corporate training · ai-native engineering
Bring AI-native engineering to your team — without the consulting markup.
Custom 1–5 day workshops for your dev team, your codebase, your stack. We come in (Vizag in-person, or anywhere via Zoom), assess where AI fits and where it doesn’t, and leave behind a workflow your team owns.
who books this
Built for teams that need to ship faster — not just “learn AI”.
- Product teams adopting AI tools and wanting senior-grade discipline (not vibe-coding)
- Service / consulting teams whose juniors need to ship faster without losing fundamentals
- Government / public-sector engineering arms modernising legacy stacks
- Mid-size companies migrating off legacy code (PHP → modern stack, jQuery → React, etc.)
- Startup engineering teams wanting a multi-CLI pluggable workflow from day one
probably not the right fit if
- ×Pure leadership upskilling — we teach engineers, not executives
- דAI for everyone” orgwide events — we go deep, not wide
- ×Pre-recorded video learning — we train live or not at all
training tracks · custom-fit
Four pre-packaged tracks. Or we build a custom one.
Track 1 · AI Coding Discipline for Junior Engineers
Take your juniors from prompt-and-pray to AI-augmented engineers with senior judgement. Code-review etiquette, when to trust AI output, when to push back, how to keep the codebase consistent.
Outcome: Your juniors ship cleaner code 5–10× faster without you having to babysit every PR.
Track 2 · Multi-CLI Pluggable LLM Architecture
Build a single adapter that lets your products swap Claude / Codex / Gemini with one env var. Zero vendor lock-in. Each engineer ships their own adapter + a real feature using it.
Outcome: Your team owns a production-grade pluggable LLM layer they understand end-to-end.
Track 3 · Production RAG Engineering
Bring your corpus (docs, transcripts, tickets, manuals). Walk out with a production RAG: ingestion, chunking, hybrid retrieval, re-ranking, evaluation, observability. Real metrics, not demos.
Outcome: A shipped RAG system on your corpus, with a measurable retrieval-quality scorecard.
Track 4 · Multi-Agent Review Loops
Design and ship a QC / DA / Fixer loop that finds, challenges, and fixes issues in your real codebase. Highest-leverage AI workflow we teach.
Outcome: Your team has its own multi-agent review loop running in CI on production code.
how we deliver
Three-step engagement. No bloat.
01
Discovery call
30–60 minutes. We listen, ask sharp questions, and propose a shape (track + duration + outcome).
02
Custom workshop
Delivered at your office, our Vizag campus, or via Zoom. We use your codebase as the canvas, not toy examples.
03
30-day follow-through
Async support in your team's Slack/Discord for 30 days post-workshop. We answer code-review questions, tune the workflow.
get a quote
Tell us about your team.
We’ll respond within one working day with a shape-and-cost proposal — no contract yet, no obligation.
- · Team size we typically train: 6–30 engineers
- · Custom workshops priced per day, from ₹50,000/day
- · Vizag in-person or anywhere via Zoom
- · English + Telugu instruction supported