20 practical lessons on production AI agents from Atlassian Team Europe
MaryamMiradi · x · 2026-10-15
Maryam Miradi distilled 20 hands-on AI engineering lessons from Atlassian Team Europe on running production AI agents:
Context graphs & agent memory
- Agents have a context problem: connect organizational knowledge across tools
- Prepare context before agents ask: precompute relationships and reuse relevant context
- Smaller context can be better: compact vectors, hierarchical retrieval, semantic matching
- Agent sessions shouldn't disappear: retain them as reusable memory
- Code review feedback should become memory: store comments, fixes, approvals for future tasks
Multi-agent workflows
- Invisible agents create invisible work: track local/cloud agent sessions, ownership, and progress
Plus more on FDEs, PR-to-video, and other practices.
Related event: Atlassian Team Europe Shares 20 Production Lessons for AI Agents(2 posts)→
More from coding & agent
- Decisions API hits GA as agents automate cloud video editing via feedback loops — dkundel · 2026-10-23
- Swarms API changelog: 8 months of streaming, multi-agent orchestration, and dynamic model pricing — KyeGomezB · 2026-10-23
- A curated library of 50+ free AI agent resources: videos, repos, one Google Doc — ifioknkem · 2026-10-23
- Vercel adds no-account deploys: drag and drop a file to get a live URL — steren · 2026-10-23
- Dev runs 5 Claude Code sessions that coordinate via MCP Agent Mail to root his network cameras — doodlestein · 2026-10-23
- Vercel ships 'vercel deploy --temporary' for ephemeral agent-built deployments — cramforce · 2026-10-23