Launch HN: Bloomy (YC S26) – AI-powered mastery learning for K-12
RU version is available. Content is displayed in original English for accuracy.
How it works: we diagnose students’ skill gaps, place them on personalized learning paths, and give them standards-aligned lessons and a Socratic AI tutor that scaffolds their learning without just giving away the answer.
The goal is to solve the Bloom 2-sigma problem (https://en.wikipedia.org/wiki/Bloom%27s_2_sigma_problem) with AI.
Short launch video: https://tinyurl.com/bloomylearning
Longer product demo: https://youtu.be/XHvoKt6qMeo
Families access for Bloomy: https://bloomylearning.com/families
I started as a teacher. I taught 7th-grade English and writing with Teach For America, and every day I struggled to deliver differentiated instruction to 30 students with 30 different sets of needs. Some students needed remediation, some needed acceleration, and many needed a tutor sitting next to them helping them reason through the next step. Benjamin Bloom’s two-sigma result—that one-on-one tutoring can produce much better outcomes than conventional classroom instruction—always felt intuitively true to me. The hard part was making that kind of attention affordable and available to every child.
Then AI changed the cost curve. When I saw schools such as Alpha organize academics around mastery rather than seat time, the model clicked. If you’ve heard of Alpha School, that is directionally the kind of learning model that inspired us. But I kept thinking about the families and schools that already exist: homeschool families, microschools, hybrid schools, and regular classrooms where most children are today.
Most students and teachers see learning gaps at the wrong resolution. They get a grade, percentile, benchmark score, or broad standard—not “this is the next skill this student should learn.” Existing personalized-learning products often feel like digital worksheets: they provide plenty of practice, but not much diagnosis or teaching. Very few have AI tutors providing the core instruction. Bloomy starts with a diagnostic—we integrate with third-party assessments and provide our own—and creates a learning path for each student. Students work one skill at a time, receive a short lesson, practice at an adaptive difficulty, and only move forward after demonstrating at least 90% mastery. The learning path updates as the student works, based on their performance and our knowledge graph of skill prerequisites (built in collaboration with Learning Commons / Chan Zuckerberg Initiative).
Each skill has three stages. Base Camp teaches the concept with worked examples. Climb provides guided practice and Socratic support. Summit is an independent ten-question mastery assessment with no hints or AI assistance. Students need to achieve 90% on the Summit to advance. If they struggle too much, they’ll be routed to a different skill better suited for their level.
BloomyBot is not a blank chat window but rather a live, interactive, and observant digital tutor. During practice, it receives the active passage or problem, the question, the student’s attempt, an authored explanation, and relevant misconception context. It follows a scaffolded tutoring ladder: first asking what the student tried, then pointing toward the concept, suggesting a strategy, working through one step together, and only providing heavier scaffolding after the student has struggled, adapting to and learning from the student along the way. Students can interrupt it, and we’ve begun to roll out multilingual support for Spanish, French, and a few other more niche languages that customers have asked for.
We currently use a variety of Anthropic and OpenAI models for BloomyBot. The tutor is restricted to the current lesson, redirects unrelated questions, limits conversation length, and is unavailable during mastery assessments. The language model does not choose the curriculum or decide whether a student has mastered a skill.
That separation is important. A conventionally “helpful” AI response can be a bad tutoring response: if it gives away the answer, the student completes the task but may not learn anything. Our goal is not to build a homework-answering chatbot. It is to put AI inside a structured loop of diagnosis, instruction, practice, feedback, and independent mastery.
LLMs can still be wrong, and we do not claim our constraints eliminate that. We reduce the surface area by grounding BloomyBot in authored lesson content, keeping it on topic, logging conversations, and removing it from assessments. Teachers and parents can review tutoring activity, students can report problems, and safety signals trigger human alerts and a backup audit. We also do not see Bloomy as a replacement for teachers, parents, or human tutors. A good human tutor is better. The narrower question we are testing is whether, during a bounded learning session a student would already be doing, a context-aware tutor can provide better help than static “correct/incorrect” feedback. Longer term, the question becomes more whether a student would perform better with one-on-one AI tutoring (at least in certain aspects of the curriculum) than with many-to-one instruction in a medium- or large-sized classroom.
Bloomy is now being used across several settings: traditional districts, charter schools, hybrid schools, microschools, homeschools, and families looking for additional academic support. In an early pilot at a charter school in Massachusetts serving ~150 students in grades 6 through 8, students averaged roughly 1.8 times the expected winter-to-spring NWEA MAP growth. This was an observational pilot, not a randomized study, so we treat it as an encouraging signal rather than proof that Bloomy caused the difference.
Parents and teachers can see what a student has mastered, what is in progress, and where support may be needed. We have found that adults generally do not want another generic score; they want to know which small number of skills deserve attention this week.
Bloomy makes money through family subscriptions and school licensing. ELA costs $39/month or $279/year per learner, and Writing Studio costs $19/month or $139/year. Math is scheduled to launch July 31 at the same price as ELA. Schools and microschools pay per student, with pricing varying by subject coverage, enrollment, rostering, and implementation needs.
Because children use Bloomy, we collect learning responses, progress data, and tutoring conversations. We do not sell personal information, use child data for behavioral advertising, or permit model providers to train general-purpose models on identifiable child data sent by Bloomy. We have Zero Data Retention agreements with both Anthropic and OpenAI. Parents and schools can request access, export, correction, or deletion under the applicable account or school agreement.
More background on me: after Teach For America, I taught and designed GMAT and GRE curriculum for Manhattan Prep / Kaplan, led the driver acquisition team for Lyft’s New England markets, completed an MBA at Stanford, and led AI transformation projects at McKinsey (so when models finally became good enough this past January to achieve the kinds of things I am pursuing with Bloomy, I was in the right place at the right time to begin building). Bloomy brings together the different parts of my career that I care most about: educational outcomes, learning design, building products, and getting useful technology into people’s hands.
I’d especially value feedback from parents, teachers, engineers working on child-facing AI, and people who have built tutoring, assessment, or adaptive-learning systems. Does the separation between guided AI help and independent mastery make sense? Where do you see the greatest potential with AI in education? Where are our safeguards insufficient? What evidence or product behavior would you need to trust something like this with a student?
Certainly there are many dangers and pitfalls we must beware of, too, but I believe we can really move the needle in K-12 (for the first time in a long time) if we use AI responsibly and intelligently.
Discussion (85 Comments)Read Original on HackerNews
You've chosen to use the most generic AI-generated prose, when you could have licensed or hired writers to craft thoughtful, rich passages. I doubt you've consulted any serious standardized test item writers in the construction of what is essentially a standardized test item-based curriculum. This is the pedagogical equivalent of a Lunchable--mass produced, wrapped in plastic, and basically nutrition-free.
- It looks like you are gating family access to K-3 for now and I think that's right. I wouldn't really be comfortable giving my first-grader a live chatbot. Maybe I would think about whether there are other non-persona modalities that could still be self-directed (i.e. I am uncomfortable with a chatbot interface on this for a six year old but gamified flash cards with options could be different).
- I think the other issue is with motivation. I have various duct-tape versions of these types of agents and the thing about it is if you're doing the learning right it can be HARD. So I would think about using motivational interviewing or other techniques to help keep the user coming back and motivated.
- I would really think about the assessments here too. Many people are worried about LLMs ruining student evaluations, but if you could bake in reliable, flexible exams that gauge user progress (even for something like a "Did you read this" quiz) I would bet teachers would like it. There is likely so much you could do on student progress observability and e.g. structuring team-based projects or having targeted student working groups to hash out hard concepts in a targeted way, etc.
This is such an interesting market and use case too because the educational system might be very structurally set up to the current pedagogical staffing model (think about the incentives for teacher's unions and administrators). If you think it will be hard to change that system as quickly as you want I would also try to have an offering direct to families / home-schoolers. I think there is also a cottage industry of tutors that might benefit. Maybe partnering with the textbook publishers? I'm sure there are some "Teach your kids better" influencers that would get you into some feeds?
On motivation: we have something called Bloomy Bucks. Kids earn these for getting questions right, mastering skills, and being consistent. They can then redeem them for privileges that the teacher/school/parent sets (e.g., homework pass, game time, whatever). This is part of the effortful dopamine that I, personally, think is the right approach to motivation. A lot of people will disagree with me on this, but I think that some amount of extrinsic motivation (something we've already been doing for quite a long time with letter grades) can cultivate intrinsic motivation. One specific application of this is that students can earn up to 1 Bloomy Buck for a meaningful interaction with BloomyBot on a given question.
On assessments: imagine if we could get rid of assessments and just have live diagnosis happen all the time? With enough data from practice and mastery, that should be possible.
We have an offering for homeschoolers, indeed. Bloomy is reimbursable in ~15 states right now through ESA-type scholarships. Great ideas!
- I think the other mistake I see here is trying to over-engineer a deterministic learner path instead of giving the AI more free reign on best next interaction and a set of goals it needs to accomplish through the session; it can feel more responsive and free-form that way from the learner's POV. - If you had voice here you could also make the screen optional. In my experience typing out long answers to questions can take a while too - so a voice mode might be helpful for learners. It would also be cool if people could take a 'photo of their work' for e.g. math equations done by hand. - To the earlier point on family end-market, an interesting idea is modeling bloomy - have some grown-up oriented courses so you can learn with / side-by-side with your child? Just an idea.
I'd love to design this to a greater extent throughout the experience so Bloomy becomes voice-first (where applicable).
https://news.ycombinator.com/item?id=48852199
I worked at an edtech startup with adaptive learning platforms in previous decades. One thing that is always difficult to surmount was that at the under K12 level were:
1. B2b it was hard to land large contracts(like getting an entire public school district to jump from large publishers like HMH or Wiley) because it turned out that the teachers themselves did not care about adaptivity when they had a thousand other things to worry about. But teachers are not the ones that make the deals. It's the school district board and The reps at large publishing just said we are also adaptive and no one would care about how you differentiated. Teachers and students really aren't the lot you have to convince in a b2b deal do you :)?
2. If you want the b2c route then the customer acquisition cost was way too high because again like to get teachers and students to actually adopt this to help them was really a hard sell, especially when the public school system has teachers that are so overburdened with other stuff.
I see that you mentioned charter schools for your pilot, which are not exactly public schools but I dunno of they come with the same set of challenges, but I wonder are these above two challenges are Also something you have had to face while scaling your product?
Almost all the founders who have tried to go into education have come out with similar thoughts.
Schools are basically legacy companies with low nps products. It might do you better to vertically integrate as hard as that is
As you stated, our primary focus is charter schools, but we’re also working with microschools, homeschool co-ops, and families directly. To make this as accessible as possible for families, we are an approved vendor in over 15 states, which allows homeschool families to use their ESA funds for Bloomy.
Our goal is to work with people who are excited to build this future with us and prove the model from there!
You've picked one hell of a time to enter the K12 market. 1:1 device backlash, AI tool scrutiny hightening, teacher exhaustion, no recovery in sight for the recent funding cliff.
Your pilot model is the way to go. My favorite tools all grew out of that model. Stay patient, listen to the early users, encourage them to spread the word. Dont' be above grinding it out at a table at some of the smaller regional educaitonal confreneces.
Sounds like you're already doing this but take IXL head on. They are ripe for the picking.
Good luck!
-Shrinking budgets forcing reevaluation of longstanding contracts, especially those that provide single-subject or limited grade band solutions -A general awareness that, despite the uncertainty around AI, schools need to "figure out this AI thing" -School choice driving demand for mastery-based curricula among alternative educational options
I love a good regional conference.
Couple comments on this being 'screen' oriented, which are as you say endemic in schools and terrible.
There's a fair amount of research that paper reading and handling and writing gets significantly higher retention than screen reading. Most especially physically writing notes, but generally comprehension is just higher for paper. Interestingly e-ink is in the middle between screens and paper.
VLMs offer the interesting possibility of 'looking over the shoulder' of students as they work examples and problems by hand through a camera. It's a harder lift, and it's more expensive, but it might find much higher buy-in to think about a combo book / workbook / AI tutor business model, not least because if you talk to almost any parent or teacher they will tell you that they are extremely worried about genz/alpha kids' abilities to focus, read with attention for longer periods of time or handwrite.
Many of the exercises can be evaluated through a VLM pretty much as easily as in a chat window -- more expensive inference, but possibly a much better world.
A middle ground here might be experimenting with something like a remarkable tablet - it's relatively easy to vibe code a responsive eink page right now, and you could do away with the camera side. I guess I'd think of pairing it with a phone app to talk that could hook up to the remarkable.
My pet theory on handwriting notes and why they're so much better than typing or just listening - if not in shorthand, they are too slow to capture lectures word for word, and thus force a first summarization/categorization step, meaning stuff has to literally go in to short term memory then get pulled out and processed; this just has to be better than typing in a sort of fast typing haze and trying to read them later. It's also the reason my college notebooks have things like (WTF?? <---) next to notes -- I was trying to synthesize and couldn't in the moment. In addition to all this, I understand brain scans show quite a high percentage of the brain gets involved when drawing/handwriting notes -- you have micro and macro muscle movements plus all the cognitive and visual tasks together.
At any rate, it will be a great service to learners to have a quality AI tutor, and I'd pitch you on looking seriously at e-ink or paper modalities if you want to help students learn even better and faster. The tech is SUUUPER close right now, or even could be there with a little willpower.
The VLM idea is especially interesting. It could let Bloomy see how a student worked through a problem, not just whether the final answer was right. We’ll definitely take a closer look at this, so I appreciate your recommendation!
I started my career as a teacher and spent > 8 hrs a day lesson planning, delivering content & grading. If I could have handed that off to a great program like Bloomy, I could have built far better relationships & my students would have been so much better off.
does bloomybot ever just let a wrong approach play out and do the postmortem after? also when a struggling student gets rerouted to an easier skill, can you tell that apart in your data from one who was thirty seconds away from the useful kind of failure? the summit gate tells you they arrived. it doesn't tell you whether the help in the middle did the teaching.
First principle: BloomyBot does not proactively engage the student unless they make 3 mistakes in a row in "Climb" (the practice portion). Then it engages them.
Otherwise, students can engage BloomyBot when they feel they need assistance.
If the student is confidently wrong and attempts to answer a question, they'll see the feedback that they're wrong, with an explanation. They can then clarify with BloomyBot. The goal here is (as you reference) to cultivate productive struggle. So we DO want the student to try their approach.
On getting rerouted to easier skills: students get 1 chance to attempt and fail a Climb. Enough questions wrong in a row (assuming they're trying) = signal that they either aren't ready to learn the skill or that they didn't pay attention to the instructional portion in Base Camp. We give them the benefit of the doubt and assume the latter. If they fail Climb a second time, they get routed to a prerequisite skill.
The Climb gates Summit through Bayesian Knowledge Tracing. Wilson et al. (2019) derived an “85% rule” from formal models of learning: training is most efficient when learners succeed at about 85% of attempts. So Bloomy uses BKT (Corbett & Anderson, 1995) to update each student’s estimated per-skill mastery after every response, and routes students to skills within their Zone of Proximal Development.
Check https://github.com/jakubkrehel/skills or https://github.com/emilkowalski/skills (more around animations), maybe https://github.com/leonxlnx/taste-skill (didn't try it)
https://www.bloomylearning.com/#demo
First, every BloomyBot response streams through an inline safety classification, and then an independent second-pass audit sweeps every stored message — a deterministic rule layer merged with a separate LLM classifier, taking the highest-severity result. It flags three categories (crisis, distress, inappropriate) across every language we support, and confirmed flags alert the teacher and school. We also constrain what the model is allowed to do: the tutor won't reveal answers, and it's completely absent from Summit assessments — so an LLM output never decides whether a student has mastered a skill. That comes from scored assessment performance against our 90% threshold.
Second, a nightly cron job runs across all BloomyBot interactions to flag erroneous outputs (so far, none) and safety alerts (these happen real-time anyway, but the cron job is a backup).
Third, I sample the interactions manually. I've read most interactions so far (although this will become much harder with more scale).
Finally, we are building structured evals to draw inferences across grade levels, skills, common misconceptions, etc. Ideally we will be able to identify the optimal level of scaffolding to help students achieve mastery, but that will take more data and time.
See: https://news.ycombinator.com/newsguidelines.html
> Don't post generated text or AI-edited text. HN is for conversation between humans.
If your metrics are good, increasing test scores is the thing thats 100% going yo get schools on board
Our team was understandably energized by these results, and we plan to run several more pilots this fall to see whether we can produce similar gains across other student populations and assessments, including the PSAT.
How do you solve for "meaning?" Is there some implicit expectation that kids arrive with motivation to discover meaning, or some extrinsic rewards?
As AI essentially commoditizes the mechanical aspects of learning, this is the question we find ourselves asking.
I would like to share our journey running a microschool (where our kids go, along with 40 others now) and how we use AI and what we think about its role.
Some useful context, because this really has informed our approach. I am an engineer turned neuroscientist and the co-author of a popular nonfiction book on the mind (and I share this here because the hard effortful self-driven work of crafting this book taught me more about the mind than anything else in my PhD or later). This work, done during the pandemic when learning was coming online, was what pushed us into setting up the school and gave us the courage to work on it from first principles and not rely on any off-the-shelf alternative pedagogy (montessori, waldorf etc). We looked at (and continue to work on) the full-stack of philosophy, pedagogy, process, practice. So the "what should they learn" is also met with "why should they learn this" and also "how should they be learning this"
The *single biggest* learning for us, which we are now able to articulate clearly, is that schools are set up to fail because there is a well-intentioned but misguided focus on measurement (what are they learning). This gravitational pull results in a focus on mechanics (the most easily measurable thing; long division, periodic tables). This results in a narrow focus on concepts (what David Perkins terms elementitis). Most importantly, what gets left out is meaning. Why should I care about this? With a well-intentioned curriculum and an administration pipette we basically leach out agency and meaning.
So we try to solve for meaning. Our biggest worry with AI is that it focuses entirely on mechanics, with very little meaning. Adults and kids are learning to discount AI-content as automated and inauthentic. We derive meaning from connection. AI can help with the mechanics, but only when meaning has been established. Without this clear-eyed understanding and buy-in we basically have chromebooks all over again, which flattened learning to 2D screens and accomplished nothing (if you look at literacy numeracy scores)
Chatbots are great if you start with meaning and motivation. I already care about the why, so I will socratically find my way to the how and what. But if we do not care about it, which really is the biggest malaise (why should a child who has not yet explored the world or literature they like care about foreshadowing or plot mountains?) Sure, the AI could make it easier, but the kids still need to care?
Wrote about our meaning > motivation > mechanics > measurement revelation and the usual unfortunate inversion here https://blog.comini.in/p/schooling-has-a-meaning-crisis-para...
We need many more people approaching education with ideas and experiments, so thank you and good luck!
How does this factor into your business?
1. Not all AI is the same. I see 2 MECE categories in education: AI that does all the thinking/execution for you (the outsourced brain), and AI that is designed to fulfill specific coaching/tutoring roles. If we design AI to ask great questions and find the Socratic thread with students, we can actually make students think harder and learn faster.
2. Social media is full of cheap dopamine. See my comment about 'effortful dopamine' for my perspective on this.
https://en.wikipedia.org/wiki/Bloom%27s_2_sigma_problem
There is certainly room for software to design a curriculum for the parent or teacher to use. We have tried (and failed) to find such a thing for our homeschool curriculum.
But giving the kid a screen? If you're even a midge honest with yourself, a screen will de-educate your child, leading to the opposite of the intended consequence.
And then you also have kids at home who are on TikTok or Instagram reels - combining screen time with easy dopamine.
Some kids using Bloomy decide to use it at home in lieu of social media time. I'd take that as a win. Cheap dopamine erodes focus and mental resilience. Bloomy focuses on ‘effortful dopamine.' We structure the experience so that students generate reward by conquering academic challenges, training the brain to find satisfaction in effort, patience, and mastery rather than passive consumption.
I'd be curious to see data that can isolate the relationship between educational outcomes and small bursts of high-quality instruction delivered via tech. That's one longer-term outcome we're trying to demonstrate. So far our efficacy results (still early pilots, but correlative) appear to be incrementally positive.
Even desiring pixel-represented "data" for this fact that is obviously observable irl is itself perhaps a result of excessive screen-time, leading to spreadsheet brain, but I can gratify you with these studies: [1], [2], [3], [4], [5]
Of course, no study will exactly disprove the claim that there is some possible content that is a net positive for kids, akin to how no study can prove that unicorns don't exist. But this is exactly the kind of brain-melt, culturally destructive kind of thinking you could expect for demanding "data" for every obvious fact.
Screen time is simply bad for kids. Don't give your kids a screen. Give them a ball, a stick, a book, etc
[1] https://jamanetwork.com/journals/jamapediatrics/fullarticle/... [2] https://jamanetwork.com/journals/jamanetworkopen/fullarticle... [3] https://red.library.usd.edu/cgi/viewcontent.cgi?article=1002... [4] https://jamanetwork.com/journals/jamapediatrics/fullarticle/... [5] https://pubmed.ncbi.nlm.nih.gov/32202633/
On one hand -- phones are evil, and the world is no longer 2004.
On the other hand, I would not be the same person if I didn't get that laptop.
Every quality of life metric (life expectancy, income, etc) goes up with better education. I guess it’s because most people in tech grew up in neighborhoods with nice schools and went to college so they don’t think about it.
Anyway, great luck.
We are also approaching Bloom’s 2-sigma challenge as the design goal. The aim is not another chatbot that gives away answers, but a patient, Socratic coach operating within a structured system of diagnosis, guided practice, feedback, productive struggle, and independent mastery.
One reason we chose college O-Chem rather than K–12 is precisely the concern raised throughout this thread about screen time and introducing conversational AI too early. Organic Chemistry is a notoriously difficult gateway course taken by older students who are already studying digitally. It gives us a more bounded, age-appropriate environment in which to test whether AI can strengthen effortful learning rather than replace thinking.
Your separation of the tutor from the underlying curriculum and mastery system is especially important. We have reached a similar conclusion: AI can ask better questions, provide patient scaffolding, and adapt how concepts are explained, but it should not independently define the curriculum, determine mastery, or become the source of truth. We therefore keep curriculum, pedagogical policy, mastery decisions, and safety controls in a deterministic orchestration layer outside the model.
Congratulations on the launch. It is encouraging to see others pursuing the same underlying educational ambition from a different starting point.
[1] chemio.ai
I would need the product to not exist. I don't want this anywhere near a child. I want humans instructing humans, teaching empathy, connection, and - most importantly - learning to learn.
Anything short of that is just building Brave New World. Electroshock the kids if they reach for forbidden knowledge.
I'm sorry to be so negative since I'm sure you worked hard on this but I find all products in this category to be 100% reprehensible.
"Computer-assisted learning. What an insult, to have the computer teach the human."
- Russ Ackoff
The school dealt with it by sitting me in front of a big box of color-coded dossiers called the SRA Reading Laboratory [1, 2] and telling me "read these at your own pace". The boxes looked just like this: https://sites.google.com/view/objects-of-school-days-past/sr... and may well have been kicking around since the 1960s.
The trouble was that "at your own pace" was code for leaving me alone in front of a box. I don't recall the reading being either interesting or hard, but it solved the problem for my teachers, since I wasn't the type to act out in class. The real lessons I got out of it were lessons in isolation and drudgery.
Looking back, I badly needed contact with an adult who could teach me things. That didn't happen—not then, and not much in later school years either. Was it the schools' fault? They simply didn't have the resources to give me the human instruction I needed.
Surely all agree that children need human contact, empathy, connection, meaningful teaching. But it doesn't help children if we hold to those principles without facing how resource-constrained this problem is. If we do that, then many children end up with nothing, or next to nothing, as happened to me long ago.
Years later, when I read a little history, older novels, and the like, I learned how the nobility had educated their children: not just with dedicated personal tutors but different ones for different subjects. That's what one would do if one could afford entirely human, entirely interactive instruction, and of course it was only available to the 0.0001%. When I read those passages I felt envy and shame at not having what I would (to this day) call a real education, and those feelings have never entirely gone away.
My point with this anecdote is: I don't think I would have been worse off if they had sat me in front of a computer instead of a box of boring readings produced by education researchers. And if the computer had had software that could adapt to me and my interests, so much the better. At least I would have learned things, even though I still would have suffered from lack of human connection that, at that age, I was unaware how much I needed.
[1] https://en.wikipedia.org/wiki/Science_Research_Associates
[2] https://hackeducation.com/2015/03/19/sra
When I was in school I remember thinking, when the futuristic utopia we envisioned in the 2000s arrives, a great deal of people will teach. It will be normal for professionals in all fields to spend some portion of their time teaching. How could it be otherwise, in a civilization which intends to preserve its knowledge and wisdom?
I remember asking my math teacher for applications and she mumbled a non-answer with some embarrassment. It was only years later that I realized, well my god, she's never stepped foot outside of a school in her entire life, no wonder she doesn't know about applications. It would have been nice, I think, to have had some contact with folks who had!
(Later still, I realized that I had reinvented the father from first principles...)
Many of our schools just don't have the teacher headcount to deliver meaningful instruction to their students. Some schools (one non-profit in Africa, for instance) have to choose between having no teacher or having Bloomy.
Are you putting forward that you'd prefer the former? No judgment if so, just trying to understand your framework here.
Right. I remember in high school, when I learned about Anki, being amazed by it. I remember thinking, well, we could replace most of the time I'm spending here, so inefficiently, with a few minutes of Anki per day. Wouldn't that be nice!
Took me a while to realize, well, learning isn't exactly the main point of school. If it were, they might invest a little more effort into making sure people actually remember what they learn! (Ebbinghaus isn't exactly cutting edge stuff.)
So I remember thinking, rather cynically, well what we're doing here could be replaced with an app! (For context this was in the 2000s.) Not that I thought education should be just an app, obviously, but rather, my complaint was that what I was getting was strictly inferior to one.
I had hoped that the advent of AI would open up fully personalized learning tracks, but instead what we seem to have gotten is technology being used to surveil children all day (a bit of an unpleasant thing to train them for, no?), and to ensure they are conforming even more tightly to someone else's ideas about how they ought to be spending their time.
To clarify, I think that someone else telling me what I'm supposed to be interested in[0] (with threat of punishment no less) is deeply offensive to the basic fact of being an organism, but how inefficiently it's being done is a second insult on top of the first one.
That being said, I welcome innovation in this space.
---
[0] I later discovered Education On The Dalton Plan in my school library, being apparently the first person in the school's existence to borrow it. The main idea of the book being that if the child directs his/her own learning, they're liable to actually learn something.
My school was a Dalton school, at least ostensibly, but most of the ideas in the book were illegal in my country. (And new laws passed while I was there squeezed it even further!) Turns out what I was after had been tried, over a century ago, but the government decided it was simply too offensive that the average person should be allowed to decide how they're going to spend their time -- at such an early age, no less!
The more accurate way to describe these situations is overwhelmed teachers with overflowing classrooms where students are left to their own (rather than schools fully absent of an adult).
Recommended Bloomy usage is ~30 mins per core subject. So certainly not the whole day. I have my own very strong misgivings about screen time for kids.
So the idea in this situation is individualized instruction of skills that can adapt live to a student, in a concentrated and limited period of tech time. Hopefully this creates a better outcome than the status quo.
I would also say that looking at the problem like it's teacher headcount that's the issue is assuming a specific education model. If there is only 1 teacher and 300 students, you can't meaningfully do a lecture-style one-way transmission of information. That's outdated anyway and not what the students need.
Your reply here, though, is flat-out against the site guidelines and it's not ok to post like that to HN, least of all in someone's launch thread (whether it's a YC startup or not).
No more of this please. You're welcome to make your substantive points thoughtfully, but if you'd first review https://news.ycombinator.com/newsguidelines.html and take the intended spirit of this site more to heart, we'd appreciate it.
Edit: your previous comment was a personal attack as well: https://news.ycombinator.com/item?id=48981467. Please stop this.
Human empathy is not optional, but rather required. Furthermore humans need to make the connection between the academic skill that's being taught and the real world application or relevance of that skill.
So LLM-assisted education has the potential to help humans be MORE empathetic and deliver the higher-leverage aspects of education only humans can do, while freeing them up from some of the inefficient many-to-one skill instruction for discrete concepts.
At the same time, I believe -- and have seen firsthand as a teacher -- that many students need instruction to learn certain concepts. Even if they don't need instruction, they need a framework or structure to learn within. (One of the big challenges I had to solve early on during my TFA time was classroom behavioral management -- it doesn't matter how good your pedagogy is if your kids won't listen to you).
Great teaching involves modeling a new skill or concept, providing some amount of training wheels, and then seeing it through to independent mastery. Is there a lot that a student can learn on their own simply by reading? Absolutely. Kids should read more books.
As others have commented, it would be better if we could give every student their own personal tutor. Until that's possible, I believe AI can be helpful in education, as long as it's responsibly designed and monitored.