Drishti
The Drishti Framework
How to apply the seven lenses to anything — plus a Bayesian forecasting sketch.
The seven lenses
| Lens | Question |
|---|---|
| What Exists | What is this, really? |
| What Changes | What is stationary vs non-stationary? |
| What Flows | What moves? Where are bottlenecks? |
| What Learns | What updates, remembers, optimizes? |
| What Persists | What survives change? |
| What Emerges | How do simple rules → complexity? |
| What Will Happen | Which futures are becoming likely? |
Walk them in order the first time. Later, jump to the lens that matches your confusion.
Universal case study template
- TL;DR — three bullets
- Phenomenon — one-sentence definition
- Seven lens blocks — collapsible sections, same order every time
- Curriculum bridge — links to mechanism topics
- Forecasting snapshot — optional under What Will Happen
Forecasting walkthrough (Bayesian sketch)
Start with a prior — what you believed before today’s evidence.
Add likelihoods — how probable is this evidence if each future were true?
Compute posterior — where probability mass moves after observing reality.
Repeat — forecasting is a loop, not a ceremony.
flowchart LR Prior["Prior beliefs"] --> Evidence["New evidence"] Evidence --> Posterior["Updated beliefs"] Posterior --> Action["Intervene on leading indicators"] Action --> Evidence
The What Will Happen lens page includes an interactive Bayesian updater lab.
When to use Drishti vs curriculum
| You want… | Go to… |
|---|---|
| See any phenomenon clearly | Drishti lenses + case studies |
| Learn the math and code | Curriculum topics + labs |
| Both | Start Drishti → follow bridge links |
Try it now
Pick something bothering you today. Spend five minutes answering only What Exists and What Flows. Stop. Notice if the problem already looks different.