Independent project / Neeladri Biswas

SIFT

A personal reflection and execution tool designed to turn reactive thoughts into patterns you can examine—and small actions you can take.

OwnershipDesigned and built independently
ContextPersonal project · This year
FocusThought capture, reflection & action
SIFT voice capture interface presented in a phone mockup
SIFT home screen with voice capture control
SIFT’s actual capture interface.
THE 30-SECOND VERSION Executive Project Briefing
01 CONTEXT

SIFT began as an experiment in helping people move from an overwhelming or abstract thought toward something concrete enough to act on.

02 HYPOTHESIS

If a difficult thought or task could be progressively decomposed into smaller layers, the next action might become easier to see.

03 WHAT I BUILT

I built an AI-assisted cognitive decomposition interface that turned a high-level thought into progressively smaller, more actionable layers, and launched the experiment on Product Hunt in June 2026.

04 WHAT I GOT WRONG

The moment SIFT was designed for was also the moment I least wanted to use SIFT. I had designed a cognitively expensive interaction for a cognitively overloaded moment.

↓ THE FULL STORY
01 / Starting point

The difficult moment between planning and doing.

I built SIFT around my own experience of rumination and overthinking. The problem was not simply a lack of goals: overwhelm, avoidance, and familiar patterns could interrupt the move from intention to action.

SIFT explores that execution gap through three lenses: fading motivation, moments of mental paralysis, and reactive thoughts that may point to recurring beliefs or behaviours.

02 / Capture & deconstruction

Give an unstructured thought a structure.

Voice dictation or text input captures a thought when friction occurs. LLM-powered serverless endpoints parse the entry into suggested emotional drivers, cognitive polarity, and possible points for change.

The seven-layer model organises the reflection:

L1 · Thought

The immediate reactive trigger.

L2 · Belief

The underlying rule or internal logic.

L3 · Mindset

The framing lens applied to the situation.

L4 · Action

The immediate behavioural response.

L5 · Habit

The recurring pattern.

L6 · Identity

The self-image associated with that pattern.

L7 · Outcome

The longer-term direction the pattern may lead toward.

These layers are the product’s interpretive framework. The AI output offers hypotheses to reflect on, rather than established facts about a person.

Reflection after capturing a thought
Reflection after capturing a thought.
Structured interpretation of the captured thought
Structured interpretation of the captured thought.
03 / Two possible paths

The Neural Hinge.

This feature presents two possible directions from an active loop: Path A explores a change in response; Path B examines the possible cost of repeating the habitual response.

Active thought loopPath A: change the responsePath B: repeat the pattern

The purpose is to make a decision point easier to notice.

Neural Hinge: an alternative response path
Neural Hinge: an alternative response path.
A second response path in the same reflection
A second response path in the same reflection.
04 / Patterns over time

A mirror for recurring themes.

The Stoic Identity Mirror and synthesis features aggregate recurring nodes across the seven layers. Second-person reflections and pattern cluster reports help surface themes across entries.

These are AI-generated reflections, not clinical diagnoses. Their value depends on whether users recognise, question, and find them useful.

Pattern Explorer with the seven-layer selector
Pattern Explorer with the seven-layer selector.
05 / Action

Make the next step small enough to start.

Side Quests translate an identified point of friction into a discrete action intended to take about two minutes. The design goal is to reduce initiation friction and create momentum.

CaptureReflectNotice a patternTry a small action

Lower friction is a design intention; sustained behavioural change is not claimed as a measured result.

Quest Map overview
Quest Map overview.
An active quest and its progression
An active quest and its progression.
06 / Technical foundation

Built across interface, state, and intelligence.

  • Frontend: Next.js 15 App Router, TypeScript, Tailwind CSS 4, and Framer Motion.
  • State and sync: Zustand with optimistic updates and local persistence.
  • Database and authentication: Supabase PostgreSQL, row-level security, realtime subscriptions, and OAuth integration.
  • Intelligence: Gemini API orchestration through serverless edge routes.

I built SIFT entirely on my own, connecting thought capture, structured reflection, and action suggestions within one experience.

07 / The Contradiction

The moment SIFT was designed for was also the moment I least wanted to use SIFT.

OVERWHELMED
→
PICK UP PHONE
→
UNLOCK
→
OPEN APP
→
EXPLAIN
→
WAIT
→
READ
→
INTERPRET
→
ACT

I had designed a cognitively expensive interaction for a cognitively overloaded moment. The intervention also lived inside one of the environments already competing for attention.

Understanding friction wasn't always the same as breaking it.

SO I CHANGED THE MEDIUM ↓
Chapter II — NudgeQ: From cognitive software to physical intervention →