Expand 2026 interview prep guide with complete practices and required skillsets

README.md

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 # tech2026
-Interview prep for 2026
+
+Interview prep for 2026.
+
+## Practices for a 2026 Tech Interview
+
+- Build a 6-8 week study plan with weekly targets for algorithms, system design, and behavioral prep.
+- Practice coding interviews in timed sessions (35-45 minutes) and explain tradeoffs out loud.
+- Use mock interviews (peer + AI + platform-based) and track recurring mistakes in a review log.
+- Master problem-solving frameworks: clarify requirements, discuss edge cases, propose brute force, optimize.
+- Practice writing production-style code: naming, modularity, input validation, and testability.
+- Rehearse debugging workflows: reproduce, isolate, inspect assumptions, and communicate fixes clearly.
+- Prepare STAR stories for leadership, conflict, ambiguity, impact, and failure/recovery examples.
+- Research company stack, product, and interview loop format; tailor examples to role expectations.
+- Run system design drills with explicit requirements, APIs, data models, scaling bottlenecks, and observability.
+- Train communication habits: summarize often, ask clarifying questions, and narrate decisions calmly.
+
+## Skillset Needed for 2026 Interviews
+
+### Core Coding Skills
+
+- Data structures: arrays, strings, hash maps, stacks/queues, trees, heaps, graphs.
+- Algorithms: sorting, searching, sliding window, two pointers, recursion, BFS/DFS, dynamic programming.
+- Complexity analysis: big-O runtime and memory, plus practical performance tradeoffs.
+
+### Software Engineering Fundamentals
+
+- Clean code principles, modular design, testing strategy, and refactoring.
+- API design fundamentals (REST/gRPC), versioning, and backward compatibility.
+- Databases: SQL modeling/indexing and NoSQL consistency/partitioning tradeoffs.
+- Concurrency basics: async patterns, race conditions, locks, queues, and idempotency.
+
+### System Design and Platform Knowledge
+
+- Distributed systems basics: caching, load balancing, sharding, replication, and failover.
+- Reliability: monitoring, alerting, SLOs/SLIs, incident response, and rollback plans.
+- Cloud fundamentals: compute, storage, networking, containers, and CI/CD pipelines.
+- Security basics: authn/authz, secure secrets handling, input validation, and least privilege.
+
+### AI-Era Readiness (2026)
+
+- Effective AI-assisted development workflows (prompting, verification, and review discipline).
+- Evaluating AI-generated code for correctness, security, and maintainability.
+- Practical understanding of LLM-enabled features, embeddings, and retrieval patterns.
+- Responsible AI fundamentals: privacy, bias awareness, and safe deployment guardrails.
+
+### Communication and Collaboration
+
+- Strong written and verbal communication during coding and design discussions.
+- Ability to justify tradeoffs with business impact, not just technical preference.
+- Product thinking: user outcomes, metrics, and iterative delivery.
+- Collaboration skills: code reviews, cross-functional alignment, and stakeholder updates.