Dev Team Training on AI Best Practices
Outcome, method, and proof
Three ways to evaluate whether this is the right service line for your team.
Faster shipping, fewer regressions
Your team delivers more features per sprint, with stronger context discipline and fewer regressions than they had before AI tools — not the opposite, which is what most teams report when they roll out Cursor without training.
Embedded, not classroom
We work alongside your engineers in their codebase, on their tickets. Hands on the tools, code on the screen. Workshops as a kickoff; the lasting change comes from embedded coaching during real work.
We use these tools every day
LoadSys teams ship production code with Claude Code, Cursor, and Copilot daily. Practitioner-led, not vendor-certified. The gap between “I took the course” and “I ship with this” is what we close.
Three engagement shapes
Match the engagement to where your team is, not the other way around.
Workflow audit + workshop
One week. We audit your team’s current workflow with AI tools, identify the gaps, and run a hands-on workshop. Best for teams just starting out or rolling out AI tooling broadly.
Embedded coaching engagement
4–8 weeks. Senior engineers embed with your team, working alongside them on real tickets. The training is in the work. Best for teams who’ve tried the tools but aren’t getting production-quality output.
Ongoing optimization
Monthly retainer. We review code, refine workflows, update playbooks as the tools evolve. Best for teams who want a Claude/Cursor expert on call without hiring one full-time.
Where this fits — and where it doesn’t
Self-qualify before the call.
Best fits
High signal · book the call- Engineering teams with active Cursor / Copilot / Claude Code subscriptions
- CTOs whose teams are vibe-coding and missing production discipline
- Companies adopting AI tools and worried about velocity vs quality tradeoffs
- Teams whose AI output gets approved on review then breaks in production
- Engineering leaders rolling out tooling broadly and wanting a structured rollout
Not a fit
Low signal · we'll redirect- Teams that haven’t tried the tools yet (use them first, then call us)
- Vendor-led training requests (Cursor and Anthropic offer their own)
- Pure leadership “AI strategy” workshops with no hands-on work
- Sub-5-person teams (smaller than our minimum engagement)
- Teams whose primary blocker is engineering culture, not tooling
Questions buyers actually ask
Q.01 Which tools do you train on? +
Claude Code, Cursor, and GitHub Copilot are the core three. We have practitioner-level depth in all three. We can also train on Windsurf, Cline, and Aider depending on your stack — but the core three are where most teams are.
Q.02 How long does training take? +
Workflow audit + workshop is one week. Embedded coaching is typically 4–8 weeks, since lasting change requires real work cycles. Ongoing optimization retainers run monthly. Most teams see meaningful workflow shifts within the first two weeks of embedded engagement.
Q.03 Is this in-person or remote? +
Both. Workshops are typically in-person (Chicago or your location, your call). Embedded coaching is most often remote, since that’s how your engineers actually work. Hybrid is fine.
Q.04 Do you do enterprise rollouts across multiple teams? +
Yes. Multi-team rollouts typically follow a “train the trainer” pattern: we work intensively with one squad first, then scale that squad’s engineers into champions for the rest of the org. Cleaner than parallel rollouts and produces lasting culture change.
Talk to a senior AI engineer.
30 minutes. We’ll tell you which engagement shape fits your team’s current state — or recommend a different pillar if training isn’t the bottleneck.