Alpinum Consulting is bringing its evidence-led approach to AI engineering education to India. The first scheduled live online delivery of the new AI-Assisted Coding, RAG, MCP and Agentic AI Training will run on 2–5 and 9–11 November 2026, from 6:00 PM to 10:00 PM IST. The programme focuses on a practical question: how can engineers use AI to accelerate software work while keeping changes bounded, tested, reviewable and safe to maintain?
Why Alpinum Is Bringing This Programme to India
India is already central to the global software-development ecosystem. GitHub’s Octoverse 2025 report states that India added more than five million developers during the year over 14% of all new accounts and led the world in developer growth. At the same time, the Government of India’s IndiaAI FutureSkills initiative is expanding the country’s AI talent ecosystem and access to AI learning.
That scale creates an opportunity, but it also sharpens the need for practical engineering discipline. Access to an AI coding assistant is not the same as being able to use it responsibly on a real repository. Working engineers need repeatable ways to define a task, provide only the right context, control tool access, test the result and explain why a change should be accepted.
Alpinum’s first scheduled delivery therefore focuses on an India-based live online cohort. The evening IST schedule is designed to support working professionals and suitably experienced advanced learners without presenting the programme as an India-exclusive offering.
The Engineering Gap the Programme Addresses
AI-generated code can look persuasive before it is dependable. It may compile and still misunderstand the requirement. A generated test can pass because it repeats the same assumption as the generated implementation. An agent can make a technically valid tool call while exceeding the access that the task actually requires. These are engineering-control problems, not merely prompting problems.
A credible workflow must therefore preserve independent review. Engineers need explicit acceptance criteria, repository-aware context, tests that challenge the change, controlled permissions, traceable actions and a handover record that another person can assess. This aligns with the broader principle in the NIST Secure Software Development Framework that secure development practices should be integrated into the software-development life cycle rather than treated as an afterthought.
From Code Generation to Controlled Engineering
| Stage | Engineering focus | Evidence of control |
| Controlled assistance | Bounded prompts, repository context and acceptance criteria | The task, constraints and expected behaviour are explicit before code is accepted. |
| Connected workflows | Repository RAG, approved resources and secure MCP access | Retrieved context has provenance; tools expose only authorised actions and data. |
| Agentic engineering | Stateful workflows, testing, tracing, human approval and handover | Actions and failures are reviewable; release authority remains with accountable engineers. |
This progression is deliberate. Retrieval-augmented generation (RAG) can help an assistant work from approved repository knowledge rather than guess from a prompt alone. Model Context Protocol (MCP) can provide structured connections to tools and resources. Agents can coordinate multi-step work. None of those mechanisms removes the need to define boundaries, validate retrieved context, restrict permissions, test outcomes and require human approval at consequential points.
Practical Learning, Not a Tool Demonstration
The programme is instructor-led and organised around guided practice. Across the full 28-hour route, the current course design includes 14 demonstrations, 14 short quizzes, 14 corresponding practical exercises and a capstone that brings coding, retrieval, tool use, verification and operational handover together.
Participants do not simply watch an assistant generate code. They work with requirements, repository context, prompts, code changes, tests, review notes and handover evidence. The objective is to make the engineering decision visible: what was requested, what context was used, what changed, how it was challenged, what remains uncertain and who approved the result.
The methods are designed to transfer across tools. Depending on the agreed setup, practical examples may use contemporary tools and frameworks such as Claude Code or Codex, Python, Git, pytest, Qdrant, the official MCP Python SDK, LangChain and LangGraph. Tool familiarity matters, but the durable capability is knowing how to control and evaluate the workflow.
The First Scheduled Programme for India
The first scheduled cohort will be delivered live online through Microsoft Teams on 2 – 5 and 9 – 11 November 2026, from 6:00 PM to 10:00 PM IST. Participants may follow the complete seven-session, 28-hour learning path or select individual four-hour sessions according to their needs.
The programme is intended for software engineers, QA engineers, architects, technical leads, working professionals and advanced learners who want structured practice with AI-assisted development. It is not a zero-experience introduction: participants should already have basic programming experience and working familiarity with Git and the command line.
Supporting Individuals, Engineering Teams and Universities
Individual participants can join the scheduled live programme using Alpinum’s supplied sample repository. Organisations and universities can request private delivery adapted to approved tools, repositories, policies and learning requirements. For private cohorts, repository and data access remain subject to the organisation’s confidentiality, security and tool-approval rules.
Participants who meet the required attendance and practical-evidence requirements may receive a certificate of completion. The emphasis is on demonstrable learning and reviewable engineering work; the programme does not promise interviews or job placement.
Building Capability That Teams Can Review
The most useful outcome of AI-assisted development is not simply more generated code. It is a workflow in which speed does not erase accountability. A team should be able to see why an agent had access to a resource, how repository context was selected, which tests challenged the change, where a human intervened and what evidence supports release or handover.
That evidence-led approach reflects Alpinum’s wider background in testing and verification. The programme treats AI assistance as part of an engineering system, one that must be specified, observed, reviewed and improved, not as an autonomous substitute for experienced judgement.
Written by : Mike Bartley
Mike started in software testing in 1988 after completing a PhD in Math, moving to semiconductor Design Verification (DV) in 1994, verifying designs (on Silicon and FPGA) going into commercial and safety-related sectors such as mobile phones, automotive, comms, cloud/data servers, and Artificial Intelligence. Mike built and managed state-of-the-art DV teams inside several companies, specialising in CPU verification.
Mike founded and grew a DV services company to 450+ engineers globally, successfully delivering services and solutions to over 50+ clients.
Mike started Alpinum in April 2016 to deliver a range of start-of-the art industry solutions:
Alpinum AI provides tools and automations using Artificial Intelligence to help companies reduce development costs (by up to 90%!) Alpinum Services provides RTL to GDS VLSI services from nearshore and offshore centres in Vietnam, India, Egypt, Eastern Europe, Mexico and Costa Rica. Alpinum Consulting also provides strategic board level consultancy services, helping companies to grow. Alpinum training department provides self-paced, fully online training in System Verilog, UVM Introduction and Advanced, Formal Verification, DV methodologies for SV, UVM, VHDL and OSVVM and CPU/RISC-V. Alpinum Events organises a number of free-to-attend industry events
You can contact Mike (mike@alpinumconsulting.com or +44 7796 307958) or book a meeting with Mike using Calendly (https://calendly.com/mike-alpinum-consulting).
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