● Terminal AI Agents Hijack Coding, Context Poisoning Threatens Developers, Manager Mode Takes Over
This article goes beyond simply which AI tool is good. It contains core points and insights hard to find elsewhere, such as why cutting-edge AI agents are regressing to the 20-year-old CLI (terminal) environment instead of modern IDEs, and essential ‘Context Poisoning’ management methods for becoming a top 1% developer. After reading this, you will be able to draw a clear picture of how the software industry will be personalized in the future and how our way of working will change into ‘Manager Mode’.
The Future of Development is ‘Manager Mode’: The Landscape Shifted by Claude Code and AI Agents
The hottest topic in Silicon Valley recently is undoubtedly the rapid evolution of AI Coding Agents. Through a conversation with Kelvin French Owen, co-founder of Segment and an early member of the OpenAI Codex project, it has been confirmed that developers are transforming from runners running the marathon themselves into ‘Managers’ who replace the players’ knees and direct the course.
What is particularly interesting is that Generative AI Trends are regressing to text-based CLIs (Command Line Interfaces), not complex and flashy graphic interfaces (IDEs). While the CLI looks like outdated technology to humans, it is the optimal environment for AI agents to access the system most purely and powerfully. Tools like Claude Code or Codex directly access databases within the terminal, find nested bugs 5 levels deep, and even write test code. This can be seen as the beginning of ‘autonomous driving’ beyond simple coding assistance.
AI Agent War: Anthropic’s ‘Human Tool’ vs. OpenAI’s ‘AGI Pursuit’
The current AI coding market is largely divided into two philosophies. This part is very important for understanding the Software Development Future.
Anthropic’s Claude Code strictly aims to be a ‘tool for humans’. Just as when you assign a task to a competent colleague, that colleague goes to the hardware store to buy necessary materials and assembles them, it grasps the user’s intent and generates sub-agents to search (grep) the file system and report results.
On the other hand, OpenAI’s Codex is heading towards a slightly more radical goal: AGI (Artificial General Intelligence). Like trying to print a house from start to finish with a 3D printer, it seeks ultimate solutions through long-term task execution and Reinforcement Learning (RL), even if the method differs from human ways. While human-friendly Claude Code may feel more intuitive right now, there are prospects that the Codex method, which runs alone for 24 to 48 hours to solve problems, might win in a future where computing power increases 10-fold or 100-fold.
Secrets Known Only to the Top 1% Engineers: ‘Context Poisoning’ and TDD
The most critical technical insight from this conversation is LLM Context Window management and ‘Context Poisoning’. This is a part many overlook; AI models, like humans, tend to just guess answers when exam time is running out.
When the conversation gets long and token usage exceeds 50%, the model enters the so-called ‘Dumb Zone’. It references previously incorrect information, or code quality drops drastically. Therefore, experts boldly initialize (Clear) the context when tokens pile up, or plant random information (Canary) early in the conversation and check it periodically to ensure the AI is maintaining its memory well.
Also, to utilize AI 100% as Productivity Tools, ‘Test Driven Development (TDD)’ is essential. If you have the AI write test code before ordering it to write code, or set up a strict test environment, the AI creates code that passes those tests at a crazy speed. Now, a developer’s capability depends not on writing code directly, but on the ability to build precise ‘blueprints and test environments’ where AI can play.
Future Outlook: The Era of 1-Person-1-Software and the Emergence of a New Generation
40 years from now, the form of software will be completely different. Currently, every company uses the same SaaS (Software as a Service), but in the future, according to AI Agent Trends, customized forked software will be provided to each company, and even each individual. If a user says “Change this function” in the chat window, my own agent will immediately modify and deploy my exclusive software version.
The new generation aged 18~22 growing up in this environment will have much superior ‘Taste’ and ‘Multitasking’ abilities compared to previous generations. They will become talents specialized in ‘Manager Mode’, capable of commanding an army of AI agents while running 10 projects simultaneously rather than the depth of writing code directly, and this will become the future competitiveness.
< Summary >
- Regression from IDE to CLI: For AI agents, the terminal (CLI) is much more advantageous for system control and debugging than graphic environments, and this is the current trend.
- Rise of Manager Mode: Developers are changing roles from ‘players’ who code directly to ‘managers’ who instruct AI on tasks and review results.
- Difference in Philosophy: Anthropic (Claude) aims for human-friendly collaboration tools, while OpenAI (Codex) aims for long-running AGI-type solvers.
- Caution for Context Poisoning: As AI performance degrades when conversations get long, periodic context initialization and token management are essential.
- Future Changes: TDD (Test Driven Development) becomes more important, and an era where AI manages completely customized software for each individual/company in real-time will come.
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*Source: Y Combinator
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