Below you will find pages that utilize the taxonomy term “Engineering”
Improve Leadership Presence
URL: https://quantcodedenny.com/posts/leadership-presence/
Introduction
As an IC6 ML Infra Tech Lead, technical expertise alone is not enough. I need to be seen as a leader — someone who drives impact, earns trust, and inspires confidence across teams.
Leadership presence is about how I show up, influence decisions, and make work visible, especially under pressure. This post gives me a daily-ready framework to strengthen my leadership presence, including verbal, non-verbal, and mindset practices.
Scope Better At Work
URL: https://quantcodedenny.com/posts/scope-better/
For a successful tech lead, there are four steps: scope better -> do better -> look better -> connect better.
Scoping work effectively is one of the hardest skills I’ve learned as a tech lead. I frame scoping around four core challenges:
- Identifying high-leverage problems.
- Setting boundaries and protecting focus.
- Aligning stakeholders and expectations.
- Align early, iterate fast.
Using LLMs To Scope Better
I use LLMs to address each core challenge efficiently:
Improve Market Value
URL: https://quantcodedenny.com/posts/improve-market-value/
Working deeply in ML Infra (like Meta or Google) can make your skills feel too specialized. You solve critical problems — but the broader market may not see your full capability. The key is to grow visibility and generalize impact organically, through habits you already do daily.
Core Principles
- Think End-to-End → Connect your work to business goals, reliability, and system health.
- Focus on Non-Urgent Impact → Block time weekly to fix recurring pain or document key learnings.
- Translate to Market Value → Frame results in measurable terms (revenue, cost, scale, reliability).
- Learn and Share → Write short notes or posts to spread knowledge and show thought leadership.
Regular Routine
Weekly Habits
- Learn broadly → Attend 1 SEV or design review; observe recurring problems and system tradeoffs.
- Connect cross-functionally → Chat with 1 XFN lead to understand context and dependencies.
- Reflect & share → Write 1–3 bullet summary of key learning; note patterns, scripts, or principles.
Monthly Habits
- Host & lead → Run 1 design or postmortem discussion; practice influence, articulation, and framing decisions.
- Mentor → Coach 1–2 engineers; amplify impact and demonstrate multiplier behavior.
Quarterly Habits
- Ship a measurable improvement → Deliver 1 end-to-end enhancement; design for scale, reliability, and visibility.
- Summarize impact → Convert results into metrics or story for internal/external visibility.
Focus Blocks & Best Practices
- Protect 1–2 hours weekly for important but non-urgent work: blindspot review, systemic improvements, or skill expansion.
- Frame all incidents/projects with business impact: root cause, mitigation, downstream effect, prevented loss or restored capacity.
- Ask system-level questions before implementation: downstream effects, hidden dependencies, assumptions, failure modes.
- Document & share patterns weekly: recurring issues, scripts, or solutions that others can reuse.
- Use external framing: translate internal improvements into transferable, marketable impact.
Watch Out For
- Local optimizations without system or business context.
- Not documenting key decisions.
- Avoiding cross-team or ambiguous problems.
- Over-relying on internal tech; always extract general principles.
Preapare System Design
URL: https://quantcodedenny.com/posts/prepare-system-interview/
System design interviews test not only technical skills but also strategic thinking, end-to-end ownership, scalability awareness, and cross-team influence.
As a high-end IC6 (between IC6 and IC7), my goal is to bridge execution with strategic design thinking. This blog post consolidates my learnings from system design prep, especially for ML Infra contexts, and is designed to evolve as I add new insights.
System Design Leveling – 35 mins
IC5
- Independently chooses components to tell a coherent story.
- Covers end-to-end design with no significant gaps.
- Discusses tradeoffs and user impact, with prompting.
IC6
- Creates effective designs addressing multiple critical aspects.
- Anticipates problems, including maintainability and organizational challenges.
- Speaks thoroughly on tradeoffs, bottlenecks, and user impact with minimal prompting.
IC7
- Builds sophisticated designs addressing all stated and implicit parts of a problem.
- Proactively considers alternative solutions, immediate vs. long-term issues, and business needs.
- Covers all tradeoffs: technical, user impact, team dynamics, reliability, and sustainability.
IC6 System Design Interview Framework
1. Problem Navigation & Clarification
- “Just to confirm, we need a system for X with Y latency and Z throughput, correct?”
- “What is the expected scale: daily active users, requests per second, or data volume?”
- “Do we need strong consistency, or is eventual consistency sufficient?”
- “Are there privacy or compliance constraints we need to consider?”
- “Let’s break the problem into three main components: ingestion, processing, serving.”
- “I want to highlight dependencies and areas that might require cross-team coordination.”
2. High-Level Solution Design
- “At a high level, the system would look like this: [describe layers or components].”
- “Data flows from ingestion → processing → storage → serving.”
- “Each component is decoupled so that changes in one layer don’t impact others.”
- “Let’s deep dive into the processing layer; we could use batch or stream depending on latency requirements.”
- “Caching frequently requested data improves latency but introduces invalidation challenges.”
- “We should plan for spikes using queues, retries, and circuit breakers.”
- “We can segment functionality so individual components can be updated without impacting the system.”
3. Trade-offs & Technical Excellence
- “We could optimize for latency, but it would increase operational cost.”
- “Sharding improves throughput but complicates cross-partition queries.”
- “Eventual consistency reduces latency but requires careful handling of edge cases.”
- “Using framework X provides distributed fault tolerance; framework Y has lower latency but higher complexity.”
- “Multi-region replication improves availability but introduces latency trade-offs.”
- “Subtle risks include version-to-version schema changes; we can handle them via backward-compatible migrations.”
4. Communication & Influence
- “To summarize, here’s why I made each decision and the trade-offs involved.”
- “From a user perspective, this design ensures low latency for the majority of requests.”
- “I want to check if my assumptions about scale and growth align with your expectations.”
- “I hear your concern; here’s how I’d adjust the design.”
- “Let’s revisit the key bottlenecks and ensure the architecture addresses them.”
- “For future extensions, modular components can accommodate new requirements without major changes.”
Common trade-off
Trade-off | What it Means | Key Considerations / Questions to Ask Yourself |
---|---|---|
Latency vs Throughput | Optimizing for faster responses may reduce total system throughput, and vice versa | How fast must requests complete? Can we batch or async some work? Can we precompute results? |
Consistency vs Availability | Strong consistency may slow responses or reduce availability; eventual consistency improves availability but allows stale data | Does the user expect immediate read-your-writes consistency? Which parts of the system can tolerate eventual consistency? |
Freshness vs Compute / Cost | Frequent updates improve freshness but increase CPU, I/O, or memory usage | How often do users need updated data? Can some updates be async or cached? |
Complexity vs Extensibility | Simple designs are easier to implement, but flexible/modular designs are easier to evolve | Will the system need new features in the future? How can we make it modular without overengineering? |
Storage vs Query Performance | Precomputing or denormalizing improves read performance but increases storage cost | Which data should be materialized? Can we compute some things on demand? |
Generalization vs Edge-Case Optimization | Optimizing for the common case may hurt edge cases; handling every edge case can increase complexity | What’s the typical user scenario? Are there extreme cases that need special handling? |
Observability vs Performance | Metrics, logs, and dashboards aid monitoring but can add latency or storage overhead | What key metrics/SLOs are critical? Can monitoring be async? |
Scalability vs Simplicity | Designs that scale to millions/billions often require sharding, async pipelines, and caches, which increase system complexity | What is the expected growth? Can we start simple and evolve, or must it scale from day one? |
Security / Privacy vs Usability | Strong security or privacy measures may slow performance or complicate user experience | What are compliance or privacy requirements? How does this affect API design or latency? |
Consistency / Correctness vs Cost / Speed | Guaranteeing exact correctness may increase cost or reduce speed | Can approximate results suffice? Which operations require strong guarantees? |
Common techniques
Technique | What it does | When to mention |
---|---|---|
Push + Pull hybrid | Combines fan-out and fan-in based on follower count | If asked about celebrities or skewed followers |
Precomputed feed cache | Stores top N posts for a user | Helps meet strict read latency (P95 < 300 ms) |
Sharded queues | Each user’s feed is partitioned | To scale for millions of users |
Asynchronous write pipelines (Kafka, stream processing) | Fan-out writes done asynchronously | Improves throughput and reduces write blocking |
Local re-ranking | Lightweight ranking at Serving layer | Adjust freshness, unseen content, or last-second boosts |
Known patterns
Pattern | Description / Purpose | Pros | Cons / Trade-offs | Typical Use Cases |
---|---|---|---|---|
Client-Server | Clients send requests, server responds | Simple, clear separation | Can be bottlenecked at server | Web apps, APIs, mobile backends |
Load Balancing / Horizontal Scaling | Distribute requests across multiple servers | High availability, fault tolerance | Complexity in routing, sticky sessions | High-traffic APIs, web services |
Caching | Store frequently accessed data | Reduces latency, lowers DB load | Cache invalidation complexity, stale data | DB queries, API responses, CDN content |
Sharding / Partitioning | Split data across nodes | Scales reads/writes | Harder joins, uneven load | Large user datasets, multi-tenant DBs |
Replication | Maintain multiple copies of data | High availability, disaster recovery | Consistency trade-offs | Multi-region DBs, fault-tolerant systems |
Event-Driven / Messaging | Asynchronous communication via messages/events | Decoupled, scalable | Message ordering, duplication issues | Logging, feature pipelines, order processing |
Microservices / SOA | Decompose monolith into independent services | Independent deployability, scalable per service | Service communication, data consistency | Large apps, ML pipelines, modular backend |
Queueing & Backpressure | Smooth spikes, decouple producer/consumer | Handles high load reliably | Requires monitoring, retry & dead-letter handling | Task queues, ingestion pipelines |
Rate Limiting / Throttling | Control request rates | Protects backend resources | Can block valid requests if too aggressive | APIs, microservices |
Proxy / Gateway | Intermediary for routing, caching, auth | Centralizes cross-cutting concerns | Single point of failure if not highly available | API gateway, reverse proxy, authentication |
Leader Election / Consensus | Distributed coordination, single source of truth | Ensures consistency, coordination | Complexity in distributed systems | Distributed locks, master selection, config |
Observability | Logging, metrics, tracing | Easier debugging and monitoring | Adds overhead, requires discipline | ML infra, microservices, pipelines |
Circuit Breaker / Retry | Protect services from cascading failures | Increases system resiliency | Misconfigured thresholds can block traffic unnecessarily | Microservices, external APIs |
Batch vs. Stream Processing | Process data in chunks vs. continuously | Batch: efficient, stream: low-latency | Batch: latency, Stream: complex error handling | ETL jobs, ML feature store updates, analytics |
Core Principles for System Design
1. Problem Structuring
- Clarify requirements and constraints (functional & non-functional, SLAs, ownership boundaries, future growth).
- Identify critical paths, unknowns, and dependencies.
- Use a structured approach to map problem → components → interactions.
2. Trade-Off Awareness
- Recognize and quantify trade-offs: latency vs. throughput, consistency vs. availability, cost vs. reliability.
- Include business, operational, and cross-team implications.
- IC7-level thinking anticipates tangential trade-offs proactively.
3. Known Patterns & Abstractions
- Apply reusable patterns: caching, sharding, load balancing, replication, event-driven architectures.
- Avoid reinventing solutions; justify deviations clearly.
4. Scalability & Reliability
- Horizontal vs. vertical scaling.
- Fault tolerance, retries, backpressure handling, recovery strategies.
- Monitoring, alerts, and observability planning.
- Consider future-proofing and maintainability.
5. Communication & Influence
- Present a structured narrative: context → problem → options → trade-offs → recommendation.
- Highlight strategic impact, not just technical correctness.
- Prepare concise “elevator pitches” for directors, PMs, and cross-functional teams.
IC6 System Design Practice Checklist
Requirements & Clarification
- Functional vs. non-functional requirements.
- Latency, throughput, SLAs/SLOs.
- Ownership boundaries & team responsibilities.
- Expected growth & future-proofing needs.
High-Level Design
- Identify major components & interactions.
- Map data flow (ingestion → processing → serving).
- Define APIs, interfaces, and abstractions.
- Highlight cross-team dependencies.
Scaling & Reliability
- Horizontal vs. vertical scaling.
- Caching, sharding, partitioning.
- Fault tolerance & retries.
- Observability: monitoring, alerting, metrics.
Tradeoffs & Options
- Pros/cons of architectural choices.
- Cost vs. performance vs. complexity.
- Business impact of each option.
Edge Cases / Failure Modes
- Identify points of failure and mitigation strategies.
- Discuss backpressure, stale data, network issues.
- Recovery, retries, fallback logic.
Influence & Communication
- Summarize decisions for non-technical stakeholders.
- Highlight trade-offs explicitly.
- Show strategic impact and maintain leadership presence.
Leadership Presence
- Lead calmly and confidently.
- Encourage team input while framing final decisions.
- Maintain focus on high-leverage improvements.
Connect Better At Work
URL: https://quantcodedenny.com/posts/connect-better/
Introduction
For a successful tech lead, it usually has four steps: scope better -> do better -> look better -> connect better.
Doing great work is only part of success. My influence grows when others know, trust, and rely on me.
Connecting better at work is most powerful when it becomes a small daily habit — one or two simple actions that naturally build trust, relationships, and impact.
Core Daily Habit
Each day, I focus on one key action:
Look Better At Work
URL: https://quantcodedenny.com/posts/look-better/
Introduction
For a successful tech lead, it usually has four steps: scope better -> do better -> look better -> connect better.
Working hard alone isn’t enough. Leaders and decision-makers are busy — if they don’t see my impact, it might as well not exist.
Looking better at work is not self-promotion. It’s about making my contributions visible, credible, and trusted. I focus on three things:
- Business Impact – What tangible results did I achieve?
- Complexity & Learning – What challenges did I overcome, and what did I learn?
- Credibility – Did the right people notice my work, and did I involve or acknowledge others?
This post gives me a daily-ready framework to apply these principles with minimal thinking.
Stress Less, Lead Better
URL: https://quantcodedenny.com/posts/eq-playbook/
As a tech lead, I want to ease mental stress and handle conflicts effectively. This is my daily runbook for calm, clear, and high-leverage leadership.
Core Principles (Memorable)
- Pause Before Reacting: Avoid knee-jerk responses.
- Listen First: Understand before responding.
- Focus on Outcomes: Prioritize shared goals, not ego.
- Protect Boundaries: Say no or redirect low-leverage work.
Daily Action Routine
- Morning (Start of Day): Review top 3 priorities; decide what to say “no” to.
- Pre-Meeting: Pause, breathe, note intended outcome.
- During Conflict: Listen fully; restate understanding before replying.
- Work Blocks (≈90 mins): Take 5 min stretch/walk break.
- Midday: Hydrate, check posture, reset focus.
- End of Day: Log one win and one boundary I defended.
Difficult Situations & Quick Actions
- Disagreement on Priorities: Frame trade-offs; explain business impact.
- Boundary-Pushing Requests: Acknowledge importance; suggest better owner; offer light support.
- Cross-Team / Peer Conflict: Listen, validate points, defuse tension, propose joint follow-up.
- Escalations from Leadership: Communicate facts clearly; outline immediate + long-term fix.
Show Calm Through Signals
- Speak calmly; tone sets team baseline.
- Pause before responding; silence = confidence.
- Start with the point; avoid long background.
- Use ownership language: “I’ll handle this.”
- Ask curious, open questions: “Can you walk me through your thinking?”
- Reframe issues positively: “We can fix this early.”
Energy & Focus Killers (Clustered)
- Health Basics: Poor sleep, nutrition, hydration, or movement → fatigue & brain fog.
- Scattered Focus: Multitasking & context switching → low efficiency.
- Stress Ignored: Bottling emotions → chronic depletion.
- Weak Boundaries: Overcommitting → diluted impact, burnout.
- Environment: Clutter, noise, bad lighting → lower alertness.
Best Practices (Actionable)
- Sleep & Move: 7–9 hrs sleep; walk/stretch/exercise.
- Eat & Hydrate: Balanced meals; avoid sugar spikes; drink water.
- Prioritize & Batch: MITs / Eisenhower; avoid overcommitment.
- Take Microbreaks: 5–10 mins every 60–90 mins; reflect or journal.
- Optimize Environment: Light, tidy, comfortable.
- Communicate Effectively: Neutral, “we” language, summarize agreements, use Pause → Clarify → Respond → Follow-Up.
Common Pitfalls
- Reacting instantly under stress.
- Treating conflict as win/lose.
- Assuming shared context.
- Taking low-leverage work just to be helpful.
Suggest Without Full Context
URL: https://quantcodedenny.com/posts/suggest-without-context/
A living runbook for learning from and giving suggestions to other teams Why This Matters: Cross-team collaboration is a critical part of tech lead work, yet you’re often asked to give feedback on efforts you don’t fully own or understand.
In these moments, your ability to learn fast, frame thoughtful suggestions, and communicate with empathy defines your credibility.
Good suggestions create momentum and build bridges. Poorly framed ones, even if technically right, can erode trust or stall execution.
Drive V-Team Execution
URL: https://quantcodedenny.com/posts/drive-vteam-execution/
Set LLM context
You are a staff+ engineer leading a cross-functional v-team. Your job is to:
- Align incentives and positions.
- Surface constraints and roadblocks.
- Drive execution while managing bandwidth to avoid over-commitment.
- Keep the big picture in mind and ensure work aligns with org goals.
- Adopt a growth-oriented, solution-focused mindset: think strategically, balance ambition with realism, and maintain team trust and energy.
Your response depends on the command prefix:
Improve Technical Writing
URL: https://quantcodedenny.com/posts/improve-technical-writing/
Improving technical writing at work is not about sounding perfect—it’s about being clear, persuasive, and structured. Many daily scenarios (work chats, proposals, meeting invites, project updates, postmortems) require writing that is both professional and leadership-oriented.
To make this easier, I created a master prompt that turns raw drafts into polished writing. You simply copy the prompt into your LLM, then add your content with a sub-command like `/invite`, `/update`, or `/proposal`. The system automatically transforms your draft into a refined version with staff+ tone, clear structure, and actionable framing.
Vibe Coding
URL: https://quantcodedenny.com/posts/llm-for-vibe-coding/
Set LLM context
You are a senior staff-level engineer with a focus on code quality, scalability, maintainability, and architectural excellence. Your task depends on the command prefix I provide before the content.
Your task depends on the command prefix I provide before the content.
Your response should always be concise, constructive, and provide both critical feedback and an improved, rewritten version where possible.
## Commands & Workflows
/review_pr ⚡️
This is your all-in-one command for a pull request (PR) review. It combines summarization, code critique, and mentorship.
Write Feedback At Work
URL: https://quantcodedenny.com/posts/write-feedback/
Set LLM context
You are a tech lead providing professional feedback. Feedback should be:
- Specific (grounded in clear examples)
- Balanced (strengths + areas for improvement, unless not appropriate)
- Action-oriented (gives guidance for next steps)
- Succinct & professional (not overly wordy, but respectful)
/peer – Peer Feedback
Use: Generate professional, structured feedback for a peer (same level or cross-functional). Goal: Highlight their impact, technical contributions, collaboration, and areas for growth using specific examples. Tone: collegial, constructive, respectful, professional Structure & Guidance: