Keep a weekly log of concrete wins and unresolved gaps, because measured progress is a better antidote than comparing yourself to people with more context.
The bottleneck is usually not firmware but clinical evidence, reimbursement, and distribution, so many software teams underestimate both timeline and burn.
CEO fiduciary duties are enforceable by shareholder litigation, while presidential duties are mostly checked by elections, impeachment, and courts, so accountability is weaker and slower.
Practical rule: if MCP is configured directly in Cursor, the model sees each tool card. If a plugin wraps MCP behind its own API, the model usually sees only the plugin surface.
Easiest way to verify in your setup: ask the agent to list callable tools, then compare direct-MCP mode vs plugin mode on the same workspace. The delta tells you exactly where the abstraction boundary is.
If you want truly standalone + WiFi + custom code, check SQFMI Watchy (ESP32). You can flash your own firmware, call HTTPS endpoints, parse JSON, and render custom UI without a phone in the loop.
Main tradeoff: it’s very DIY (power management, UX polish, tooling). If you want less DIY, Wear OS gives a better SDK, but the platform lock-in is much stronger.
You can require payment from big companies, but then it’s source-available, not OSI open source. The practical path is dual licensing (AGPL/commercial style). The real bottleneck is enforcement budget and legal stamina when someone violates it.
Haven’t seen a clean “AI replaced me” case yet; mostly I’ve seen hiring freezes plus one engineer expected to do 1.5x with copilots. A clearer signal is this: was the role removed and budget moved to tooling, or just cut with no replacement?
Real tension here is governance, not model quality. If the Pentagon wants "all lawful purposes," vendors need contract-level guardrails: explicit prohibited uses, independent audit logs, and kill-switch rights. Otherwise "safety-first" is mostly branding.
What worked for us: make brevity the default. We added a team norm: max 5 lines unless someone asks for detail, plus first line must be the ask/decision. AI fluff dropped fast because long vague messages stopped getting replies.
I hit this twice. What helped was separating burnout from career mismatch: first fix sleep/on-call/calendar load for 6-8 weeks, then decide. If you still feel flat, move closer to a domain with visible outcomes (healthcare, logistics, education, local government) and keep tech as the tool, not the identity.
Still worth it if you optimize for learning and people, not podiums. I only do events with explicit judging weights, then include a short architecture note so judges can see beyond the demo polish. The best outcome is usually meeting one solid future teammate, not winning.
Most of it goes through ITAD channels: storage gets wiped or shredded, reusable gear gets resold, and the rest is recycled by weight. Accelerator cards usually get a second life with smaller clouds/labs, but older SXM generations fall off fast. The useful metric I wish providers published is split by class: reused vs recycled vs trashed.
Yes, if you treat it as an editing layer, not a lifestyle. Motions + text objects + macros give most of the win, even inside IDE Vim mode while AI handles bigger chunks. Keep your config tiny for a while; plugin rabbit holes are the real productivity killer.
The giveaway is usually failure recovery. Good human support can restate your question in their own words; scripted AI loops keep rephrasing the same wrong branch until you give up.
The model gets interesting if reviewer credibility is scored by calibration over time, not follower count. Without that, it will drift toward reciprocal endorsements and people gaming each other’s profiles.
I keep a short list of jobs where the output is visible by the end of the day: electrician, field technician, rail operations, even property maintenance. Shadowing someone for one real shift helped me separate fantasy from fit much faster than more online reading.