MindFrame
How it works

AI Coaching That Names the Pattern — Not Just the Mistake

MindFrame's coach isn't a chatbot you ask for motivation. It's a system of scheduled, scoped, transparent AI passes over your own training data. Here's exactly what it does, what it sees, and where it stops.

Six coach surfaces

Each one runs on its own cadence. Each one has a clear input, output, and a thumbs-feedback loop back to us.

Session Narrative

Results page, instantly

After every session

A 3-sentence story of what just happened: where you were calibrated, where confidence outran , and what the arc of your session says about today.

Input: Your 10–20 attempts in this session — confidences, accuracies, timings, and per-dimension score deltas.

Output: Prose, not scores. Written to be read, not skimmed.

Next Move

Results page, 24h cache per session

The one thing to do tomorrow

A single focused recommendation — which mode to play next, or which concept in your review deck needs another pass before it fades.

Input: Your weakest dimension this session vs. your trailing 30-day average + which Review Deck items are entering the 're-forget' zone.

Output: One sentence. One link. Designed to fit inside your day.

Agentic Coach Inbox

Monday 09:00 local, on your dashboard

Weekly proactive insights

A short letter from the coach every Monday: one pattern, one celebration, one recommendation. You never have to ask — it writes itself.

Input: Your full 7-day session history + any manually flagged attempts + prior Coach Insight outcomes (which ones you dismissed).

Output: Inbox-style cards with thumbs feedback — the model learns which insights land.

Theory-of-You

First of each month

Monthly essay

A long-form essay naming how you think now — what's changing, what's stubbornly the same, and the working theory of your cognitive style.

Input: Your full month of sessions, reflections, prediction outcomes, and Coach Insight history.

Output: Full essay (600–900 words) with its own shareable OG image and audio narration.

Blind Spot Mirror

Dashboard, refreshed nightly

High-confidence-wrong diagnosis

Finds the cluster of attempts where you were most certain and most wrong, names the bias pattern, and hand-picks 3 bespoke challenges to retrain it.

Input: Attempts where confidence ≥ 75 and = 0, across the last 30 days.

Output: A short diagnosis + 3 specific challenges wired for one-tap start.

In-Session Reasoning Nudge

Live, mid-session

Real-time, on wrong answers

When you miss a challenge without writing a justification, a soft prompt asks why — with 4 seconds to skip. Pure , no scolding.

Input: The attempt state — wrong, no reasoning captured.

Output: One line of copy. No AI call.

The coaching loop, in 5 steps

AI is the last step, not the first. Deterministic scoring runs first; the coach reads what it computed.

  1. 1

    You train

    Answer challenges, rate confidence, optionally write reasoning.

  2. 2

    We score

    Deterministic scoring computes , , reflection slope, adaptation delta.

  3. 3

    Coach reads

    When a coach surface triggers (session end, weekly cron, etc.), a scoped prompt runs against the relevant slice of your data.

  4. 4

    You review

    Every output is visible on-surface with a thumbs widget + link back to the attempts it was built from.

  5. 5

    Coach adapts

    Thumbs-down outputs are down-weighted in future prompt context. The model learns your taste without learning your identity.

Design principles

Every AI feature on MindFrame is held to the same five rules.

Dimensional, not generic

Generic AI coaches produce generic advice. The MindFrame coach works against five measured dimensions — , reasoning, , reflection, adaptation — so every recommendation can be traced to data and evaluated later.

Reads your sessions, not your soul

The coach sees attempt-level stats and free-text justifications you chose to write. No cross-site tracking, no guesses about mood. What the coach doesn't have, it doesn't pretend to.

Caches aggressively, regenerates on real change

Session narratives cache for 24h per session id. Weekly insights regenerate on the Monday cron. Theory-of-You regenerates monthly. You don't pay — in latency or in noise — for reruns that would say the same thing.

Shows its work

Every AI card has a thumbs widget. Every insight links back to the mode or challenge it's rooted in. You can click through to see the attempts the coach was looking at.

You can turn it off

The coaching layer is additive. Turn it off in settings and the dashboard still gives you scores, , and raw analytics — the product still works without a single AI call.

Models, privacy, and what we don't do

What we use

  • Claude Haiku for session narratives, Next Move, Blind Spot diagnoses, Agentic Coach inbox.
  • Claude Opus for monthly Theory-of-You essays where length and nuance matter.
  • Deterministic scoring — no AI — for , , reflection slope, adaptation delta.

What we don't do

  • Cross-site tracking or third-party ad tech. Your sessions stay with MindFrame.
  • Training on your data. Prompts run at inference only — your training data isn't used to fine-tune anything.
  • Black-box scoring. Every number you see has a formula you can look up in the glossary.

Why coaching at all?

Metacognition training produces a g = 0.63 effect on academic performance (de Boer, Donker & van der Werf, 2018) — but only with specific, immediate, reasoned feedback. Vague praise produces no improvement (Halpern, 2014). The coach exists because the research is clear: feedback quality is the lever, not feedback quantity.

Try it in 60 seconds

Answer one challenge. No sign-up. You'll see how confidence-rated attempts become the input that the coach reads.

Put a coach on your thinking

Your first session produces your first Session Narrative within 10 seconds of finishing.