AI First^® Training for Tech

1) Is this just prompt tips, or will our process change?
It’s designed to change how you work, not just how you prompt. We fold AI-assist into existing rituals,  Definition of Ready/Done, backlog refinement, code review, release comms, and post-mortems, so the steps are auditable and repeatable inside your SDLC. You finish with a published prompt/pattern library in your current tools, updated working agreements, or an adoption plan with named owners, success metrics, and clear stop-for-review gates for high-stakes work. We can prioritize certain objectives in our intake call.

2) Do engineers need ML or Python experience?
No. Core AI training program assumes no coding and focuses on tool-agnostic patterns that boost velocity without changing your tech stack. For teams that want it, we offer optional advanced paths (Python/SQL, evaluations, and light RAG concepts) calibrated by role and stack. However, the baseline curriculum is accessible to PMs, EMs, QA, and ICs alike.

3) How do you handle IP and privacy?
We run exercises on synthetic or redacted data only, inside your approved environment or a sandbox with logging, SSO, and strict data retention controls. We do not push source or confidential materials to public models; usage boundaries are codified in policy starters you can adopt with Legal/Security, and we’re happy to work under NDA with role-based access and audit trails.

4) What impact should we expect in month one from the Corporate AI Training Program?
Most teams see shorter story prep and PR turnaround, cleaner test scaffolds, and fewer handoff misses,  tracked against simple baselines like cycle time, rework rate, and defect discovery. You’ll have a ranked pilot list running immediately, a lightweight adoption dashboard for telemetry, and office hours to unblock teams; results vary by maturity, but the plan is explicit and measurable from day one.

5) Can we do Corporate AI training in multiple offices at once?
Yes. We deliver on-site, virtual, or hybrid with a single curriculum, localized examples, time-zone-friendly scheduling, and recordings when permitted. A dedicated producer coordinates cohorts, headcount (4 to 200+), and tech checks so each location stays within its tooling policy while sharing the same outcomes, templates, and governance standards.