A week ago I wrote about Space Academy, the AI homework trainer I built for my second-grader on top of his actual school textbooks. Here's the update, and it's really about one thing: what it takes to keep generated content honest when the consumer of that content is a nine-year-old who will happily learn whatever you get wrong.
The numbers first: the app now covers 41 pages of two textbooks (math, Moro grade 2, pp. 4-35, and Russian, Kanakina, pp. 37-58), 199 tasks, 214 check questions. Every one of them traces back to a scan of the printed book.
The scan gate, in practice
The rule is boring and absolute: no task enters the database without verification against the printed textbook. A vision model transcribes each task with a narrow prompt (one task at a time, not the whole page), then a second pass compares the transcription against the scan. On mismatch, the scan wins.
The interesting decision is what happens where automatic verification can't be honest. Clock readings on a small dial, ruler measurements: the model can read the scan, but a wrong reading would poison a whole exercise chain. So those cards deliberately ship without a reference answer. The child enters their own result, the card is marked for an adult to check, and the expected format sits in the hint. It feels like a regression until you frame it right: an unverified answer in a solver is worse than no answer.
The method lives in the deploy, not the prompt
The learn method (probe, plan, teach) is enforced by a build gate: a page without a lesson plan (a small human-readable DAG from base facts to the lesson goal) and without a motivation line for every task fails the build. No prompt injection can route around it because the check runs in CI, not in the model.
Two smaller things that came out of live use:
- "Pick four correct inequalities out of six" is a set, not a sequence. Checking is element-wise; answer order is irrelevant.
- Wrong answers got personality. If a child drops an antonym from the wrong sense of the word into "shallow pond / shallow rain", the trainer answers "Rain is never deep, here 'shallow' is about drop size" instead of a generic "incorrect". The kids' favorite is circular examples: eight shuffled cards with no visible answers, where each answer is the first number of the next card. Compute in your head, pick the card that starts with the current number, and when the last card loops back to the start, the circle closes and the task credits itself. The wrong card simply doesn't snap into the chain, so a mistake is visible without a check button. ## Tools beat gamification Two additions worth stealing for any learning app:
- A real ruler. Every math page has a button that slides up a drawer with a 30 cm ruler, millimeter ticks, and scrolling like the physical tool. Two taps on the scale and the ruler draws the segment itself: "from 6 cm to 14 cm, length 8 cm = 80 mm".
- A photo report. One button photographs the finished page and opens the system share sheet, so "show me your homework" takes two seconds instead of a negotiation.
## SpaceLocker: the guard is native, the trust is not
The desktop piece is a single self-contained C# executable built from Linux with
dotnet publish -r win-x64 --self-contained. While the daily quota (set by a parent: "math, p. 36") is unfinished, a process monitor kills Steam and Roblox every 15 seconds, YouTube is blocked via the hosts file with marker lines, and launching a game brings up a fullscreen screen with quota progress. Alt+F4 does nothing. The screen closes on a finished quota or the parent PIN. The guard asks the Space Academy API for homework status under the cadet's session, so the source of truth stays on the server where the work actually happens. ## What I would tell anyone building this The stack is ordinary (React, TypeScript, Tailwind, Express, SQLite, .NET for the guard). The hard part isn't the stack. It's the discipline: a content pipeline that treats the textbook scan as ground truth, a method enforced in the build, and honest blanks where verification cannot be honest. That combination is rare, and it's what makes the tool trustworthy enough to put in front of a child every day. It's a family project, not a SaaS. If you want a deeper breakdown of the verification agent or the deploy gate, ask in the comments. Originally published at https://automata.sale/en/blog/ai-automation/space-academy-weekly-update/ --- This article was prepared with AI assistance (drafting and adaptation) and reviewed by the author before publishing. tags: aiagents, edtech, automation, dotnet
Top comments (1)
The scan gate idea resonates strongly — when the consumer of your content is a nine-year-old, there is no room for confident hallucinations. Anchoring everything to the actual printed textbook instead of letting the model freestyle is the right call, and "the method lives in the deploy, not the prompt" is a great way to put it: verification as infrastructure rather than instruction-following hope. Thanks for sharing the weekly update.