Algorithmic Mastery with AI - Full Day
In today’s AI-powered era, mastering algorithms isn’t just about passing interviews — it’s about solving real-world problems with clarity, efficiency, and scale.
This workshop equips developers, architects, and technical leads with a 7-step framework for algorithmic problem-solving — enhanced by AI tools like ChatGPT and GitHub Copilot. Through hands-on coding, guided exercises, and AI-augmented decision-making, participants will learn to move from brute force to elegant, optimized solutions that scale.
Outcomes:
Confidence to solve problems with clarity and structure.
A personal toolkit of reusable algorithmic patterns.
Ability to use AI to accelerate problem-solving safely.
Practical experience connecting algorithms → systems.
A repeatable framework for tackling interviews and production challenges.
Audience:
Developers & Software Engineers (coding mastery).
Technical Architects (system-level optimization).
Engineering Leaders (mentorship, design reviews).
Net Result:
You leave not just as a better coder, but as an AI-empowered problem solver who can transform any problem into a systematic, optimized, and scalable solution.
Agenda:
Module 1: Foundations of Algorithmic Thinking
Why algorithms matter beyond interviews.
The 7-step problem-solving framework.
AI as partner, not crutch.
Mini-exercise: clarify → brute force → optimize.
Module 2: Arrays, Hashing & Sliding Window Techniques
Frequency maps, prefix sums, two pointers.
Fixed vs. variable window problems.
Hands-on: Longest substring without repeats.
AI demo: auto-generating edge cases.
Module 3: Trees, Recursion & Divide-and-Conquer
Binary trees, BSTs, traversals.
Recursion principles: base case design, stack depth.
Divide & conquer in search/sort.
Exercise: Subset generation with recursion.
AI support: spotting infinite recursion.
Module 4: Graph Algorithms in Action
BFS vs. DFS, cycle detection, topological sort.
Shortest path algorithms (Dijkstra, A*).
Real-world uses: routing, dependencies, scheduling.
Hands-on: Course prerequisite (DAG + cycle check).
Module 5: Dynamic Programming & Greedy Strategies
DP basics: overlapping subproblems, optimal substructure.
Memoization vs. tabulation.
Greedy wins vs greedy fails.
Exercise: Coin change → greedy vs DP.
AI demo: recurrence relation generation.
Module 6: Optimization & Complexity Awareness
From brute force → optimized solutions.
Time/space complexity refinement.
When to optimize, when not to.
Hands-on: optimizing rotated array search.
AI code review: spotting inefficiencies.
Module 7: System-Level Algorithmic Thinking
How algorithmic choices shape APIs & backend logic.
Readability, modularity, maintainability.
Scaling strategies: caching, sharding, parallelism.
Capstone exercise: build scalable recommendation logic.
AI for documentation + design alternatives.
About Rohit Bhardwaj
Rohit Bhardwaj is a Director of AI & Data Architecture at Salesforce, where he focuses on enterprise AI, agentic systems, cloud-native architecture, distributed systems, data platforms, security, and large-scale transformation.
Over his career, Rohit has designed and led complex enterprise platforms across AWS, Google Cloud, microservices, real-time data, API ecosystems, resilient distributed systems, and AI-enabled architectures. His work increasingly focuses on the challenges enterprises face as software evolves from deterministic services to AI-native and agentic systems—particularly around reliability, governance, evidence, security, observability, cost, and safe autonomy.
Rohit is the author of System Design with AI Interview Guide: Designing Scalable, Agentic, and Defensible Systems, published by Apress. The book presents a modern approach to system design covering scalability, distributed systems, AI architecture primitives, security, reliability, economics, agentic systems, and real-world architectures including e-commerce, ride sharing, payments, fraud detection, messaging, video streaming, file storage, and search. (Springer Link)
Book:
Amazon: https://a.co/d/09Zs1twa
Publisher / Springer Nature: https://link.springer.com/book/10.1007/979-8-8688-2782-2
O'Reilly: https://learning.oreilly.com/library/view/system-design-with/9798868827822/
Rohit is also an O’Reilly instructor and a frequent speaker at technology conferences including No Fluff Just Stuff, UberConf, GIDS, and other international events. His talks focus on practical architecture lessons from building and operating complex systems, including AI control planes, trusted agents, inference at scale, evidence-first RAG, AI security, distributed-system failure, and AI-era software architecture.
As a trusted advisor and architecture leader, Rohit works at the intersection of business strategy and deep technical architecture—helping teams translate complex business problems into scalable, resilient, secure, and economically sustainable systems.
Rohit holds an MBA in Corporate Entrepreneurship from Babson College and graduate-level education in Computer Science from Boston University and Harvard University.
Connect with Rohit:
LinkedIn: http://linkedin.com/in/rohit-bhardwaj-cloud
X / Twitter: @rbhardwaj1