From the inside
Two subjects, both from the side of the people who build the systems. Markets: options pricing, the risk systems underneath them, market data, market making and execution — a derivatives pricing engine and SPAN margining for 400k investors, a greenfield risk system at Revolut, execution and hedging at scale. And AI engineering: the harness, the workflows and the knowledge layer behind building with agents every day. Explanations of this material are not scarce. Knowing which details decide whether it holds up is.
Every page that carries a number runs on the same pricing engine as the calculators, so nothing here can describe a shape the tools do not produce.
Options
14 pagesThe concepts every strategy assumes, then one page per structure — each with a live payoff chart you can edit and open in the calculator.
- Concepts
What an option actually is
Calls, puts, strike, expiry and the difference between intrinsic and extrinsic value — the vocabulary everything else assumes.
The Greeks, without the calculus
Delta, gamma, vega and theta as four questions about the same position, and which one actually kills you.
Implied volatility is the price
Why an option's quoted premium is really a volatility number, and what the smile is telling you.
- Strategies
Long call
The simplest bullish option: defined risk, unlimited upside, and a bill for time decay every day you are wrong.
Long put
Downside exposure with a floor on the loss — the cleanest way to be short without unlimited risk.
Covered call
Own the underlying, sell someone the right to take it from you above a set price, and keep the premium either way.
Cash-secured put
Get paid to bid below the market, with the cash set aside to buy if you are filled.
Bull call spread
Buy a call, sell a higher one. Cheaper than the call alone, with the upside capped at the short strike.
Bear put spread
The same trade pointed down: buy a put, sell a lower one.
Long straddle
Buy the call and the put at the same strike. A bet on movement, indifferent to direction.
Short strangle
Sell an out-of-the-money put and call. Collect premium while nothing happens — and carry an undefined tail.
Iron condor
A short strangle with both tails bought back. Same idea, defined risk, smaller credit.
Long butterfly
A cheap, narrow bet that the underlying finishes at a particular price.
Collar
Hold the asset, buy a protective put, and sell a call to pay for it.
Risk
4 pagesHow the positions above are margined and measured — the systems side, which is the part I actually built.
SPAN, and why your margin is not what you expected
How exchange portfolio margining actually works: the sixteen-scenario risk array, spread charges, and the short option minimum that catches people out.
VAR, and what it does not tell you
Value at Risk in one sentence, the three ways to compute it, the reason it is not a coherent risk measure, and why regulators moved to Expected Shortfall.
DV01 and the shape of rate risk
The one number a rates desk actually watches, how it relates to duration and convexity, and why a single parallel shift is not enough.
Dynamic hedging, and where the premium goes
Sell an option, hedge it to expiry, and watch the premium leave through the hedge — why the price you collect is the price of the gamma you are short.
Markets
3 pagesHow prices arrive and how orders meet them — market data, market making and execution, from the side of the systems that run them.
Market data is a claim about the past
Ticks, books and the plumbing between an exchange and a price on screen: normalisation, conflation, gaps, staleness, and what a composite price quietly hides.
Market making is inventory management
Where a spread comes from, why a market maker skews rather than widens, the reservation price, adverse selection measured by markouts, and when to hedge rather than hold.
Execution, from order to fill
Order types, smart order routing and liquidity aggregation, the latency budget, pre-trade risk checks, and how to measure what execution actually cost.
AI engineering
4 pagesBuilding with models and agents in production: the harness around the model, the workflows that keep it honest, and the knowledge it reads and writes.
The harness is most of the product
A model is one component. The context it is given, the tools it may call, the permissions around them and the checks after them decide whether an agent is useful.
Agentic workflows that hold up
Plan, act, verify — and why the verify step has to be something the model cannot talk its way past: tests, type-checks, property checks, and a human at the irreversible step.
Knowledge bases: typed beats retrieved
Why retrieval over a pile of documents fails quietly, what hybrid search fixes, and why goals, decisions and artefacts work better as typed nodes with provenance.
Product engineering when code is cheap
When an agent can write the diff, the scarce work moves to the spec, the verification and the taste encoded in rules — and the line between product and engineering moves with it.
Library
3 pagesWhere to go when this runs out — one page each for books, series and films.
Books
The reference texts worth owning, the narratives worth reading, and where to look when both run out.
TV series
Longer form gets closer to the texture of the job than any film has managed — desk culture, hierarchy, and the parts nobody puts in a prospectus.
Films
Which films get the culture right even when they bend the mechanics, and which ones to watch knowing exactly what they are.
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