Growing Pains: Scaling AI Coding across Team and Repo Boundaries
Details
If 2024 was the year of autocomplete and 2025 belonged to early-adopter agentic experiments, 2026 is the year of enterprise implementation. But what happens when you move Claude Code and GitHub Copilot out of a pristine, solo sandbox and force them into a messy, multi-team, multi-repo enterprise architecture?
We will pull apart real-world solo and team-based agentic workflows, focusing on the configuration, commands, and custom toolsets required to make AI work in production, and how it can go wrong.
We will practically look at:
- Write Python, Get Rust: Prompt structures and verification tools used to safely translate logic across language boundaries.
- Mob-Programming Markdown Specs: Turning architectural requirements into actionable agent instructions using shared cross-technology contracts.
- Breaking the Repo Wall: Technical strategies (including custom tools/MCPs) to give your agent visibility into upstream API dependencies and infrastructure repos without blinding it with context explosion.
- The `AGENTS.MD` Blueprint: Writing a shared team configuration file that guides the AI’s architectural choices without overfitting or retaining obsolete custom patterns.
Expect live terminal examples, real configuration files, and an honest look at the failure modes, rate limits, and security constraints of scaling AI tools in a polyglot enterprise environment.
Speaker:
* Graham Knapp
Host: Gabor Szabo
Language: English
Location: Zoom