Prompt engineering training teaches professionals to design, test and refine instructions for AI models so outputs are accurate, consistent and fit for purpose. It covers techniques such as role and context setting, few-shot examples, step-by-step reasoning and output formatting, and ends with a tested, reusable prompt library for the team.
- Recommended: 2 days in person, or 4 × 3-hour live virtual sessions ending in a library sprint
- Level: Intermediate · In person · Live virtual · Blended
- Designed with the ADDIE model and customised to your context
- Offered by Bodhih since 2008 to 2,000+ organisations across 7 regions
Also known as: prompt engineering course, prompt engineering workshop, prompt writing training, corporate prompt engineering training
Where and how: prompt engineering training as an in-person workshop in Bengaluru, Mumbai, Delhi NCR, Gurugram, Hyderabad, Chennai, Pune, Kolkata, Ahmedabad and Jaipur; as a live online course; or delivered overseas in Dubai, Singapore and across the Middle East, Asia and Africa.
From lucky prompts to reliable prompts
Once basic AI use is common, the next problem is inconsistency. Two colleagues ask for the same report and get very different quality, and nobody can explain why.
Prompt engineering training treats prompts as reusable work assets. Teams learn to write them deliberately, test them on edge cases and store the strongest versions where everyone can find them.
What participants will be able to do
Structure complex prompts
Combine role, goal, context, constraints and output format into prompts that work the first or second time.
Use proven techniques
Apply few-shot examples, step-by-step reasoning, decomposition and self-critique where each one fits.
Control the output
Request tables, JSON, checklists or house-style text so results drop straight into your workflow.
Test and compare prompts
Evaluate prompt versions against a simple rubric instead of relying on gut feel.
Ground answers in sources
Supply reference documents and instruct the model to cite them, reducing invented content.
Own a team prompt library
Publish a documented set of prompts with owners, version notes and usage guidance.
Who should attend
- Professionals who already use an AI assistant weekly and want better results
- Analysts and reporting teams producing recurring summaries and insights
- Content, marketing and communications teams working to a brand voice
- HR, L&D and sales operations teams creating templates at scale
- IT and GCC teams preparing to build AI features or agents
Program outline
Recommended design, customised to your context after a short needs analysis.
01Anatomy of an effective promptModule 1 · 90 min+
- How models read instructions and context
- The six building blocks of a strong prompt
- Common failure patterns and how to diagnose them
- Rewrite drill: five weak prompts made strong
02Core techniquesModule 2 · 2 hours+
- Zero-shot versus few-shot prompting
- Asking for step-by-step reasoning and plans
- Breaking big tasks into prompt chains
- Self-critique and revision prompts
03Structured outputs and formatsModule 3 · 90 min+
- Tables, bullet schemas and JSON for downstream use
- Style guides and tone controls
- Length, reading level and audience settings
04Working with documents and dataModule 4 · 2 hours+
- Grounding prompts in reference files
- Extraction and classification prompts
- Asking for citations and flagging uncertainty
- Lab: turn a 30-page RFP into a compliance matrix
05Testing, evaluation and safetyModule 5 · 90 min+
- Building a small test set and rubric
- Checking for bias, leakage and prompt injection risks
- What never goes into a prompt: data privacy rules
06Prompt library sprintModule 6 · 2 hours+
- Choosing ten high-value recurring tasks
- Templating with variables and instructions for users
- Peer testing and versioning
- Publishing and governance for the library
How we deliver it
Bring your own tasks
Participants arrive with two or three recurring tasks. Every technique is applied to those tasks, so the library reflects real work.
Test-driven prompting
Each lab includes a mini test set and rubric, building the habit of evaluating prompts rather than trusting a single good answer.
Tool-agnostic methods
We teach techniques that transfer across major AI assistants, while running labs on your approved platform.
ADDIE-based customisation
Our analysis stage reviews sample outputs and pain points, so modules are weighted to what your teams actually struggle with.
Tailored versions
For IT and GCC engineering teams
Adds prompts for code explanation, test generation, log analysis and documentation, plus an introduction to system prompts and agent instructions.
For business and operations teams
Focuses on reports, emails, SOPs, meeting outputs and customer responses, with no coding required.
How we measure impact
Through the Evaluate stage of ADDIE, participants complete a pre and post practical assessment on AssessAll, where AI-graded tasks score prompt quality and output accuracy. We also compare output samples before and after the program against a rubric agreed with your team. At 30, 60 and 90 days we review library usage, new prompts contributed and manager feedback on quality and turnaround time.
Pair this program with AssessAll, Bodhih’s AI assessment platform, for pre- and post-program skill measurement.
Frequently asked questions
What is prompt engineering training?
It is a skills program that teaches people to write, test and improve instructions for AI models. Instead of trial and error, participants learn repeatable techniques, formatting controls and evaluation methods. The goal is consistent, high-quality output that a whole team can reproduce using shared templates.
Can non-technical people learn prompt engineering?
Yes, because most prompt engineering for business work is structured writing and clear thinking, not coding. Our prompt engineering training uses plain language and business scenarios. A technical variant is available for developers who want to work with system prompts, structured outputs and agents.
What are the main prompt engineering techniques?
The core techniques are role and context setting, clear constraints, few-shot examples, step-by-step reasoning, task decomposition into prompt chains, output formatting and self-critique. Grounding answers in supplied documents is also important. The program shows when each technique helps and when it adds nothing.
How do you build a prompt library for a team?
Pick recurring, high-value tasks, write a template for each with variables and usage notes, test it on several real examples, then store it where the team works. Assign an owner and review it quarterly. The final module of the program is a guided sprint to build exactly this.
How long does it take to learn prompt engineering?
The fundamentals can be learned in a few days of focused practice. Bodhih recommends two days in person or four live virtual sessions, followed by on-the-job use. Skill keeps growing as people apply the techniques to new tasks and share what works.
Is prompt engineering still relevant as AI models improve?
Models are better at guessing intent, but clear goals, context, constraints and verification still decide whether output is usable. As organisations build assistants and agents, well-designed instructions matter even more. The skills taught here are about clear specification and testing, which do not go out of date.
What will participants take away from the program?
Each participant leaves with a personal set of tested prompts for their recurring tasks, a one-page technique guide and a rubric for judging output quality. The team also leaves with a shared prompt library, including owners and version notes, that can be published on your intranet or collaboration platform and improved over time.