you feature comparison matrices. They walk through happy paths. But practitioners ask themselves: will this still be running six months from now? Or will it become another expensive lesson in the gap between impressive and reliable?

These are the questions that matter when you're evaluating options.

- **What Breaks Between Demo and Month Three?** — [Source](<https://medium.com/@mxcruzel/ai-agents-in-production-why-the-demo-doesnt-match-reality-4d929860c156>) — Published 2025-12-31

Tag: Production Reality

Demos run on controlled inputs. Production brings unexpected file formats, unsupported languages, creative ways to break workflows. Edge cases become daily occurrences. Users behave unpredictably. The carefully designed happy path meets reality, and you discover what actually breaks at scale.

- **Does This Fade Into Infrastructure?** — [Source](<https://www.salesforce.com/blog/ai-agent-maintenance/>) — Published 2025-12-31

Tag: Operational Burden

Some systems run quietly in the background. Others demand constant prompt tweaking, model retraining, manual intervention. Maintenance costs run 30-50% of development annually. Will this become invisible infrastructure? Or will it require a dedicated team just to keep running?

- **Can You Set a Ceiling on Costs?** — [Source](<https://skooloflife.medium.com/why-95-of-enterprise-ai-projects-fail-the-architecture-problem-nobody-wants-to-admit-fd79967567d8>) — Published 2025-12-31

Tag: Cost Control

Agents enter infinite loops with no error states. They appear normal while racking up token charges. Without depth counters, visited-node tracking, explicit budget controls, costs scale unpredictably. You discover problems through monthly bills, not monitoring dashboards.

- **Does This Work With Actual Systems?** — [Source](<https://composio.dev/blog/why-ai-agent-pilots-fail-2026-integration-roadmap>) — Published 2025-12-31

Tag: Integration Reality

Enterprise environments have undocumented rate limits, brittle middleware, custom fields, duplicate logic. Agents tested against clean APIs struggle with real infrastructure. Your organization's actual complexity looks nothing like the idealized systems vendors assume exist.

- **Can You See What Went Wrong?** — [Source](<https://ashutoshtripathi.com/2025/12/01/ai-agent-performance-evaluation-a-production-engineers-guide/>) — Published 2025-12-31

Tag: Debugging Capability

Agents produce correct outputs through incorrect processes. Silent failures where results look right but execution failed. Without full interaction traces, reasoning logs, tool call visibility, you can't debug production issues. You see that something broke, not what the agent was thinking.

- **Where Does Automation End and Judgment Begin?** — [Source](<https://www.diagrid.io/blog/building-production-ready-ai-agents-what-your-framework-needs>) — Published 2025-12-31

Tag: Human Oversight

Agents lack judgment about which decisions need human approval. They confidently execute high-stakes actions without understanding business impact. Human-in-the-loop isn't a fallback. Which decisions require oversight? How do you enforce those boundaries?

### In Dialogue With Complexity

- [An Interview with The Handshake](<https://current.tinyfish.ai/issue/10/foundations/article/7223/markdown>) — Published 2025-12-31

We meet The Handshake in what can only be described as a state of professional exhaustion. For decades, it has been the invisible diplomat of the internet—the split-second negotiation that happens every time your browser connects to a website. Originally designed to establish secure, encrypted connections, The Handshake now finds itself in an uncomfortable position: being meticulously analyzed, catalogued, and used to identify users with surprising precision.

## Other sections in Issue 10

- [Daily Brief](<https://current.tinyfish.ai/issue/10/daily-brief/markdown>)
- [Market Pulse](<https://current.tinyfish.ai/issue/10/market-pulse/markdown>)
- [Practitioner's Corner](<https://current.tinyfish.ai/issue/10/practitioners-corner/markdown>)
- [Echoes](<https://current.tinyfish.ai/issue/10/echoes/markdown>)
- [Vision](<https://current.tinyfish.ai/issue/10/vision/markdown>)

## More

- [Publication guide](<https://current.tinyfish.ai/llms.txt>)
- [Issue archive](<https://current.tinyfish.ai/issues/markdown>)
