01 · Planner
Decomposes the source into a learning path
Parses the document or transcript, extracts topics and dependencies, and emits an ordered plan of modules and steps you can review, reorder, or rewrite before the session starts.
Multi-agent learning system
Four agents. One adaptive learning loop.
Repeater is not a single model behind a chat box. It is a pipeline of specialised agents that plans, teaches, tests, and adapts to you, so every next session targets your gaps.
Source material
InputPDF12 pages · 1 transcript · 3 diagrams
Photosynthesis & Calvin cycle - notes.pdf
Lecture.mp4Transcript.txtSlides.pdf
Repeater pipeline
Adaptive session
Guided learning loop
01 · Planner
Decomposes the source into a learning path
02 · Explainer
Teaches each step in the modality that fits
03 · Evaluator
Probes understanding with quizzes and open questions
04 · Adaptive
Finds your gaps and builds the next session
Architecture
A pipeline, not a chatbot.
Each agent owns one job and passes a typed contract to the next. Failures are recoverable, decisions are inspectable, and every module on the plan goes through the same loop.
02 · Explainer
Teaches each step in the modality that fits
Picks the right format per concept: short video, narrated walkthrough, mind map, flashcards, comparison cards, or animated diagram. Audio and visuals come from the same context, no copy-pasting between tools.
03 · Evaluator
Probes understanding with quizzes and open questions
Generates targeted multiple-choice items and open-ended prompts grounded in the step content, compares answers against the source, returns structured feedback, and re-explains the parts you missed so you can choose to dig deeper or move on.
04 · Adaptive
Finds your gaps and builds the next session
Reads signals from prior runs — wrong answers, skipped steps, hesitations, and time-on-step — to see exactly where you struggle, then generates the next session to close those gaps. Learning that is actually personalized, not one-size-fits-all.
End-to-end flow
From raw source to adaptive session.
Every interaction is captured as state. The planner kicks off, the explainer and evaluator alternate per step, and the adaptive agent closes the loop by shaping the next session around your gaps.
01
Ingest
Drop in a PDF, slide deck, lecture video, or transcript. Repeater extracts text, audio, and structural cues to build a normalised representation.
02
Plan
The planner agent produces a typed learning plan with modules, steps, and step types (explain, quiz, summary). You can confirm it, edit modules, or regenerate before the session begins.
03
Teach
The explainer agent picks a modality per step: short narrated video, mind map, flashcards, animation, or comparison cards. Materials are rendered inline, not linked out.
04
Test
The evaluator agent issues quizzes and open questions. Responses are checked against the source and answered with structured feedback. Missed parts are re-explained. You decide whether to dig deeper or continue.
05
Adapt
Once a session ends, the adaptive agent reads all signals, sees where you are weak, and builds a new session that targets exactly those gaps.
Multimodal output
Visual, auditory, kinesthetic, chosen per step.
The explainer agent does not default to walls of text. It selects the modality that fits the concept and the learner's prior interactions.
Narrated video
Short clips with synchronised voice-over and on-screen visuals, generated from the source and the planned step.
Mind maps
Concept graphs that expose the topology of a topic before drilling into the details.
Flashcards
Atomic prompt/response pairs scoped to the current step, surfaced exactly when the evaluator decides recall is the right test.
Animations
Step-by-step animated diagrams for processes, cycles, and mechanisms where motion carries the meaning.
Adaptive sessions
Every session is built around your gaps.
After each session, the adaptive agent reads your interaction trace (answers, confidence, time-on-step, retries), sees where you are weak, and writes a new session plan that targets those gaps. The longer you use it, the more precisely it converges on your weak spots.
Remembers where you struggled
Every session feeds the next. What you missed comes back; nothing is regenerated from scratch.
Targeted re-teaching
Topics with failed evaluations come back first, with a different modality and a different angle, not the same explanation twice.
Editable plan
Every module on the plan shows what it will cover before the session starts. Rename, reorder, remove, or regenerate any step: the loop runs on your version, not a black box.
Where a multi-agent loop beats a single chat.
Where you need a path, a check, and a way back.
University study
A 60-page chapter becomes an evening's plan, with quizzes that show what stuck.
Professional certifications
Long syllabi into testable modules. Time goes where you fail.
Internal training
Onboarding docs into guided sessions, with checks built in.
Self-directed learning
Drop a paper or a video: the planner exposes the structure.
Technical questions
Why a multi-agent system instead of one large prompt?+
Each agent has a narrow contract. The planner returns a typed plan and the evaluator returns structured feedback on the answer, so failures are localised and the pipeline is inspectable. One large prompt would conflate planning, teaching, and feedback, and degrade on long documents.
Can I edit the plan before the session starts?+
Yes. The planner agent emits a learning plan with modules and steps. You can rename, reorder, delete, or regenerate any module before entering the teach/test loop.
What happens when I get an answer wrong?+
The evaluator does not grade you and does not gate progression. It returns feedback and re-explains the part you missed. From there you decide whether to dig deeper on the topic or move on with the rest of the session.
How does it personalize the next session?+
The adaptive agent reads your interaction trace from prior sessions, including wrong answers, retries, time-on-step, and skipped steps. It sees where you struggle and generates a new session plan that targets those gaps with different modalities.
What sources work as input?+
PDFs, slide decks, lecture videos, audio recordings, transcripts, and free-form prompts. Audio and video are transcribed and aligned before the planner runs.
Run the loop on your next document.
Drop a source, watch the planner produce the path, then move through teach and test until the adaptive agent has enough signals to target your gaps in the next session.