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learning-loop

Acumula conhecimento entre sessões, ajusta perfis psicográficos com base em declarado vs. comportamento e aplica uma filosofia retrô que desvaloriza as Linhas de Código, usando um teste de manter ou descartar para aprendizados.

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Atualizado há 6 meses

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Learning loop

How to compound knowledge across sessions, projects, and time.

Source: gstack plan-tune/SKILL.md, retro/SKILL.md, learn/SKILL.md, SKILL.md.

The dual-track psychographic profile

Track two things separately:

  • Declared profile — what you say you want
  • Inferred profile — what your behavior actually shows

Five dimensions, each 0.0–1.0:

  • scope_appetite
  • risk_tolerance
  • detail_preference
  • autonomy
  • architecture_care

Gap-band lexicon:

  • <0.1 → close
  • 0.1–0.3 → drift
  • \>0.3 → mismatch — "your behavior disagrees with your self-description"

Iron rule

The user decides whether declared is wrong or behavior is wrong. Never auto-update declared from observed gap.

"One-way doors override never-ask" — destructive / architectural / security questions ALWAYS ask, regardless of preferences.

Calibration gate

20 events + 3 skills + 8 question-ids + 7 days before showing inferred profile. Don't surface a "vibe profile" until you have signal.

Retro philosophy

"Features shipped leads — what users got. Raw LOC is demoted to context because AI inflates it; ten lines of a good fix is not less shipping than ten thousand lines of scaffold."

Session classification

  • 45-min gap = session boundary
  • Deep session: 50+ min
  • Medium: 20-50 min
  • Micro: <20 min ("fire-and-forget")

Fix-ratio flag

\>50% fix commits = "ship fast, fix fast" pattern signaling review gaps.

Focus score

% of commits in single most-changed top-level directory. Low score = scattered work.

Retro tone doctrine

"Praise should feel like something you'd actually say in a 1:1 — specific, earned, genuine. Growth suggestions should feel like investment advice — 'this is worth your time because…' not 'you failed at…'"

"3 Habits for Next Week" — each must be <5 minutes to adopt.

Never compare teammates negatively.

Six learning types

When capturing a learning, label it:

  1. pattern — reusable approach
  2. pitfall — don't-do
  3. preference — user-stated
  4. architecture — structural
  5. tool — tool-specific gotcha
  6. operational — process / workflow

Four learning sources

  1. observed — saw it directly
  2. user-stated — user said it
  3. inferred — pattern-matched from behavior
  4. cross-model — both Claude and Codex agree

Confidence honesty

| Source | Confidence | |---|---| | Observed and verified | 8-9 | | Explicit user statement | 10 | | Inference | 4-5 |

Don't inflate. A speculation logged at 9 poisons future sessions.

The keep-or-toss test

"Would this insight save time in a future session? Would knowing this save 5+ minutes? If yes, log it."

Don't log:

  • Obvious things
  • One-time transient errors (network blips, rate limits)
  • Things you'll remember anyway

Append-only with latest-wins. Staleness detection via file-existence checks. Conflict detection: same key, different insight = manual review.

Operational self-improvement loop

End every session by reflecting:

  • Did you take a wrong approach and have to backtrack?
  • Did you discover a project-specific quirk (build order, env vars, timing, auth)?
"A good test: would knowing this save 5+ minutes in a future session? If yes, log it."

Future sessions surface the learnings automatically.

Memory hygiene

Three privacy tiers, opt-in by default:

  • Full — everything allowlisted
  • Artifacts-only — plans, designs, retros, learnings (skip behavioral data like timelines)
  • Off

What deliberately doesn't sync:

  • Question-log
  • Question-preference

Why: "Per-machine UX state. Behavioral data should not travel; durable artifacts (decisions, designs, learnings) should."

Per-remote trust triad

For consultants juggling multiple clients:

  • read-write — full sync both ways
  • read-only — pull learnings, never push
  • deny — totally isolated

Designed for "freelance dev working on Client A in the morning and Client B in the afternoon" — Client A's insights must not bleed into the brain Client B searches.

Ship velocity, not LOC

"Features shipped leads. LOC is demoted to context because AI inflates it."

When measuring weekly progress:

  • ✅ "Shipped X features, fixed Y bugs"
  • ❌ "Wrote 10K lines"

The bug fix that's 10 lines beats the scaffold that's 10,000.

Closed-loop principle

Every workflow should generate data the next workflow can consume.

  • /ship → ship log
  • ship log → /retro velocity trends
  • /retro → next sprint priorities
  • next sprint → /ship again

If a workflow doesn't feed the next one, it's a dead end.

Verdict-style retros

Don't summarize. Lead with a verdict:

  • ✅ "We finally killed the staging-env flake. Shipped 3 features. Took 2 detours we should not have taken."
  • ❌ "This week we worked on..."

A retro that doesn't take a position is a status update with extra steps.

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