Agentic coding workshops for engineering teams
Most teams adopt AI coding tools individually and never build a shared way of working, so output stays inconsistent. This agentic coding workshop trains engineers as a team on real repositories, not demos. You leave with a tested AI coding workflow, clear rules for using coding agents, and a team adoption plan that survives past the first week.
Book a callWhat the workshop is for
The workshop gives teams a practical operating model for using AI coding tools together. It is built for real engineering work, not passive demos or generic prompt tips.
What teams practice
Participants plan tasks, delegate bounded work, review generated diffs, repair tests, encode team conventions, and decide where human judgment must stay in control.
What changes afterward
The expected outcome is a shared vocabulary, a repository-ready set of conventions, and a concrete list of workflows where the team can safely raise throughput.
Official references
Current product documentation we use when shaping this training topic.
Selected research
Representative field notes connected to this topic.
May 13, 2026
Fast mode is not the default: when fast models earn it
The fast model is a tradeoff you make on purpose: scope ledgers, replay sandwiches, and connector cards that keep fast agent runs reviewable.
May 15, 2026
Codex mobile CLI docs your team can read anywhere
The codex mobile cli question is a docs question: how a team keeps AGENTS.md rules, run notes, and verification transcripts readable away from the desk.
How to Set Up Agentic Coding Workflows and Guardrails
How to set up agentic coding workflows and guardrails for Codex, Claude Code, and Cursor, with receipts a reviewer can actually check.
May 9, 2026
Agentic workflows from PR to merge
A PR review workflow for agentic coding teams: connector ownership, scoped tasks, replay transcripts, and human approval lanes from PR to merge.
May 16, 2026
Codex mobile CLI: runs that survive review
A codex mobile cli pattern for running Codex CLI from anywhere: verification latches, model pins, and connector rosters that keep remote runs reviewable.
May 10, 2026
AI agent guardrails that hold
A field guide to AI agent guardrails for recursive agent chains: connector ownership, child receipts, and review evidence that survives the merge queue.
Related training topics
How can platform and infrastructure teams use shared OpenAI Codex agent workflows?
Safe AI coding practices for development teams
UK AI coding workshops for engineering teams
Codex workflows: CLI, MCP, and review
Have you tried these?
Run the change on one branch. The methodology puts that in Review: an engineer still owns the merge. Training is the team version of that step.
Bring this into your team
We tailor the training to your codebase, adoption stage, and review standards.
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