Paweł Kieliszczyk

Imagine you just joined Google as an SWE. It’s your first week, and you’re overthinking everything. You’re surrounded by world-class engineers, new systems, and an overwhelming urge not to mess up. The pressure to prove yourself is real, and so is the anxiety…so what should you do? Over the years, I’ve moved across orgs, teams, and sometimes, entire companies. Here’s exactly what I did (and still do) to ramp up faster and enjoy the process without letting anxiety win → Don’t let yourself stay stuck. If you’re blocked for more than 30 minutes, ask for help. Share what you’ve tried, show initiative, and intent. → Read way more code than you’re assigned. Dive into related modules, historic PRs, and old design docs. The context you gain helps you spot patterns and avoid mistakes. → Ask about the story behind the system. Find out why things are built a certain way, what’s failed before, and what’s on the roadmap. Understanding the “why” beats memorizing the “what.” → Volunteer for unglamorous work. Take ownership of tests, docs, or nagging integration bugs. This is where you quietly learn the most and build your internal network. → Offer help before you’re an expert. Chime in when you see questions, review PRs, or share a script. Even small contributions get you noticed for the right reasons. → Connect with skip-levels and cross-team leads. Set up short intros to learn about the broader vision and team priorities. You’ll spot opportunities to add value beyond your immediate tasks. → Document what you learn as you go. Share notes, update READMEs, or post quick how-tos in team channels. Your future self and your teammates will thank you. → Shadow someone during incidents or launches. Sit in on debugging sessions or war rooms, even if you’re just observing. You’ll see how senior folks think, react, and communicate under pressure. → Keep a running list of “how did that break?” moments. Every time you see a system fail or a hotfix go live, dig in. Reverse-engineering past problems is the fastest way to understand the architecture. → Show up with curiosity and intent, every day. Don’t just tick off JIRA tickets. Look for the bigger picture. People notice when you genuinely want to learn and contribute, not just “do your job.” Some orgs assign mentors, some don’t. Either way, these habits put you in the driver’s seat. Ramping up is less about brilliance, more about consistent intent. And the ones who learn this early end up leading teams later.

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Everyone software engineer wants to do the cool stuff. – AI features – microservices at “FAANG scale” – real-time streaming and zero-downtime everything But this Avocado represents what being a Software Engineer looks like. As a software engineer, 80% of your job is fixing: → flaky CI and brittle tests → nulls, off-by-one errors, and bad defaults → time zones, locales, and encoding weirdness → dependency hell and version conflicts → schema migrations, rollbacks, and backfills → race conditions, deadlocks, and retries that storm → logs that say nothing and alerts that scream everything → pagination, idempotency, and rate-limit corners And guess what? Without this work: → launches slip or roll back → dashboards lie, and incidents pile up → customers churn, trust drops, weekends burn The quality of your features depends on the quality of your foundations. Respect both parts of the job.

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90% of engineers using AI coding tools are doing it wrong. They're treating AI like a code monkey. Fire prompt → Get code → Accept all changes → Ship. That's why we see 128k-line AI pull requests that became memes (look this up, it's a fun read). After spending quite a bit of time using AI dev tools, I discovered the real game isn't about generating more code faster. It's about rapid engineering while managing cognitive load. My workflow now: 1. Start with AI-generated system diagrams 2. Ask questions until I understand the architecture 3. Create detailed change plans 4. Break down into AI-manageable chunks 5. Maintain context throughout This isn't coding. It's orchestration. The best engineers aren't typing anymore. They're conducting symphonies of AI agents, each handling specific complexity while the human maintains the vision. Think about it → We're moving from IDEs to "Cognitive Load Managers." Tools that auto-generate documentation, visualize dependencies in real-time, and explain impact before you commit. The future isn't AI writing code. It's AI helping you understand what code to write. The billion-dollar opportunity? Build the tool that turns every engineer into a systems architect who happens to code. We're not being replaced. We're being promoted. Who else sees this shift? #AI #SoftwareEngineering #DevTools #FutureOfCoding #TechLeadership

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“I pressed the button, broke the system, and caused the impact. Will this impact my performance or promotion?” asked a junior engineer. The answer is no. But there is nuance: At Amazon, we have a process to learn from mistakes. It uncovers gaps instead of pointing fingers. That might be rare, even unique to Amazon, but it’s how it should be everywhere. It isn’t a free pass to operate recklessly or avoid responsibility. No matter how careful and prepared we are, mistakes will eventually happen. What matters is how you show up afterward. First, did you escalate early? Did you bring in the right stakeholders quickly and explain what was happening with honesty? Second, did you go as far as needed to fully understand what failed and why? Last, did you make sure the right fixes were implemented and mechanisms created? Did you personally ensure those action items were closed? Making mistakes is human. Turning them into learnings that strengthen systems and prevent repeats is growth. Making sure everyone feels safe to be fully honest in this process is great management. Applying those learnings across larger organizations and the company is leadership.

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Your PR got blocked during the code review.  You have about 20 comments, most of which are minor suggestions.  The deadline is near, and your manager just asked for an update. Here’s what you shouldn’t do in this situation: - Take it as a personal attack. - Get defensive or start justifying every little thing. - Respond emotionally or rush to reply. - Blame others for missing details. - Drag out the discussion in comments. Instead, do this: - Stay calm and treat it as constructive feedback. - Go through the comments with an open mind. - Ask for clarification where needed. - Address the issues in a clear, focused way. - Propose a quick call to resolve any bigger concerns. Comments are great for feedback and documenting ideas, but they don’t communicate the tone or how you want to say it. While working in a team, it’s not just about what you say but also how you say it. A short conversation can clear up misunderstandings in minutes that might take hours to hash out through written replies. Sometimes, a quick chat leads to a much smoother and faster resolution.

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