Prompt systems
Pattern libraries, system prompts, and modular prompt chains that are easier to maintain, test, and improve.
Hey. I’m Sunil,
AN AI EDUCATOR& APPLIED AIOPERATOR
I help organizations turn generative AI from an interesting experiment into something dependable, useful, and ready for production.
Agentic workflows
Task decomposition, tool-use orchestration, and guardrails so multi-step work completes more reliably.
Eval & governance
Quality gates, golden sets, rubric scoring, and audit trails before systems fail in production.
Team enablement
Playbooks, roles, review loops, and working methods that turn isolated experiments into repeatable capability.
Cited by
Crafting reliable & impactful AI systems
Blended strategy and implementation: prompt systems, agents, evaluation, and the operating model that makes generative AI durable in production.
- 20+
- Years across marketing, cybersecurity, design, analytics, and AI
- $30MM+
- Recovered or saved for businesses over about five years
- 20k+
- PromptEngineering.org subscribers
- Cited
- Across academia, government, and industry
Education & research
PromptEngineering.org
The education and research brand for practical AI literacy: prompt systems, production agentic workflows, and the frameworks teams can actually run. Libraries cover Partials, Agents, and Miniscripts. The site reaches 20k+ subscribers.
Visit PromptEngineering.orgACE
Aim, Coordinate, Execute — split intent, routing, and deterministic work so automations stay testable.
5C
Clarity, Contextualization, Command, Chaining, Continuous Refinement — a prompt-construction loop.
PseudoLangs
Constructed notations between prose and code, so encoding — not just wording — carries the load.
01
What is Prompt Engineering?
The systematic design, refinement, and evaluation of prompts and the structures around them — not just clever phrasing.
Read on site02
Agentic Workflows
How agents plan, act, and verify: when they beat static automations, and how structured outputs and guardrails make them production-ready.
Read on site03
The ACE Framework
Aim defines the business intent, Coordinate decides who runs next, Execute does the work with scripts and tools you can test.
Read on site04
Introduction to PseudoLangs
Purpose-built notations for talking to models. How you encode a prompt — not only what it says — changes the result.
Read on site
Also on the site: System Prompts for LLMsThe 5C FrameworkPartials libraryAgents libraryMiniscripts & Processors
The discipline
AgentEngineering.org
Less hype. More working systems. The site covers the design, tooling, evals, failure modes, and operating practice behind AI agents that have to survive real work. Read foundations first, then mechanics, then AgentOps.
Visit AgentEngineering.orgFoundations
What an agent is, what changes from a plain LLM, and how much autonomy a task actually needs.
Mechanics
How systems decompose work, take action with tools, remember, and reason through multi-step runs.
AgentOps
Traces, evaluations, guardrails, and human controls as an ongoing production practice.
01
What Is Agent Engineering?
The discipline of designing, building, evaluating, and operating goal-directed AI systems that reason over state, use tools, and act under explicit control.
Read on site02
Introduction to AI Agents
Goal-directed software that uses models, tools, context, and control loops across multiple steps — without the hype.
Read on site03
AgentOps: Running Agents in Production
The operating layer that turns traces, evaluations, guardrails, and human controls into a practice for live autonomous systems.
Read on site04
Structured Outputs & Guardrails
Structured outputs constrain shape, guardrails constrain policy, and execution boundaries constrain power. Safe agents need all three.
Read on site
Also on the site: When to Use a Workflow Instead of an AgentTool Use: How Agents Take Action
Next
Let’s make the work operational
For consulting, speaking, or PromptEngineering.org work, start on LinkedIn. Email is available on request.