Dying

Podcast 2 — In conversation

Speaker A: I am never quite sure how formal I should be when using the word dying. It seems to span so many registers.

Speaker B: It genuinely does, and that range is part of what makes it interesting. At the formal end you have dying wish, dying declaration, dying patient — all precise and solemn. At the informal end you have I am absolutely dying, which means roughly the opposite of solemn. Same word, completely different tone.

Speaker A: How do you navigate that in writing?

Speaker B: Context and collocation — the words around it. Dying declaration, dying wish, dying breath — the company these keep signals formality. Dying of embarrassment, dying laughing, absolutely dying — these are informal hyperboles and the surrounding phrasing makes that clear immediately.

Speaker A: What about dying versus dyeing? That is another homophone confusion, is it not?

Speaker B: Yes — and this one catches people because dyeing, the participle of dye, looks identical to dying when spoken. She was dyeing her hair means she was applying hair colour. She was dying for a coffee means she desperately wanted one. Written down they are spelled differently, but a spell-checker will not catch the confusion if the wrong word is also a real word.

Speaker A: I have seen dying breed a lot — is that still current?

Speaker B: Very much so. A dying breed refers to a type of person, practice, or thing that is becoming increasingly rare — perhaps facing extinction but not quite gone yet. Traditional bookshops are a dying breed. Independent music shops. Film photographers. The phrase has enough wistfulness to it that it works even in fairly formal prose.

Speaker A: Are there close synonyms that work well?

Speaker B: Several, each with a different flavour. Fading is gentler — a fading light, a fading hope. Perishing is more formal in British English — perishing in the cold. Expiring carries a slightly bureaucratic feel — an expiring contract, an expiring certificate — though it also works for living things in elevated prose. Passing is a common euphemism for death itself — she passed peacefully. Each synonym shades the meaning differently.

Speaker A: What about declining — is that a near-synonym?

Speaker B: In the sense of weakening over time, yes — but declining lacks the imminence that dying carries. A declining market might recover. A dying market is in its final stages. Dying implies an end is near; declining merely indicates a downward trend.

Podcast 3 — Prompt engineering

Speaker B: Today we use the word dying as the domain anchor for a set of AI prompts spanning healthcare, software engineering, business intelligence, and analytics. The word is precise enough to locate a context immediately, and technical enough to generate appropriately calibrated output. Let us begin with a healthcare UI prompt.

Prompt: Design a UI component for a hospital patient management system showing a clinical care stage timeline. The timeline progresses from admission through acute care, critical care, palliative care, and end-of-life planning stages. Use subdued, respectful colour tones. Clinical staff can update the current stage using a dropdown with a timestamp confirmation. The component must be accessible with ARIA labels and work on tablet screens used at bedside.

Speaker B: The phrase end-of-life planning rather than dying keeps the language clinical and appropriate for a healthcare interface while still communicating the domain clearly to the AI. The bedside tablet specification drives a responsive, large-touch-target design. The ARIA requirement makes it usable with screen-reader assistive technology.

Speaker A: End-of-life planning as a phrase does a lot of work there without being either euphemistic or blunt.

Speaker B: That is the art of healthcare vocabulary in UI briefs. Here is a database design prompt.

Prompt: Create a database schema for a hospice care management system. Include a patients table with a current_status enum containing values: admitted, stable, deteriorating, critical, palliative, and end_of_life. Add care_plans linked to patients, staff_assignments with shift records, medication_schedules with dosage and frequency, and a dying_wishes table recording documented patient preferences for end-of-life care, linked to a legal_representative contact.

Speaker B: The dying_wishes table is the detail that makes this schema clinically complete. In hospice care, documented patient preferences are legally and ethically significant. By naming the table explicitly, the AI generates a properly relational structure with a legal representative link — something a generic patient management schema would never produce unprompted.

Speaker A: That legal representative link would be genuinely important in a real system.

Speaker B: Exactly — legal representatives have rights of access and notification. Here is a software engineering prompt.

Prompt: Build a session timeout handler for a web application that treats an expiring session as a dying session. When the session has two minutes remaining, display a full-page overlay with an animated countdown timer and two options: extend my session and log out securely. If no action is taken before the timer reaches zero, cancel all pending requests, clear local storage, and redirect to the login page with a session expired message.

Speaker B: The phrase dying session signals to the AI that this is a graceful degradation problem — not a crash, but a controlled wind-down. Cancelling pending requests before redirect prevents data corruption. Clearing local storage prevents credential leakage. The overlay design ensures the user cannot accidentally ignore the warning.

Speaker A: The cancel pending requests step is often forgotten in session timeout implementations.

Speaker B: And it causes subtle bugs when overlooked. Here is a full application prompt.

Prompt: Generate a complete legacy preservation platform for elderly and terminally ill users. Features: a life story recorder with video and audio upload, message scheduling to deliver emails or videos to named recipients on future dates specified by the user, a digital asset assignment tool mapping online accounts and files to designated beneficiaries, a trusted contact system for account management after the user can no longer access the platform themselves, and strict privacy controls including data deletion on request.

Speaker B: The phrase terminally ill users defines a population with specific needs — the platform must be simple enough to use when health is declining, emotionally supportive in its tone, and legally robust in its asset assignment. Those requirements cascade from that single phrase into every design decision: large text, clear navigation, no dark patterns, and legally binding asset records.

Speaker A: The trusted contact system is something most platforms do not think about until they receive a complaint.

Speaker B: Platforms that serve elderly users need to build that in from day one. Here is a business analytics prompt.

Prompt: Build a dying metrics dashboard for a retail business. Identify product lines whose revenue has declined for three or more consecutive quarters, classify them as dying lines, and display each with its current quarter revenue, percentage decline rate, and estimated quarters until zero revenue. For each dying line, calculate the cost of maintaining it versus discontinuing it and display a recommended action: monitor, review, or discontinue.

Speaker B: Dying lines as a business classification generates a precise analytical framework — not just declining but three consecutive quarters of decline, a threshold that filters out seasonal fluctuations. The cost-versus-discontinuation calculation makes this an actionable decision support tool rather than a passive report.

Speaker A: The estimated quarters until zero revenue is a number I have never seen in a dashboard but it would be very useful.

Speaker B: It focuses the conversation. Here is an SEO analytics prompt.

Prompt: Create a dying keywords tracker for an SEO analytics tool. Monitor a portfolio of target keywords and flag any keyword whose monthly search volume has declined by more than twenty percent for two consecutive months as a dying keyword. Display the keyword, its peak volume month, current volume, percentage decline, and three suggested replacement keywords with rising search volume. Generate a monthly alert report for keywords entering dying status.

Speaker B: Dying keyword as a classification maps precisely onto declining search volume trends. The two-month threshold prevents false positives from seasonal patterns. Replacement keywords with rising volume converts a problem report into an actionable recommendation — the AI generates a complete research and alert system from a single domain concept.

Speaker A: Suggested replacements turn this from a warning into a workflow.

Speaker B: And here is a systems engineering prompt.

Prompt: Build a process watchdog module for a Node.js application that detects dying processes. Monitor all child processes and flag any process as dying if it exhibits abnormal CPU usage above ninety percent for thirty consecutive seconds or memory consumption above the configured threshold for sixty seconds. On detection, log the dying process identifier, resource metrics, and timestamp, attempt a graceful restart, and if the restart fails three consecutive times, send an alert via the configured webhook and mark the process as terminated.

Speaker B: Dying process as a technical state is more informative than crashed or failed — it captures a process in degradation before final termination, allowing the watchdog to intervene gracefully. The three-consecutive-failure threshold prevents restart loops from consuming resources indefinitely. The webhook alert makes the system observable from external monitoring tools.

Speaker A: Detecting the dying state rather than waiting for the crash is the whole value of a watchdog.

Speaker B: Exactly. And the word dying put the AI in precisely the right conceptual space to generate that design.