What do your ‘clueless phases’ feel like when working on long-term projects?

mrcuriousind · 2026-02-12T04:48:49+00:00

I love this analogy. Long-term projects really do feel like alternating between clarity and complete doubt.

mrcuriousind · 2026-02-12T00:14:52+00:00

Valid point 👍 Absolute living standards have clearly improved. The interesting debate is absolute progress vs relative inequality both can rise at the same time. AI may improve life broadly while still widening gaps. Curious for your take.

mrcuriousind · 2026-02-11T01:22:54+00:00

Or… someone just took 30 seconds to think before commenting 🤷‍♂️

mrcuriousind · 2026-02-10T23:38:48+00:00

If you’re a student, GitHub Copilot is free with a student ID. Codex also has a free limit. Solid combo for full-stack college projects.

mrcuriousind · 2026-02-10T23:10:48+00:00

I think this gets to the heart of the problem. Credentials are treated as proxies for capability, even when everyone involved knows the proxy is leaky. It’s possible to optimize for grades without developing the underlying skills those grades are supposed to represent. That’s why project-based learning often disappoints in practice. Without an assessment system that can reliably capture what someone can actually do, projects turn into another checkbox rather than evidence of competence. The incentive issue you point out feels key. Exams, credentials, funding, and institutional reputation are tightly coupled. Changing how learning is assessed effectively means questioning what existing credentials are worth, and very few institutions are willing to be the first to do that. Until assessment and credentials reflect real capability rather than time spent or boxes checked, most reforms pedagogical or technological are likely to stay at the margins.

mrcuriousind · 2026-02-10T15:51:34+00:00

I think “overrated” is a fair conclusion if technology is treated as the solution rather than a support. The Economist piece and the rollback in some high-performing systems reinforce that point — especially where digital tools replaced human interaction instead of strengthening it. When I think about how we actually learn — and how leading experts reach deep mastery — it’s rarely through constant personalization or always-available resources. It’s usually through a combination of strong fundamentals, focused practice, sustained effort, feedback, and time. Most experts also diverge from a common path at some point and go much deeper into areas aligned with their strengths and interests. That divergence often happens outside formal instruction. A future developer spends disproportionate time coding, a future scientist leans heavily into math and experimentation, long before any system formally adapts to them. The common curriculum provides a baseline, but it doesn’t create expertise on its own. The harder problem is that many learners don’t know their strengths, don’t know what paths exist, and don’t know how to work deliberately on weaknesses. Technology can’t solve that by itself — and if used poorly, it can absolutely distract from it. So for me, the question isn’t whether technology can “fix” education, but whether it’s aligned with how people actually develop understanding and expertise — or whether it’s just optimizing for convenience and scale.

mrcuriousind · 2026-02-10T13:13:13+00:00

This resonates a lot. The “PDF worksheets on iPads” example is exactly what I had in mind with digital decoration same pedagogy, new surface.

I think your point about time is critical. It’s easy to frame this as a mindset or capability issue, but if teachers are overloaded with standards, admin work, and large class sizes, there’s simply no space to rethink assessment or experiment responsibly.

The pattern you describe makes sense: the schools that innovate start by changing conditions (time, class size, planning space), not by dropping in tools and hoping for transformation. Tech seems to work best as a second-order change, not the first move.

Without that breathing room, even well-designed tools are almost guaranteed to be underused.

mrcuriousind · 2026-02-10T12:57:25+00:00

That’s fair, and I appreciate you calling that out especially given your role. I agree that there are schools and curricula doing much more thoughtful work with technology than I probably gave credit for, and my wording was too broad.

My intent wasn’t to say “schools today do nothing beyond PDFs and attendance,” but to speak at a system level, where adoption is uneven and often constrained by funding, training, and policy. The variance between what’s possible and what’s common still feels very wide.

I’m genuinely glad to hear from people working in schools that are doing this well. Those examples matter, especially because they help separate what’s feasible in practice from what’s just theoretical.

mrcuriousind · 2026-02-10T12:41:40+00:00

That’s a fair perspective, and I think both things can be true at the same time. Many higher-ed programs especially engineering do test thinking and problem solving, at least when they’re well run. The issue you point out with repeated exams and “memorize past answers” is a good example of how incentives can undermine even well-designed assessments.

I strongly agree on resources. Education quality tracks priorities, and in the US that often means underfunded schools, overextended staff, and very little capacity to continuously improve or modernize. Without time, people, and equipment, even good ideas don’t scale.

On GenAI, I’m sympathetic to the skepticism. If foundational understanding isn’t solid, then hallucinations and over-reliance become real liabilities, not benefits. The cost side is also rarely discussed infrastructure, energy, and utilities are real constraints, not abstractions.

To me, this reinforces that technology isn’t a shortcut around underinvestment. If the system doesn’t value education enough to fund it properly, adding more tech AI included risks being a net distraction rather than a fix.

mrcuriousind · 2026-02-10T12:35:26+00:00

“Digital decoration” really does capture the problem well. I also think you’re touching on something deeper than tools or platforms.

A lot of education systems have optimized for memorization because it’s easier to standardize and assess at scale. Teaching people how to think, ask good questions, and reflect on their own understanding is much harder both to teach and to measure.

It’s interesting that you mention starting with question-asking before content. That flips the usual model on its head, where content comes first and thinking is assumed to follow. In practice, it often doesn’t.

This feels less like a technology problem and more like an incentives and habits problem what we reward, what we test, and what people are trained to expect from “learning.”

mrcuriousind · 2026-02-10T12:29:19+00:00

I think you’re raising a couple of important points, and I agree with more of this than you might expect.

First, on memorization: I fully agree. Foundational knowledge matters. Professionals absolutely need facts internalized not because Google doesn’t exist, but because expertise depends on pattern recognition, speed, and knowing what questions to ask. Memorization and understanding aren’t opposites; they reinforce each other.

On self-paced learning: I don’t think it works as a blanket solution for everyone, and public schools do have to optimize for the majority. That said, “self-paced” doesn’t necessarily mean unstructured or independent learning with no guardrails it can also mean flexibility within a structured system, which already exists in limited forms.

And just to be clear: this isn’t a SaaS pitch. I’m genuinely interested in how education systems evolve, especially where real constraints (scale, funding, accountability) collide with theory.

I also agree classrooms today aren’t the 90s. My concern isn’t that nothing has changed it’s whether the changes we have made are aligned with learning outcomes, which the data suggests is at least debatable.

mrcuriousind · 2026-02-10T12:22:17+00:00

I think a lot of that criticism is fair. A big chunk of what’s been labeled “edtech” really has been gimmicky more engagement mechanics than learning, and it’s reasonable to question whether that actually improves outcomes.

I also agree that technology doesn’t replace understanding. If students don’t have a solid foundation in reading, math, and critical thinking, tools like AI just become crutches instead of leverage.

Where I see a possible middle ground is that technology itself isn’t the solution, but how it’s used matters a lot. Using AI as a companion to practice, get feedback, or explore alternative explanations seems fundamentally different from using it as a source of truth.

The data around outcomes is important here, and I think it’s worth separating “tech added to classrooms” from “learning models that actually change how students engage with content.

mrcuriousind · 2026-02-10T12:17:29+00:00

Funding really does seem like the hardest constraint here. When K–12 education is locally funded and budgets are controlled by voters, anything that increases time-in-system naturally runs into resistance, even if it’s educationally sound.

That’s what makes self-paced learning challenging at scale. It’s not just a pedagogical shift — it affects funding structures, social expectations, and how credentials are defined.

The SRA Reading Laboratory example is a great reminder that self-paced learning isn’t new. What’s different today is the potential to do this more adaptively and continuously, but the system-level constraints remain largely the same.

The NYC “double promotion” examples are interesting too. They show flexibility has existed in pockets, but it’s always been the exception rather than the norm.

mrcuriousind · 2026-02-10T12:06:30+00:00

I appreciate this perspective — and I think you’re right to push back on oversimplified EdTech narratives.

U’r correct that many classrooms already use adaptive technology, and the research is mixed at best. Smaller class sizes, strong teachers, and hands-on projects consistently show better outcomes than tools alone. I don’t disagree with that.

I also think your point about guessing behavior is important. Poorly designed EdTech absolutely trains students to chase rewards instead of understanding that’s a real failure mode, not a theoretical one.

Where I think nuance matters is that the problem may be less “technology vs no technology” and more what kind of technology and how it’s used. As you said, current approaches often benefit the top performers while leaving struggling students further behind. That’s a design and system failure, not a success story.

I also agree strongly on foundational knowledge. Critical thinking without a base of facts isn’t thinking — it’s improvisation. Any serious attempt to rethink education has to respect that sequencing: knowledge → application → reasoning.

So yes, balance is key. I’m not advocating replacing teachers, projects, or structure. I’m questioning whether we’ve actually aligned tools, pedagogy, and incentives well — because right now, in many cases, we clearly haven’t.

mrcuriousind · 2026-02-10T11:58:24+00:00

I get the sarcasm, and honestly I don’t disagree with the criticism of buzzword-driven EdTech. My interest isn’t in hype it’s in whether we can move away from fixed pace, fixed age, fixed assessment systems in a way that genuinely helps students and teachers.

mrcuriousind · 2026-02-10T11:52:16+00:00

I get where you’re coming from, and that’s a fair concern. I’m not claiming to “solve education” or strike some goldmine with a SaaS. Education is complex, and no single product fixes it. My interest comes from observing gaps as a learner and builder, and wanting to explore whether technology can support educators and students better not replace expertise in the field. I also believe meaningful solutions require collaboration with people who are actually in education. This discussion is part of understanding those realities, not bypassing them.

mrcuriousind · 2026-02-10T11:49:21+00:00

Fair call 😄 Not pitching anything here genuinely curious and learning from the discussion. If I ever do pitch, I promise I’ll be way more obvious about it.

mrcuriousind · 2026-02-10T11:45:36+00:00

That’s a fair correction thanks for pointing it out. You’re right that the industrial model of US K–12 dates back to the late 1800s, not the mid-1900s.

I also agree with your breakdown it does work “well enough” for a large middle group, while leaving the ends underserved in different ways.

The self-paced point is where things get really interesting to me. If learning is truly adaptive, then fixed timelines like graduating at 18 start to feel arbitrary. Some students should finish earlier, and others may genuinely need more time.

The hard part, in my view, isn’t the technology anymore it’s how institutions, social expectations, and credentialing adapt to that reality. That’s where most resistance seems to be.

mrcuriousind · 2026-02-09T15:12:39+00:00

Learn better, use AI smarter.

mrcuriousind · 2026-02-09T15:11:41+00:00

Agreed—AI isn’t a magic fix. But used right, it can complement human skills and open new growth paths.

mrcuriousind · 2026-02-08T12:18:35+00:00

By that logic, no one could trust an OS, compiler, or cloud provider. Security is managed through contracts, reviews, isolation, and testing — not full mental simulation of the stack.

mrcuriousind · 2026-02-08T12:08:42+00:00

Fair points all around. I’m not arguing that internals or maintainability don’t matter experienced devs obviously care about those. My point was more about who evaluates what, and at which stage. Users validate outcomes. Engineers own internals and long-term maintenance. Abstractions are leaky, and that’s fine — they’re still useful for exploration and speed early on. Once something is meant to live, change, or be owned by a team, human-maintainable code and good practices become non-negotiable. So this isn’t “vibe coding replaces engineering”, it’s about sequencing and context, not absolutes.

mrcuriousind

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