Marc von HolzenFoundations — Gear Up Velocity
Your engineers are ready to start working with agents. This engagement helps them get setup.
Best Suited For
Engineers ready to integrate AI agents into their daily workflow.
Your team members have varying degrees of adoption of the new tools, not everyone is convinced.
The high performers are leading the way, but security, quality and consistency are a concern.
What We Deliver
Your team ships using agents. Engineers have the skills, patterns, and confidence to ship with AI agents as part of their standard development process.
- Engineers prompt, plan, and ship with agents daily
- Testing feedback loops available to agents
- Code review processes adapted for agent output
- Community of practice shares learnings across the team
We apply these practices for specific initiatives or timeframes.
Outcome
Deliver well-understood features faster and with less effort
The team reaches signficant higher velocity
Key Integrations
- Best practices for agentic development
- Guidelines, workflows and skills disseminated and improved through iterative feedback
- Test infrastructure integrated with MCP
- Architecture and requirements pulled into context
Activities
Author
Select and integrate agents into the development workflow. Establish patterns for prompting, context management, and permission handling that work with your existing practices.
- Evaluate team- and project-specific confidentiality, privacy, and security requirements
- Select agentic service providers, package levels and cost monitoring processes
- Recommend agent tooling and integrations (IDEs vs terminal based, backend vs mobile vs frontend)
- Capture guidelines (coding, security, infrastructure, testing, …), identify owners and setup feedback loops
- Define model for engineers to discover and fetch relevant artifacts
- Ensure well-defined conventions for requirements (including user story, acceptance criteria, success and failure paths, error handling, logging and metrics)
- Identify risk areas and manage default permission sets
- Learn effective planning mode, context management practices, persistent memory tooling, skills, commands
- Setup communication channels and community of practice (CoP) to disseminate learnings
Test
Build confidence in agent-generated code. Develop testing strategies that validate agent output and catch issues before they reach production.
- Determine, setup or build MCP servers to access testing infrastructure
- Automate deployment and management of testing infrastructure
- Setup testing feedback loops to teach agents how to validate code themselves
- Learn how to use TDD effectively
- Establish metrics for agent-assisted code quality
Ship
Deploy with confidence. Create the guardrails and review processes that let your team ship agent-assisted work at production quality.
- Establish partial commit and push workflows to enable early feedback
- Set up automated agent review for published branches and PRs
- Create code review processes specific to agent generated code
Roadmap
Ready to Ship with Agents?
Let's discuss how to integrate AI agents into your engineering workflow.
Get In Touch