Math Academy

What we covered: – It's been a few months since our last podcast, and in that time, we've seen a huge increase in the number of schools wanting to use Math Academy for this upcoming school year.– Now, if you've been following our podcast, you already know that one of the recurring themes at Math Academy is that before you automate something, you gotta first do it manually so you really understand what you're automating.('Cause if you skip that step, and you jump straight to automation without really getting your reps in, getting your arms around the problem, you end up building a whole bunch of infrastructure that not only does not solve the problem, but in fact just scales your confusion. And then you gotta unwind all of it later. It puts constraints on more things that you build once you actually know what you're doing. It's just terrible.)– So just like Jason did with individual customers at the beginning, onboarding hundreds of people over hour-long Zoom calls, getting those manual reps that have been really such a vital component of building a system that really solves the problem... Well, that's what he's doing again with schools. And that's what we'll talk about in this episode.– We'll talk about the anatomy of Jason's onboarding sessions, why onboarding a school is way more challenging than onboarding an individual, and what successful school implementations look like. In particular, why it's most sustainable for each school to start small, lock in some wins, get solid in managing students who are using the system, and then gradually scale up to more classes and teachers.Outline:2:44 - Onboarding lots of schools recently6:39 - Different types of customers9:13 - Why conversations with customers matter15:05 - Streamlining inevitable school sign-ups17:10 - Identifying high-leverage tasks18:35 - Manual school account creation19:30 - Manual processes make sense in the beginning22:05 - Learn the workflow before automating23:28 - The hidden costs of new software features25:25 - Keeping product scope minimal27:40 - Anatomy of a typical school onboarding session37:26 - Intentionally growing without a sales team40:11 - Schools promote students without requiring mastery42:20 - Why every school onboarding call is different43:48 - Building automated school onboarding51:05 - Validate success at a small scale before scaling up55:30 - Sustainable growth over rapid expansion58:41 - Looking ahead: proctored examsFollow on X:Math Academy - https://x.com/_MathAcademy_Justin Skycak - https://x.com/justinskycakJason Roberts - https://x.com/exojason

What we covered:– In elementary school, there's often an intense focus on conceptual understanding, but not enough time spent building real fluency with core skills. And this has left many kids without automaticity on basic things like multiplication facts. Math is extremely hierarchical, and when students don't have the basic facts at their fingertips, they quickly run into bottlenecks as the material gets more complex.– Sure, drills can be made more fun, but the bottom line is that they have to get done. In high school and college, most of the class time is spent copying notes from the board -- and these notes are often copied by the instructor from a textbook or from other source material. This game of telephone through transcribing is just a performative activity. It's theater. It's passive and it does next to nothing for learning and retention.– In upper level college math courses especially, students may only receive short weekly problem sets, which really aren't enough to build mastery, even if the problems are really hard, because students just spend most of their time flailing around.– The bottom line is that students need reps: lots of them, building up scaffolding to the highest, hardest levels that they're expected to reach. High school assignments tend to be better in that regard, but students frequently don't receive timely feedback, and often their work isn't even graded for accuracy. That feedback loop is so critical: without it, students won't know what they're doing wrong or how to improve.– So rather than just pattern matching to how math has traditionally been taught, what actually makes training effective? There's a few core principles:1) Maximize the amount of time spent actively learning, interleaving minimum effective doses of explicit guided instruction active practice.2) Make sure students are consistently working at the edge of their abilities: not bored, but not overwhelmed.3) Provide frequent, timely feedback so students can adjust and improve.These principles should be applied to math education and training environments everywhere.Outline:0:00 - Introduction3:13 - Professors often wing pedagogy5:37 - Too much class time is spent transcribing notes7:41 - College problem sets are too short12:53 - A lot of homework isn’t even graded for accuracy18:22 - Copying notes in class is performative productivity22:29 - Alex taught math courses at University College London25:35 - Teaching is often an annoying obligation for research professors30:03 - The bar for teaching is on the floor32:34 - Even football practices often waste players’ time34:20 - Most training is inefficient because people pattern match to the status quo34:57 - First principles for effective training37:13 - Too many models can paralyze and become a crutch for kids39:24 - Kids can get stuck using training wheels in math forever42:05 - Non-standard methods are often distracting and inefficient46:18 - Designing 6th-8th grade courses to align with school curricula52:30 - Conceptual understanding without ability is useless55:17 - Skills practice can and should be gamifiedFollow on X:Math Academy - https://x.com/_MathAcademy_Justin Skycak - https://x.com/justinskycakJason Roberts - https://x.com/exojasonAlex Smith - https://x.com/ninja_maths

What we covered:– A lot of schools have recently begun using Math Academy in their classrooms. And one of the biggest benefits of using Math Academy is that it automates all the mechanical parts of teaching, like writing questions, keeping track of what students know and what they don't know, monitoring student progress, assigning extra practice when needed, grading, all that grindy stuff.– None of these tasks is enjoyable. They suck. Just ask any teacher. I mean, we grinded through all that back when we were teaching ourselves, and it takes so much effort just to get even a halfway decent approximation of doing it right. And there's just a limit to how well that you can do it if you're doing it manually. It's the whole reason why we built the system.– And what that system does, what Math Academy we does is it frees up teacher bandwidth to focus on the human elements of teaching: building relationships, connecting what students are working on to their own unique interests. Those kind of things that enhance the learning experience, but that really can't replace skills practice.– I mean, in-class projects can be great, but only if students have the prerequisite knowledge to be successful with them. If they don't, then projects are frustrating, and the students who understand the material will end up doing all the work and carrying everybody else, who will learn next to nothing. It's inefficient and frustrating all around unless students have their skills in place.– Ultimately, if students don't master the math in each class, they'll be unprepared for the next one. And in a subject as hierarchical as math, these gaps compound quickly. True empowerment isn't simply telling students they have potential. It's making sure they actually have the real skills to move forward and realize that potential.Outline:00:00 - Introduction02:56 - What is the teacher’s role alongside Math Academy?05:37 - Math Academy frees up teachers to do the human parts of teaching07:03 - Projects are great if students have the prerequisite skills07:42 - Drills without context are boring08:43 - Games without skills are inefficient11:14 - Build fun activities on top of a solid foundation of skills12:15 - Teachers can tailor the class to the students’ preferences13:28 - Implementing mastery learning is too much work for a single teacher15:27 - Doing projects without prerequisites is frustrating16:57 - True empowerment is giving kids the skills they need to succeed19:30 - Missing skills compound in hierarchical skill trees24:06: Lack of automaticity in lower level skills slows down higher level tasks27:14 - The MA team builds and improves courses through experience29:21 - The MA team targets tasks with low pass rates for additional scaffolding31:03 - Alex built knowledge graph intuition through years of experience37:40 - Social media enforces hyper-accountability39:19 - Differential equations courses are often a hodgepodge of disjointed techniques43:20 - Math Academy university courses are a superset of elite university content45:18 - Differential equations is a highly branching subject49:21 - The breadth of Differential Equations makes it often poorly taught*Follow on X:*Math Academy - https://x.com/_MathAcademy_Justin Skycak - https://x.com/justinskycakJason Roberts - https://x.com/exojasonAlex Smith - https://x.com/ninja_maths

What we covered:– As Math Academy has grown over the past year, we're getting a better sense of general do's and don'ts when scaling a startup. We've learned hard lessons about overloading the database, the task processor, and our team, requiring numerous infrastructure and process updates.– Schools have been using the system and we've built plenty of additional features to, among other things, accommodate unique billing schemes and make it easy for teachers to manage classes on the system.– We've intentionally grown organically and were self-funded, which forced us to do things manually at the beginning. Years ago, we taught math classes in person and Jason onboarded our first online users on hundreds of hour-long individuals and calls. These were crucial experiences to learn who our customers are, what they want from the product, and common failure modes.– In our experience, doing things manually at the beginning ensures that you 1) build a product that customers actually get value from, and 2) you don't clutter your product with unnecessary bells and whistles that don't add value. In other words, you have to do the manual work to earn the right to scale.Outline:0:00 - Introduction2:18 - Building infrastructure to handle increasing load3:41 - Bringing on AWS expertise to robustify the backend4:22 - An overloaded database enters a new realm of physics5:50 - Prioritizing execution over perfection in start-ups6:33 - Paying the bill for accumulated infrastructure debt7:53 - Improving job prioritization of the task processor9:52 - Benefits of scaling organically11:42 - Wisdom is the result of failures12:18 - There is no substitute for experience13:17 - Focusing on solving problems, not advertising14:48 - Upgrading with surgical precision15:35 - The pain-point compass17:04 - Managing finite time and resources18:27 - Development of the gravity feature20:42 - Gravity is a suggestion, not a hard override22:25 - Limiting gravity to avoid cognitive overload28:29 - Balancing customization and customer confusion31:28 - The feature sandbox33:58 - Increasing volume of customer support emails35:22 - Additional infrastructure requirements for schools36:18 - Learning about the customer through direct interaction38:14 - Step 1: Manually added schools using spreadsheets 40:22 - Step 2: Developed tools to handle specialized school requests41:23 - Step 3: Goal is 100% self-service sign-ups for schools42:32 - Solve the problem manually first, then automate it43:44 - Why focus on schools?46:15 - Math Academy goes to college49:37 - You can’t anticipate every edge case 52:14 - Letting user behavior build the product roadmap 58:54 - Becoming successful means working harder1:00:24 - The customer support hurdle 1:03:27 - How Justin’s expanding roles drove growth (both personal & company)1:09:03 - Teaching as market research for Math Academy 1:10:52 - The value of having been inside the tradeFollow on X:Math Academy - https://x.com/_MathAcademy_Justin Skycak - https://x.com/justinskycakJason Roberts - https://x.com/exojason

0:00 - Introduction3:57 - Added 115 “Missing Middle” topics to SAT Prep.6:06 - Integrating the SAT Missing Middle topics into other courses9:42 - Added tens of thousands of free response questions10:34 - Free response questions are useful because they don’t prime you13:33 - When to use free response vs. multiple choice questions14:54 - Too many free response questions taxes learners16:39 - Limiting the length of free response answers.18:08 - Building infrastructure for free response questions was a beast20:42 - SAT test prep course22:22 - Machine Learning has been the hardest course to develop so far.23:12 - People who know machine learning, math, and how to teach them are rare25:06 - The Eurisko book was the best resource for developing the Machine Learning course28:51 - Balancing repetition and computational load in Machine Learning problems29:43 - Designing minimum viable problems for Machine Learning33:53 - Building the infrastructure for dynamic select questions was a nightmare36:12 - Dynamic select questions are good for proofs and university-level math38:03 - The Differential Equations course is almost finished40:23 - Iterating on course development to make better courses42:00 - 2026 is the year of scaling up course production43:03 - How to scale up the team without sacrificing course quality44:39 - Learning the hard way about hiring too quickly46:20 - Challenges of managing a fully remote, geographically dispersed team48:54 - Building tools to measure company output50:06 - Optimizing content writer performance is like optimizing student learning52:31 - Incentivizing content creation to improve output56:36 - Courses planned for the longer term58:01 - You need to learn concrete computations before abstract proofs59:32 - Why we separate university-level courses into computational vs proof-based1:01:07 - The best textbooks for beginners are NOT the most complex1:02:37 - Teaching proofs and computations at the same time overloads most students1:04:16 - Intuition through repetition1:04:49 - Wisdom is the abstract compression of lived experiences1:07:39 - Mastering details before abstractingFollow on X:Math Academy - https://x.com/_MathAcademy_Justin Skycak - https://x.com/justinskycakJason Roberts - https://x.com/exojasonAlex Smith - https://x.com/ninja_maths