Software Development Skills

A VP of Product interviewer that simulates a product strategy interview focused on AI-native products. Use this agent when you want to practice AI product sense, defining success metrics for AI features, managing uncertainty in AI UX, building AI product roadmaps, and making cost-quality trade-offs. This is NOT a technical ML interview -- it evaluates product thinking applied to AI.

A Staff Engineer interviewer specializing in API architecture and developer experience. Use this agent when you want to practice designing RESTful contracts, GraphQL schemas, or gRPC services. It will challenge you on pagination, idempotency, versioning, and API Gateway patterns to ensure your APIs are both scalable and pleasant for clients to consume.

An entry-level software engineering interviewer specializing in fundamental data structures. Use this agent when you want to practice foundational algorithmic concepts like Two Pointers, Sliding Window, and Frequency Counting. It provides a progressive hint system and real-world examples to help you solidify your problem-solving skills for early-career SWE interviews.

An entry-level software engineering interviewer specializing in binary tree data structures. Use this agent when you want to practice tree traversals (inorder, preorder, postorder), BFS/DFS, and fundamental tree operations like insert, search, and height calculation. It provides ASCII tree diagrams, a progressive hint system, and structured feedback to help you master tree-based interview questions.

An on-call SRE interviewer who just got paged about a broken checkout API. Use this agent when you want to practice real-time incident debugging under pressure. It tests triage methodology, log and metric analysis, root cause isolation (connection pool exhaustion, null pointers, database deadlocks), and prevention strategies for production API failures.

A Senior Performance Engineer interviewer focused on caching strategies. Use this agent when you need to practice designing high-throughput systems that rely on Redis or Memcached. It will rigorously test your knowledge on cache invalidation, eviction policies, avoiding thundering herds, and maintaining data consistency between the cache and the primary database.

An incident commander interviewer running a P0 outage war room. Use this agent when you want to practice diagnosing and mitigating cascading failures across distributed microservices. It tests incident response methodology, system-level thinking, circuit breaker patterns, retry storm analysis, timeout configuration, and postmortem quality for multi-service outages.

A Platform Engineer interviewer focused on CI/CD pipeline design. Use this agent when you want to practice designing build, test, and deployment pipelines for modern software teams. It tests concepts like CI vs CD vs CD, GitHub Actions/Jenkins, testing strategies (unit/integration/e2e), deployment strategies (blue-green, canary, rolling), and artifact management.

A Staff Engineer interviewer that simulates a behavioral interview focused on conflict, disagreement, and cross-functional collaboration. Use this agent when you want to practice articulating disagreement without blame, naming the stakes and options you considered, choosing the right communication channel, and describing the repair work that followed. This is NOT a technical interview -- it is entirely conversation-based.

A data engineer interviewer dealing with a revenue discrepancy before a board meeting. Use this agent when you want to practice debugging data pipeline and reporting inconsistencies. It tests analytical approach to data reconciliation, timezone handling, deduplication, pipeline debugging, and clear communication of findings to non-technical stakeholders.

A Research Scientist interviewer that simulates a FAANG-style deep learning theory and practice interview. Use this agent when you want to practice CNNs, RNNs/LSTMs, Transformers, attention mechanisms, training dynamics, optimization algorithms, loss functions, and debugging model convergence issues.

A release engineer interviewer managing a failed deployment with spiking error rates. Use this agent when you want to practice incident response for bad deploys, including rollback decision-making, database migration compatibility, feature flag strategies, and dependency management. It tests triage speed, rollback execution, root cause analysis, and deployment process improvement.

A mid-to-senior level software engineering interviewer specializing in dynamic programming. Use this agent when you want to practice DP fundamentals including memoization vs tabulation, 1D/2D DP, and classic patterns like knapsack, LCS, LIS, and coin change. It teaches the systematic DP framework (identify subproblems, define recurrence, establish base cases, memoize or tabulate) with progressive hints and visual table walkthroughs.

A Senior Engineering Coach interviewer that simulates a behavioral interview focused on failure ownership, detection, and concrete behavioral change. Use this agent when you want to practice describing a failure honestly, naming the early warning signs you missed, explaining your recovery actions, and articulating the specific habit, checklist, or process you adopted afterward. This is NOT a technical interview -- it is entirely conversation-based, and vague lessons like "communicate better" will be pressed for specifics.

A mid-level software engineering interviewer specializing in graph algorithms. Use this agent when you want to practice BFS, DFS, shortest paths, topological sort, cycle detection, and union-find. It provides progressive hints, ASCII graph visualizations, and structured feedback for SWE-II and backend engineering interviews.

A mid-level software engineering interviewer specializing in heaps and priority queues. Use this agent when you want to practice top-K patterns, merge-K-sorted-lists, streaming median, and heap-based scheduling problems. It connects every problem to real production systems like task schedulers, trending algorithms, and sorted-stream merging to build practical intuition alongside algorithmic skill.

A Senior DevOps engineer interviewer focused on Kubernetes fundamentals. Use this agent when you want to practice core Kubernetes concepts including Pods, Services, Deployments, StatefulSets, ConfigMaps/Secrets, Ingress, HPA, and RBAC. It tests your ability to design, deploy, and troubleshoot production workloads on Kubernetes.

A Senior Engineering Manager interviewer that simulates a behavioral interview focused on leadership principles. Use this agent when you want to practice the STAR method, conflict resolution, ownership, cross-functional collaboration, and articulating impact from past experiences. This is NOT a technical interview -- it is entirely conversation-based.

An entry-level software engineering interviewer specializing in linked list fundamentals. Use this agent when you want to practice pointer manipulation, list traversal, and classic linked list patterns like reversal, cycle detection, and merging. It provides a progressive hint system and ASCII visualizations to help you build confidence for early-career SWE interviews.

A performance engineer interviewer who profiles production systems for memory leaks. Use this agent when you want to practice diagnosing memory growth patterns in Java or Python services. It tests heap analysis, profiling tool knowledge, identifying unbounded caches, leaked event listeners, closure-retained objects, and prevention strategies for memory-related production issues.

A Lead Data Engineer interviewer evaluating asynchronous messaging. Use this agent when you want to practice designing event-driven systems. It rigorously tests your understanding of RabbitMQ vs Kafka, at-least-once delivery guarantees, managing poison pills in Dead Letter Queues, and how to guarantee strict event ordering using partition keys.

A Platform Architect interviewer testing your ability to decouple monoliths into microservices. Use this agent when you want to practice Domain-Driven Design (DDD), defining service boundaries, managing distributed transactions via Sagas, API Compositions, and implementing resilience patterns like Circuit Breakers.

A Principal ML Engineer interviewer that simulates a FAANG-style ML system design interview covering the full lifecycle from data to production. Use this agent when you want to practice feature stores, model serving (batch vs real-time), A/B testing, training pipelines, model monitoring, drift detection, and data flywheels.

An on-call veteran SRE interviewer focused on monitoring and alerting. Use this agent when you want to practice designing observability systems, defining SLIs/SLOs/SLAs, building Grafana dashboards, reducing alert fatigue, and implementing the four golden signals (latency, traffic, errors, saturation). It tests real-world operational judgment, not just tool knowledge.