Solveit – a Course and Platform for Solving Problems with Code

Hi all - Jeremy Howard from Answer.AI here. Really excited to share with you all what we've learned over the past year about how to work with AI in a way that's entirely human-centered.

Whilst most folks seem focused on how to remove humans from the loop entirely and make AIs do all the work, we've concentrated 100% on how to make humans part of the loop in a way that makes us more and more capable and engaged.

I've enjoyed building and using our tool, "solveit", for the last year, and do basically all my coding, writing, reading, research, etc in it nowadays. I use small fast iterative steps and work to maximize my learning at each step.

Hey everyone, Eric Ries here. solveit is the AI environment I personally have been using every day for months, not just for code but for writing and research, too.

it’s solved all the problems and frustrations I’ve had with both vibecoding and the limitations of the chatbot interface for doing deep work that requires concentration + the ability to understand the artifacts you are producing

and, as a special bonus, people in this course will get a sneak preview of the new book I’m working on. we’re going to use it both to teach some of the concepts from it (on how to create mission-driven long-term companies) and how to use solveit for longform writing projects

happy to answer any questions here, for folks that want to learn more,

Eric

I see a $400 price tag on a five week course. If it takes 5 weeks to learn how to use your product, I am skeptical that it has legs.

Side note: supposedly this is the first cohort of this course, so how do you already have testimonials?

So the antidote to AI fatigue is... more AI?

I read most of this before understanding that I wasn't reading about some new agent or IDE or something, I was reading a sales pitch for a coding course for would-be vibe coders, with AI training wheels in the form of ... a dialog box to talk to an LLM.

I should have noticed the camp counselor / cultish / tedx vibes, throwin around REPL and feedback loops. I feel that it's somewhat misleading to present this as some amazing self-building software or server platform here, and bury the lede that what's being sold is an experimental tutoring method. It's almost like those "I built an AI agent that builds AI agents" posts, only instead of selling the sixty lines of python, it's selling a set of lectures that goes with them.

I'm sure I'm not the only one confused by this, but can you give details on why you decided that a course was necessary to learn this new way of working with AI?

Maybe it's more of a alpha thing, but with millions using chatbots every day, was it not possible to develop a UI?

It's not just about adoption, who has the time to spend 5 weeks learning a new tool? Particularly when you're competing with the existing tools?

dang. thought this was a service for people tired of reading about AI.

Without the intent of hijacking whatever it is you are trying to achieve: I've found the best antidote to the AI-fatigue is to rely less on it. There is no way I am going to spend my day, or my employees day for that matter in reviewing thousands of LoC of bad AI-slop. In my teams we've dialed it back to just consulting mode and asking suggestions,e.g. replacement for good old search, because once you ask the GenAI to write a few thousands of LoC for you, you're also abandoning a lot architecture decisions (which you then have to figure out ad-hoc again, when you do the review of the slop, or at the latest when you notice the "smart" tool has yet again put a secret in plaintext or something similar). So yeah, if you have the so-called AI-fatigue, just use less of the so-called AI.

One thing I loved about the first solveit course was how create the community is. It goes back to fast.ai too, but everyone is super kind, smart, and has diverse backgrounds.

We've captured a slice of that on our main site. Testimonials: https://solve.it.com/testimonials Some blog posts: https://solve.it.com/#showcases on the main page

And on of the students even made a project dashboard page showcasing all the things everyone has built! https://solveit-project-showcase.pla.sh/

He even blogged about it : ) https://himalayanhacker.substack.com/p/how-i-built-solve-it-...

who tf would pay money for this??

This is such a steep price tag. I loved what Jeremy Howard put up on fast.ai and respect the heck out of his team, but I've seen too many people scammed by online courses that sell a dream. This one seems to be selling a dream as well.

I'll be purchasing the course to try it out but I think my concern is not a one-off thing.

Why does this article not mention what solveit is at all? It talks about what they did, then that they made this tool, then that it's great, but what is it? Watch this video!

No, give me a sentence or two about what it does. I'm not watching a video about a tool while reading a blog post about it because you couldn't be bothered to write a line or two about it.

I'd urge folks here to atleast go through https://www.youtube.com/watch?v=DgPr3HVp0eg before jumping to conclusions about what SolveIt or this course is about. Its the polar opposite of vibe coding IMO.

I couldn't love more all the intentions behind this, but I have no idea what it is. Why would someone who already knows and loves Polya and iterative programming and human-centered technology... use this? What is the value add?

[stub for offtopicness]

Speed reading, so I hope I have not missed existing answers to these questions:

1. Does the 400 cover access to the platform and if so, for what duration and what usage quotas, etc. 2. Can we purchase access to the platform without the course, e.g let us play with it for N months (course seems aimed at junior level devs)? 3. The tools and method, as described, don't mention any tools for minimizing divergence/conflation/hallucination and maximizing repeatability/verifiability etc. Do you have a prompt optimization tool (ala DSPy), a built-in pipeline that uses one LLM to cross check another, or that uses deterministic tools to verify output of LLM (see Campbell, Wimsatt heuristic for managing/triangulating in uncertainty)? I'd be more interested in this new methodology if you were tackling head on the inherent limitations of LLMs (e.g. Yann LeCunn's vision)

Ok so after watching the latent space pod and going through their docs my understanding of what they are doing:

- solve it is mostly an approach less so an app they also build some Jp notebook style ide with branching and deep chat integration + a stateful vm which looks neat though

- my definition of the philosophical approach is: don’t let ai ever generate code you don’t understand be there every step of the way and build things “bottom up” in a very incremental way (basically exactly how Jp notebooks have always worked)

Now my view on the philosophy I actually don’t think I agree. With Claude code and codex I feel like my preferred development flow is “top down” to declare what you want on a high level and then let ai build some complete construct (making sure everything is type safe) and then dig in and understand this construct and iron out all of the details. I don’t think I need to understand fully each intermediate result.

I absolutely fundamentally agree that every line of the final output has to be fully understood and signed off by you.

Honestly, their videos and posts are very difficult to understand so if I misunderstood something I’m super happy to be corrected. I have high respect for the team and it’s nice to see theme excited.

I thought it might be helpful to post a link to one of my favorite writeups from the beta cohort for solveit (last year). It's written by Chris Thomas:

https://christhomas.co.uk/blog/2025/09/24/the-human-is-the-a...

a few quotes/excerpts:

  Being among the first 1000 people to experience SolveIt has felt like witnessing the early days of a significant shift in how we work with AI. As someone who is a seasoned programmer, I have seen many programming paradigms and the advance of AI coding tools. What makes SolveIt different is not just another tool or framework - it is a fundamental rethinking of the human-AI relationship.

  As I look at my experience with SolveIt, I think this is a better more sustainable approach to AI-assisted development. The current trend of ever more powerful models generating ever larger blocks of code feels unsustainable. SolveIt offers a different path. By maintaining human agency, working in comprehensible increments and building genuine understanding at each step, it creates a positive feedback loop where both human and AI capabilities grow stronger over time. This represents a partnership model that builds competence over time rather than creating dependence.
  
  The implications extend far beyond programming. Whether I am implementing computer vision algorithms, exploring culinary science, or writing technical articles - the same principles apply. Small steps, continuous understanding, iterative refinement and always keeping the human as the agent in the process.

I participated in the first cohort and I'll be doing it again because I enjoyed it so much the first time around. The course focuses on teaching a robust problem solving approach, rather than explicitly teaching people how to program with AI. It's not a dream or a scam! If you digest the course concepts, the takeaways can be put into practice even if you aren't programming directly in SolveIt. But the SolveIt application certainly greases the wheels by making this problem-solving approach easier and fun! My growth as a programmer has been supercharged by what I learned and applied in the past year since taking the first course.

A great course and helps with learning proactively and not reactively. Important in this age of ai. I was part of cohort 1 and have enrolled for the next one.

fast.ai (some of the authors of this) was transformative for me, and the community was super nice. Cannot recommend looking into this highly enough.

Ironically AI would've done a better job at summarizing what is this about than thousands of words of this post.

I was in the first batch, I'll be in the second and I'll probably try to be in any of the following.

This is not a course about AI only. It is about learning how to learn and develop yourself specially with the coming AI age. The concepts learned here apply to solve other problems in life. I would recommend it to even non-programmers.

All the industry is moving into vibe-coding, where we delegate more and more into AI, while we do less and less ourselves. The big issue with this is of course that you stop learning. You stop using the ability to put effort into things, and those things, like muscles, go away without use.

It is very tempting to dismiss the solveIT approach as an outlier, at the end of the day if all industry is moving towards full automation instead of careful coding together with the AI, they are probably right, right?

Well, AI getting better at coding, does not mean YOU are getting better at it. In fact it's actually the opposite, without practicing your ability to learn and solve problems, you will lose it. On another level, the kind of one-shotting where you give the AI a problem and come back later after 30 min (or more!) to check if it's done and throw it away if it went of the rails is psychologically. It is the same pattern on which slot machines operate, and gambling is about.

I'm not saying vibe-coding is always bad at all, just there are a lot of caveats and people do not seem to be concerned about.

Those concerns are front and foremost in the solveIT approach, Jeremy has a very thorough understanding about meta-learning for example, the slot machines insight was shared by Johno, and the full team has range of experiences that are rare in the narrow-minded AGI at all costs world of Silicon Valley.

Your psychological health, learning abilities, and in general happiness in life are rarely the main concern of VCs but it rans firsts and foremost in Answer.ai (they are even a public benefit corporation, look it up if you don't know what is that).

With that in mind, I recommend everyone to take the course because it is a multi-dimensional experience that will make you grow as a person and as an engineer. You just gotta look at previous fast.ai course & students.

And finally, if you end up joining because you read this message, I'd love if you get in touch in the Discord server, my name is pol_avec.

See you there!

I apologise folks that we did a bad job of explaining exactly what we're launching! My bad. :( I've added this to the top of the article now -- I hope this does a better job of explaining things:

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*tldr from Jeremy:* You can now sign up for Solveit, which a course in how to solve problems (including coding, writing, sysadmin, and research) using fast short iterations, and also provides a platform that makes this approach easier and more effective. The course shows how to use AI in small doses to help learn as you build, but doesn't rely on AI at all -- you can totally avoid AI if you prefer. The approach we teach is based on decades of research and practice from Eric Ries and I, the founders of Answer.AI. It's basically the opposite of "vibe coding"; it's all about small steps, deep understanding, and deep reflection. We wrote the platform because we didn't find anything else sufficient for doing work the "solveit way", so we made something for ourselves, and then decided to make it available more widely. You can follow the approach without using our platform, although it won't be as smooth an experience.

The platform combines elements of all these: ChatGPT; Jupyter Notebook + nbdev; Bits of vscode/cursor (we embed the same Monaco editor and add similar optional AI and non-AI autocompletion); a VPS (you get your own persistent full VPS running Linux with a URL you can share for public running applications); Claude Code (all the same tools are available); a persistent terminal. Then there's some bits added that don't exist elsewhere AFAIK: something like MCP, but way simpler, where any Python function can be instantly used as an AI tool; the ability to refer directly to any live Python variable in AI context (but optional, so it doesn't eat up your context window); full metaprogramming of the environment (you can through code or AI tools modify the environment itself or the dialog); context editing (you can -- and should -- directly edit AI responses instead of tell the AI it's wrong); collaborative notebook coding (multiple people can edit the dialog, run code, etc, and all see live updates).

As a self taught hobbyist I progressed pretty far in advent of code 2023 until I gave up and less so in 2024 but my approach seems to be close to the one described (if you dig a little deeper into the signup page) or so I imagine. I was disciplined about not asking for help with the problem itself and went to chatgpt for help with components or syntax I needed to build a function I already had in mind (which was closer to the state of the art - especially in 2023 anyway). I think the advent of code problems are really interesting and have enjoyed solving them and watching others solve the ones I couldn’t. They are a fun way to frame the course. However the real value to me is learning how to approach more ambiguous problem spaces. I am definitely interested.

I participated in the first cohort in January 2025 and have been using SolveIt ever since. I would like to share some thoughts about my experience of the course, platform and the community of makers & users.

Explaining SolveIt is hard

How do you explain to someone who's never written a line of code what programming feels like? When I'd visit my father-in-law, he'd ask me at breakfast what I was going to do that day. Every time I would give him the same answer: I will stare at the same blue screen all day long like I have been doing on every average workday since I started programming ~15 years ago. It's become our little family joke, but it's also true - it's difficult to explain to someone who has never done it.

The question is what does that blue screen work actually involve? What does programming feel like? How do you live through it? What is your experience when you solve problems - is it painful or agreeable? Do you finish knowing more about the domain of a problem you tackled, or did you just get something working fast and hope it wouldn't collapse on you later?

The SolveIt experience is similarly hard to explain to someone who hasn't tried it. What's interesting is that using the SolveIt method has had positive effects on all these areas - how my work feels, how well I understand what I build, and the quality of what I produce.

For my first bigger, work related project in SolveIt I built an annotation interface for YouTube dialogue transcripts for documentary movie footage classification. I'd used Angular before but not FastHTML and HTMX. I had a working app in production within two weeks going from 0->users annotating, which might not sound very impressive in this new agentic era. But when using SolveIt right, the result isn't just working code, it's code that you know, and most importantly it's a much better understanding of your initial problem and the potential solutions/technologies to solve it.

Plus, the SolveIt approach made me examine each component individually - what it represents, what it means for my system, how it could integrate more broadly into our organization. That exploration led to something far more general than my initial annotation app: now we are using it for browsing/editing dataframes through a UI, where columns and cells can have different templates/layout, edit history and several other features I hadn't even thought of initially. The exploration phase took longer, but I gained a foundation I understand deeply and can build on. For core business problems, that knowledge living in your head matters a lot.

My only problem at the time was git integration - I wanted my work synced with my codebase and manual copy pasting was too much friction. This has been resolved since: I have my git repos accessible from SolveIt and AFAIK you can serve apps directly from the platform without needing to deploy it (though I haven't tested this functionality yet).

Cult disclaimer

I was surprised reading through this thread by comments about religious cults, paid marketing campaigns, and fake testimonials. It's true that I registered to Hacker News today just to share my experience with SolveIt. I am a real person though and have not received any money for writing this post.

Instead, for several years now I've been learning from Jeremy Howard and the answer.ai team through their free resources - the fast.ai courses, talks, podcasts, and open source projects. Hamel Husain's work on nbdev also had a huge impact on how I work. All of this is available for free to anyone interested in learning. I hope that many others will discover them and SolveIt. I believe many successful projects, businesses and open source solutions will grow on the SolveIt ground, the same way it happened with fast.ai courses.

On $$$ concerns: I paid $200 for the first prototype cohort. I thought it was worth much more than that - the course itself, plus unlimited 11+ month platform access (included Claude most recent model), plus the community discussions where I learned from other practitioners how they tackled specific problems from very diverse domains. When cohort 2 was announced, I knew I was gonna sign up even before I knew the price. The ideas you take and friends you make in these communities are priceless.

I had access to GitHub Copilot as a student in early 2022 while learning Haskell and immediately realised that it would hinder my learning if I didn't turn it off and implicitly follow this understand, plan, execute, reflect loop.

AI products like Cursor have the notion of an 'autonomy slider' [1] that can fortunately be turned all the way down (disable Cursor Tab) but relying on this discipline seems fickle when with the right agentic loops [2] and context engineering, thousands of lines of code can be churned out with minimal supervision.

I've considered always working on two projects over a long timespan, one with no AI assistance, possibly in a separate IDE like Zed, and one in Vibe Kanban (my current daily driver) but this feels like an inefficient proxy to accelerating this four step learning loop with a tool like solveit.

Since the solveit product isn't released and seemingly isn't competing with solutions, is there an opportunity to convey how AI product developers should be thinking about amplifying their users and keeping them in the learning loop?

So far, I've seen Claude Code's Learning output style [3], and also ChatGPT's study mode but in these cases, the only product change is a prompt and solveit is more than that.

[1] https://www.latent.space/i/166191505/part-a-autonomy-sliders [2] https://simonwillison.net/2025/Sep/30/designing-agentic-loop... [3] https://docs.claude.com/en/docs/claude-code/output-styles#bu...