How to Solve Real Problems

𝗕𝗶𝗴 𝗣𝗿𝗼𝗯𝗹𝗲𝗺𝘀 𝗗𝗼𝗻’𝘁 𝗡𝗲𝗲𝗱 𝗕𝗶𝗴 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀. 𝗧𝗵𝗲𝘆 𝗡𝗲𝗲𝗱 𝗦𝗺𝗮𝗹𝗹𝗲𝗿 𝗣𝗿𝗼𝗯𝗹𝗲𝗺𝘀. —𝘮𝘺 𝘱𝘦𝘳𝘴𝘰𝘯𝘢𝘭 𝘷𝘪𝘦𝘸; 𝘰𝘱𝘪𝘯𝘪𝘰𝘯𝘴 𝘢𝘳𝘦 𝘮𝘺 𝘰𝘸𝘯. 𝙈𝙤𝙣𝙨𝙩𝙚𝙧𝙨 𝙖𝙧𝙚 𝙟𝙪𝙨𝙩 𝙥𝙪𝙯𝙯𝙡𝙚𝙨 𝙬𝙞𝙩𝙝 𝙗𝙖𝙙 𝙋𝙍. When I face an overwhelming problem—the kind that demands “bold visions” or “massive refactors”—I stop. Instead, I ask: What’s the smallest meaningful unit in this chaos? (𝘍𝘪𝘳𝘴𝘵 𝘱𝘳𝘪𝘯𝘤𝘪𝘱𝘭𝘦𝘴.) Can I carve the monster into smaller, digestible creatures? What’s one piece I can fix today—without waiting for permission? This isn’t theory. It’s how I solve real SDV problems. 𝗔 𝗥𝗲𝗮𝗹 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: 𝗗𝗶𝘀𝘀𝗲𝗰𝘁𝗶𝗻𝗴 𝗖𝗿𝗼𝘀𝘀-𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻 (Multiple runtimes, domains, SoCs—a beast, until disassembled.) 𝗧𝗵𝗲 𝗦𝗰𝗮𝗹𝗽𝗲𝗹: → Single source of truth for communication contracts. → IDLs that scale across runtimes and protocols (evaluate ruthlessly). → Protocol mapping — right tool for each path: - AUTOSAR → Performance Core: SOME/IP (stateful) or PDUs (deterministic) - Performance Core → Infotainment: gRPC over TCP/IP (reliable services), or UDP for low-latency streams - Intra-Performance Core: Shared Memory IPC (zero-copy, no serialization) → Data brokers? Only where unavoidable — and auto-generate them. → Software structure: isolate building blocks like a virologist. 𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹: → Build reference platforms in parallel — virtual and real. - Virtual first: simulators/VMs to validate logic early - Hardware second: test timing, I/O, Layer 2 quirks → Never wait for full hardware. It’s expensive. And late. 𝗕𝗿𝗲𝗮𝗸 𝘁𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 — 𝗯𝗲𝗳𝗼𝗿𝗲 𝗶𝘁 𝗯𝗿𝗲𝗮𝗸𝘀 𝘆𝗼𝘂𝗿 𝘁𝗲𝗮𝗺. #SoftwareDefinedVehicle #SystemArchitecture #ShiftLeft #Middleware #EmbeddedSystems

Machine learning education is broken, especially for those who aspire to start solving real-world problems at a company. Most classes, courses, and books start with a dataset and show you how to train a model. dataset → model This is, at best, 5% of the work you'll need to do. Real-life problems never start with a "dataset," and they never end after you finish training a model. I've never seen a company with a "dataset" ready to go. In fact, most companies don't even have any data at all. It's your job to determine what data you need and how to collect it. Here is a simplified process that will give you a better idea of how people solve real problems: problem → framing → data → model → feedback → repeat Before understanding the problem and deciding how you'll frame it to solve it, you can't start thinking about datasets. A few other challenges: 1. How do you get data from its source? 2. Is the data diverse enough to solve the problem? 3. Do you have enough data? 4. How is the data biased? 5. How frequently does the data change? 6. How sensitive is the data? 7. Are there missing, inconsistent, or incorrect values? 8. How noisy is the data? 9. How can you trace back every piece of data to its source? 10. Are there any legal restrictions on the use of the data? 11. How do you scale as data grows? 12. How quickly does the data become stale? Building systems that work requires a lot of effort. I wish more people would talk about this.

Get rid of long lasting problems in business or leadership Most people don’t realize this, but one of the biggest reasons problems go unresolved, especially in leadership and business is because we mistake the characteristics of a problem for the root cause. - We see poor results and assume laziness. - We notice slow progress and blame the system. - We sense tension in a team and chalk it up to personalities. This could be more symptoms, and solving the symptoms aren’t solutions. Why? Because they’re signals. And if you treat the symptom, the real issue keeps growing underground. Let me give you a simple but powerful tool: Deploy the “5 Whys” technique. You experience a problem, and instead of jumping to fix it, you ask “Why?” not once, but five times. Each answer takes you deeper. For example: Problem: A project missed the deadline. 1. Why? Because tasks took longer than expected. 2. Why? Because there was confusion about the priorities. 3. Why? Because team members didn’t get clarity during the kickoff. 4. Why? Because the manager assumed everyone was on the same page. 5. Why? Because the process lacks a clear communication structure. Now you’ve got something real to work with. Whether you’re leading people or managing your own growth, surface-level fixes will always create repeat problems. Go deeper. Ask better questions. That’s how you get lasting solutions. Now, what’s one ongoing issue you’ve been “fixing” but never solved? Try the 5 Whys on it, and if you need help walking through it, I’m just a message away.