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When Execution Gets Cheap, Advantage Moves

Cheap AI model routing is table stakes. The real advantage is context-rich frontier scouting: finding the work nobody knew to put on the list.

source-derived teaching interpretation verification required verified source identity

AI has made known work cheaper. That is useful, but it is not the strategic frontier. The scarce advantage is now finding the work that did not exist on yesterday's task list.

AI commoditizes known execution. Strategic advantage moves to discovering new work, asking better frontier questions, redesigning workflows, and routing proven patterns back into cheaper execution.

Source dossier

Reader confidence starts with source posture.

Open source video

Source title: You Can't Compete on Cheap Models Anymore.

Source roleStrategy commentary source and teaching prompt, not benchmark authority.
Source/channelAI News & Strategy Daily | Nate B Jones
Publication date2026-07-05
Duration00:15:39
Transcript postureYouTube automatic captions, preserved out-of-band and not reproduced here.
Claim postureVerified identity facts, source claims, teaching interpretation, unresolved details, and softened exclusions are separated.
Verification postureReady with softened wording; exact model-price, porch-workflow, and large-migration details are not verified facts.
Public-safe boundaryNo raw transcript, subtitles, media, screenshots, keyframes, or packet files are published.

Reading posture

Use the source for the strategic contrast: routine execution gets cheaper, but advantage moves to better questions, expert context, workflow discovery, and verification.

Hashimoto and Ghostty identity claims are verified. Model-price, porch-workflow, and large-migration details remain source claims requiring verification.

One-minute brief

Known execution is no longer the scarce part

Known execution is becoming cheap. Cheap model routing is operational hygiene. Frontier scouting is where new workflows are discovered. Proven workflows should move back into cheap execution.

What changedExecution is easier to route.

AI systems increasingly compress the cost and time of known, repeatable work. That makes execution easier to buy, route, and normalize.

Why it mattersCheap execution can converge.

If every team runs the same known task list through similar models, the output converges. Cost falls, but differentiation does not automatically rise.

Reader payoffScout, verify, then route.

Fund expert frontier scouting, verify the discoveries, and route proven repeatable pieces back into cheap execution.

Thesis/article reading lane

The argument before the diagrams

A compact reading path for leaders who need the strategy logic before the operating model, ledger, or prompt suite.

What changed is not just that models got cheaper. Known work is easier to route, repeat, and compress, which makes cheap execution useful operationally. It reduces waste on tasks the organization already understands.

That does not make model routing a strategy. Routing is operational hygiene: it decides how cheaply familiar work moves through the system. Strategy begins when teams ask what work should exist next, which old task list is now obsolete, and where expert context can expose a better frontier.

Frontier scouting means giving context-rich people permission, budget, and verification gates to test questions that were not on yesterday's list. The point is not to celebrate expensive models; it is to find new workflows that cheap execution could not discover by itself.

Once a frontier workflow is proven, it should not stay exotic. The repeatable pieces move back down into cheap execution, where they can be routed, governed, reviewed, and industrialized without confusing routine throughput for discovery.

Leadership takeaway: fund the scouting layer deliberately, verify what it finds, then move proven patterns back into the execution layer.

When everyone can run similar AI workflows at similar cost, differentiation moves to the quality of the question and the originality of the task list.

Two-layer AI strategy stack

Separate execution routing from frontier discovery

The strategic mistake is forcing both jobs into one model-selection decision. Cheap execution and frontier scouting are different layers with different economics.

Top layer

Frontier Scouting

Expert context produces new questions, permissioned bets, and prototypes that did not exist on the old task list.

expert context permissioned bets novel question prototype verification
known tasks route downward
new discoveries prototype upward
proven patterns industrialize downward
Bottom layer

Cheap Execution

Known tasks, repeatable workflow pieces, and verified patterns route into lower-cost execution after the work is understood.

known task repeatable workflow low-cost routing industrialize

Source examples with claim posture

Examples are useful only when their posture is visible

The source supplies strong teaching examples. This artifact keeps their publication status explicit so unresolved details do not become accidental facts.

source claim, verification required

Hashimoto model-cost comparison

Lesson Known tasks can converge across different execution routes.

Verification status Hashimoto and Ghostty context verified; exact model prices and runtimes not published as facts.

Source link Mitchell Hashimoto public site and Ghostty About support identity context only.

Publication-safe wording The source frames a contrast between routine known work and harder expert-shaped work.

source claim, verification required

Porch-marketing workflow

Lesson Frontier scouting can discover workflows that were not on the old marketing list.

Verification status No independent deployment proof used for publication.

Source link Source video only; no external support used for deployment proof.

Publication-safe wording Treat as a source example of a possible workflow pattern, not a verified business case.

analogy only

Factory electrification analogy

Lesson New capability matters most when the operating system is redesigned around it.

Verification status Used as analogy, not as a full industrial-history claim.

Source link Historical support was used only to keep the analogy plausible and bounded.

Publication-safe wording Do not bolt a new power source onto an unchanged layout and call that transformation.

source claim, verification required

Large code migration example

Lesson Frontier execution only scales when the review and verification system can absorb the work.

Verification status Exact Stripe migration numbers remain unresolved.

Source link Source video only; no primary Stripe confirmation used for publication.

Publication-safe wording Use as a source claim about verification infrastructure, not as a confirmed Stripe case study.

Cost trap

Routing is not strategy

The trap is treating model routing as strategy. Routing decides how cheaply known work gets done. Strategy decides which work is worth doing next.

Cheap execution + unchanged task list = faster sameness

Leader diagnostic

The section to screenshot

These questions separate teams optimizing old work from teams discovering new work.

  1. Has the AI task list changed in the last 90 days?Bad signal Old list, faster throughput.Better operating question Which new work became visible?
  2. Are we discovering new work or accelerating old work?Bad signal Savings reported as transformation.Better operating question What changed because the work itself changed?
  3. Who has permission to spend frontier budget?Bad signal Frontier spend requires too many approvals.Better operating question Where can expert context test a bounded bet?
  4. Who has enough context to ask non-obvious questions?Bad signal Prompt access without domain depth.Better operating question Which operators can see the missing workflow?
  5. What review system can absorb a 10x workflow?Bad signal Workflow output grows faster than review capacity.Better operating question What verification gate scales with the output?
  6. Which frontier prototypes can be routed back to cheap execution?Bad signal Prototype never becomes routine capability.Better operating question What repeatable pieces should industrialize?
  7. Where are we mistaking cost optimization for strategy?Bad signal Model routing treated as strategy.Better operating question Which decision is about advantage, not cost?

Operating model loop

Discovery has to become a loop

The frontier model discovers. Governance verifies. Cheap execution scales. The loop matters more than any single model.

01

Scout

Purpose Find questions missing from the old task list.

Failure mode Only cheaper throughput.

02

Prototype

Artifact Frontier experiment with context and permission.

Failure mode Demo without review path.

03

Verify

Owner Domain reviewer plus evidence gate.

Failure mode Source claim becomes fact.

04

Route

Artifact Repeatable execution path.

Failure mode Frontier model used for routine work.

05

Industrialize

Purpose Scale only the verified pattern.

Failure mode New workflow stays bespoke.

Claim / evidence ledger

Claim posture is part of the artifact

Unresolved claims are not styled as verified. That boundary is enforced by the focused validator.

verified fact

Source identity, Hashimoto co-founder context, and Ghostty terminal-emulator identity.

Publishable
source claim

Source framing around routine task convergence and harder frontier-shaped work.

Attributed
teaching interpretation

The two-layer AI strategy stack, cost trap, leader diagnostic, and operating loop.

SharePlane synthesis
unresolved

Exact model prices, model rankings, porch workflow deployment, and Stripe migration numbers.

Not verified
softened or excluded

Exact price/performance claims, vendor endorsement, and proof-like treatment of source anecdotes.

Excluded as fact

Visual prompt suite

Copy-ready prompts for derivative teaching graphics

Each visual concept includes a mainline white variant and a dark expressive variant. Prompt text is selectable and readable without JavaScript; copy buttons are progressive enhancement.

01. Hero Visual

Conveyor-belt execution versus radar-and-blueprint frontier scouting.

Mainline white prompt - Aspect ratio 16:9
Render a mainline white 16:9 premium editorial operating-model illustration for an article titled "When Execution Gets Cheap, Advantage Moves." Purpose: make the strategic contrast legible in one glance. Composition: split the frame into a left execution lane with identical task cards moving through routing nodes and a right frontier-scouting table with blueprint sheets, radar arcs, expert context packets, and prototype branches. Visual hierarchy: the left side is orderly, efficient, and lower-emphasis; the right side is brighter, more spacious, and clearly higher leverage. Palette: warm ivory background, charcoal ink, graphite structure, muted electric blue discovery paths, and small amber verification marks. Objects: conveyor lane, task cards, route gates, blueprint map, radar sweep, context packet, verification stamp. Output intent: usable as a hero or social-card source image with negative space for HTML title overlay. Negative constraints: no logos, readable brand names, fake product UI, people posing, decorative AI brains, neon cyberpunk, raw source material, transcript snippets, benchmark charts, or vendor claims.
Dark expressive prompt - Aspect ratio 16:9
Render a dark expressive 16:9 strategy-board illustration for "When Execution Gets Cheap, Advantage Moves." Purpose: dramatize cost-compressed execution versus context-driven discovery without becoming sci-fi decoration. Composition: left side shows a dim conveyor compressing repeated task cards through routing gates; right side shows a luminous scouting map with radar arcs, blueprint lines, expert context packets, prototype paths, and amber verification gates. Visual hierarchy: execution is low-contrast and repetitive; frontier scouting is crisp, directional, and anchored by the radar sweep. Palette: black, graphite, near-white labels, muted electric blue discovery lines, and amber verification marks. Objects: task cards, routing gates, blueprint table, radar arc, context packet, prototype branch, verification stamp. Output intent: a premium dark hero visual or section opener. Negative constraints: no model dashboards, fake screenshots, robots, glowing brains, logos, raw transcripts, source packet files, price claims, or vendor rankings.

02. Two-Layer Strategy Stack

Frontier scouting, verification, and cheap execution as one operating model.

Mainline white prompt - Aspect ratio 16:9
Render a mainline white 16:9 technical architecture diagram titled "Two-Layer AI Strategy Stack." Purpose: explain that model routing and frontier scouting are separate operating layers. Composition: lower layer contains known tasks, repeatable workflow pieces, low-cost routing, cost meters, and throughput arrows; upper layer contains expert context, permissioned bets, novel questions, prototype branches, and verification gates. Visual hierarchy: upper discovery layer has stronger blue lines and more whitespace; lower execution layer is structured, dense, and amber-gray. Palette: warm ivory, charcoal, graphite, muted blue, amber, and restrained green for proven industrialization. Objects: stack layers, arrows down/up/down, route gates, prototype nodes, verification stamp, industrialized pattern. Output intent: a reference-grade architecture figure for the article. Negative constraints: no vendor logos, model names, exact prices, benchmark charts, fake UI, raw source references, or claims that unresolved examples are verified.
Dark expressive prompt - Aspect ratio 16:9
Render a dark expressive 16:9 operating-model board titled "Two-Layer AI Strategy Stack." Purpose: make the stack feel like a serious field guide rather than a dashboard. Composition: top layer shows frontier scouting with expert context packets, permission tokens, novel question nodes, prototype branches, and verification gates; bottom layer shows cheap execution with known tasks, repeatable workflows, routing lanes, and industrialized patterns. Visual hierarchy: bright blue discovery layer above, subdued amber-gray execution layer below, with three clear arrows: route known tasks down, prototype new work up, industrialize proven pieces down. Palette: black, graphite, near-white, muted blue, amber, and muted green. Objects: layer rails, route arrows, context packets, prototype nodes, gates, industrialization rail. Output intent: a dark technical explainer panel. Negative constraints: no fake software UI, vendor logos, model scoreboards, exact price claims, raw transcripts, or unsupported performance rankings.

03. Old Task List vs New Work List

Fast sameness compared with expanded strategic discovery.

Mainline white prompt - Aspect ratio 4:3
Render a mainline white 4:3 editorial comparison graphic titled "Old Task List vs New Work List." Purpose: show that faster old work is not the same as discovering better work. Composition: left column contains a stale checklist being copied through automation with repeated boxes, duplicated task cards, and a subtle conveyor motif; right column contains a strategic map where branches, question markers, prototype paths, and verification gates emerge from the old list. Visual hierarchy: left side is compact and repetitive; right side is more open, directional, and valuable. Palette: ivory, charcoal, graphite, muted electric blue, amber, and restrained red-orange caution marks. Objects: checklist, duplicate cards, conveyor, question nodes, prototype branches, verification gates. Output intent: a screenshot-worthy section graphic. Negative constraints: no cartoons, stock-photo people, vendor branding, fake dashboards, raw source text, unreadable microtext, or claims that examples are proven deployments.
Dark expressive prompt - Aspect ratio 4:3
Render a dark expressive 4:3 comparison graphic titled "Old Task List vs New Work List." Purpose: make the old-work/new-work distinction immediately visible. Composition: left side shows dim duplicated checklists flowing through a fast automation lane; right side shows a brighter strategic discovery map with branching prototype paths, expert context packets, question markers, and amber verification gates. Visual hierarchy: the old list is repetitive and boxed-in; the new work list has depth, motion, and clear review checkpoints. Palette: black, graphite, near-white, muted blue, amber, and restrained red-orange. Objects: duplicated checklist, automation lane, context packet, question marker, prototype branch, verification gate. Output intent: a dark field-guide visual for the diagnostic section. Negative constraints: no logos, model names, people, neon sci-fi, fake product UI, raw transcripts, packet files, or unsupported business-case proof.

04. Cost Trap

Cheap execution plus an unchanged task list equals faster sameness.

Mainline white prompt - Aspect ratio 16:9
Render a mainline white 16:9 warning-panel illustration titled "Cost Trap." Purpose: communicate that cheap execution plus an unchanged task list creates faster sameness. Composition: a precise routing machine processes identical task cards at lower cost, with compressed cost bars, throughput marks, and repeated outputs; one muted-blue scouting signal sits outside the machine as the missing strategic layer. Visual hierarchy: the machine is crisp and efficient but boxed-in; the scouting signal is smaller but clearly higher leverage. Palette: warm ivory, charcoal, graphite, amber warning accents, muted blue, and restrained red-orange. Objects: routing machine, identical task cards, cost meter, throughput arrows, warning gate, external scouting signal. Output intent: a sober executive warning graphic. Negative constraints: no horror imagery, flames, robots, meme style, logos, fake UI text, vendor rankings, exact prices, or benchmark charts.
Dark expressive prompt - Aspect ratio 16:9
Render a dark expressive 16:9 warning-panel illustration titled "Cost Trap." Purpose: show the danger of treating cheaper routing as strategy. Composition: a graphite routing machine compresses cost while producing identical output cards; amber warning gates and cost meters frame the machine, while a muted-blue scouting signal outside the box points toward the missing discovery layer. Visual hierarchy: repeated outputs dominate the center, warning gates create tension, and the blue scouting cue offers the strategic escape. Palette: black, graphite, near-white, amber, muted blue, and restrained red-orange. Objects: routing machine, task cards, cost bars, warning gates, scouting beacon, review marker. Output intent: a dark section opener with room for the equation in HTML. Negative constraints: no monsters, fires, robots, fake dashboards, vendor logos, model names, raw source material, price tables, or benchmark claims.

05. Factory Electrification

Analogy for redesigning the operating layout around new capability.

Mainline white prompt - Aspect ratio 21:9
Render a mainline white 21:9 cinematic editorial illustration of a factory operating model being redesigned around a new power source. Purpose: use the factory-electrification analogy to explain workflow redesign without presenting it as historical proof. Composition: left side shows an old centralized power spine feeding fixed workstations in rigid sequence; right side shows distributed work cells, local energy nodes, flexible routing, and intelligent flow. Visual hierarchy: old layout is dense and linear; redesigned layout is open, modular, and more capable. Palette: warm ivory paper texture, charcoal industrial linework, muted blue blueprint overlays, graphite structure, and amber annotations. Objects: central shaft, fixed stations, distributed cells, local motors, routing paths, blueprint overlays. Output intent: a wide analogy banner. Negative constraints: no steampunk clutter, fantasy machinery, worker caricatures, brand names, unsafe details, source claims as facts, transcript excerpts, or vendor claims.
Dark expressive prompt - Aspect ratio 21:9
Render a dark expressive 21:9 blueprint-style factory redesign illustration. Purpose: show that new capability should change the operating layout, not merely power the old one. Composition: left side uses graphite linework for an old centralized power spine, fixed stations, and rigid flow; right side uses luminous blue blueprint paths for distributed work cells, local energy nodes, flexible routing, and intelligent process paths. Visual hierarchy: old layout is dim, narrow, and rigid; new layout is brighter, modular, and reviewable. Palette: black, graphite, near-white linework, muted blue overlays, and amber verification markers. Objects: power spine, fixed stations, local nodes, distributed cells, route paths, verification marks. Output intent: a dark analogy panel. Negative constraints: no brand names, people posing, unsafe machinery, neon sci-fi, source excerpts, raw packet material, vendor claims, or literal proof framing.

06. Frontier Scouting Field Guide

Permissioned bets by context-rich experts.

Mainline white prompt - Aspect ratio 4:3
Render a mainline white 4:3 field-guide card visual for AI leaders. Purpose: support a diagnostic section about permissioned frontier scouting by context-rich experts. Composition: a clean tabletop contains a strategic scouting map, radar overlay, context packets, budget tokens, verification stamps, and branching prototype paths, with clear empty zones where HTML diagnostic text can sit. Visual hierarchy: map and radar create the main path; context packets and permission tokens explain who can scout; verification stamps mark what must be checked before scaling. Palette: warm ivory, charcoal ink, graphite grid, muted electric blue discovery paths, amber risk markers, and small green proven-pattern marks. Objects: scouting map, radar arcs, context packet, budget token, prototype branch, verification stamp. Output intent: a screenshot-worthy diagnostic companion visual. Negative constraints: no fake readable text, brand names, people posing, glowing brains, excessive icons, unsupported claims, raw transcript material, or model rankings.
Dark expressive prompt - Aspect ratio 4:3
Render a dark expressive 4:3 field-guide card visual for frontier AI scouting. Purpose: make the leader diagnostic feel practical, executive, and inspectable. Composition: a black tabletop carries radar arcs, expert context packets, prototype branches, budget tokens, amber verification stamps, and small route-back markers for proven workflows. Visual hierarchy: radar arcs lead the eye, prototype branches show discovery, and verification stamps create disciplined checkpoints. Palette: black, graphite, near-white labels, muted blue discovery paths, amber gates, and muted green industrialization marks. Objects: radar arc, context packet, prototype branch, budget token, verification stamp, route-back marker. Output intent: a dark diagnostic header or card image. Negative constraints: no people, magic brains, fake software UI, vendor logos, raw transcript material, model rankings, source packet files, or mystical AI imagery.

07. Operating Model Loop

Scout, prototype, verify, route, industrialize.

Mainline white prompt - Aspect ratio 16:9
Render a mainline white 16:9 process-model diagram titled "Scout, Prototype, Verify, Route, Industrialize." Purpose: show how frontier discovery becomes a repeatable operating loop. Composition: begin with ambiguous signals and expert context, move into prototype branches, pass through verification gates, route repeatable pieces into low-cost execution, and industrialize them into stable workflows; include a feedback path from industrialized workflows back to scouting. Visual hierarchy: five stages are readable left-to-right with a strong loop-back rail; verification is a clear gate, not decorative. Palette: ivory, charcoal, graphite, muted blue, amber verification accents, and restrained green for proven patterns. Objects: stage cards, context signals, prototype branches, verification gate, routing lane, industrialization rail, feedback arrow. Output intent: a clean operating-model figure. Negative constraints: no circular-arrow clipart, 3D gimmicks, vendor logos, unreadable microtext, fake dashboards, raw source files, or unsupported performance claims.
Dark expressive prompt - Aspect ratio 16:9
Render a dark expressive 16:9 technical loop diagram titled "Scout, Prototype, Verify, Route, Industrialize." Purpose: make the operating model feel actionable and governed. Composition: luminous muted-blue discovery paths start at expert context, split into prototype branches, pass through amber verification gates, then route proven repeatable pieces into graphite execution lanes and industrialized workflows; a feedback rail returns learning to scouting. Visual hierarchy: discovery paths glow, verification gates interrupt the path, execution lanes are lower-contrast but orderly. Palette: black, graphite, near-white, muted blue, amber, restrained red-orange for failure modes, and muted green for proven patterns. Objects: context packet, prototype branch, verification gate, routing lane, industrialization card, feedback rail. Output intent: a dark technical field-guide diagram. Negative constraints: no generic process clipart, model names, fake dashboards, raw source files, benchmark claims, vendor logos, or decorative AI motifs.

08. Claim Ledger

Evidence posture as a public design component.

Mainline white prompt - Aspect ratio 16:9
Render a mainline white 16:9 editorial data-panel visual titled "Claim and Evidence Ledger." Purpose: show that evidence posture is part of the public artifact, not a footnote. Composition: a structured ledger with rows for verified fact, source claim, teaching interpretation, unresolved, and softened or excluded; each row has an integrated status marker and an empty content lane for HTML table text. Visual hierarchy: verified and source-backed rows are calm, unresolved rows carry amber caution, excluded rows carry restrained red, and teaching interpretation remains neutral. Palette: warm ivory, charcoal, muted blue, muted green, amber, gray, and restrained red. Objects: ledger rows, status chips, verification stamp, caution mark, exclusion rail, evidence notes. Output intent: a public provenance panel that feels authoritative but readable. Negative constraints: no fake citations, legal clutter, academic stock imagery, raw transcript excerpts, source packet files, fake vendor dashboards, or unsupported verification claims.
Dark expressive prompt - Aspect ratio 16:9
Render a dark expressive 16:9 evidence-ledger panel for a public strategy artifact. Purpose: make claim posture visually clear without making unresolved claims look verified. Composition: a graphite table with category rows for verified fact, source claim, teaching interpretation, unresolved, and softened or excluded; use integrated status markers and a right-side evidence lane. Visual hierarchy: verified uses muted green, source claim uses muted blue, unresolved uses amber, excluded uses restrained red-orange, and interpretation stays neutral. Palette: black, graphite, near-white type, muted green, muted blue, amber, red-orange, and quiet gray. Objects: status chips, ledger rows, verification stamp, caution gate, exclusion mark, evidence lane. Output intent: a dark provenance graphic for article and social reuse. Negative constraints: do not invent citations, show source packet files, use transcript text, depict vendor dashboards, imply unresolved claims are verified, or include benchmark scoreboards.

09. Closing Synthesis

Execution abundance, valuable selection, and context-driven discovery.

Mainline white prompt - Aspect ratio 21:9
Render a mainline white 21:9 cinematic closing banner for a premium AI strategy artifact. Purpose: summarize the final synthesis: execution gets cheap, selection gets valuable, context decides the frontier. Composition: three connected panels flow left to right: abundant execution with many small task cards, valuable selection with one chosen route from many, and context-driven discovery with a blueprint map and radar arcs revealing new paths. Visual hierarchy: the center selection path connects abundance to discovery; the frontier panel should feel decisive without overwhelming the closing text area. Palette: warm ivory, charcoal, graphite, muted electric blue, amber verification highlights, and quiet gray. Objects: task cards, decision path, blueprint map, radar arc, context packet, verification mark. Output intent: a wide closing visual with generous negative space for HTML copy. Negative constraints: no logos, robots, generic globe networks, neon overload, fake text, raw source material, exact model claims, or model rankings.
Dark expressive prompt - Aspect ratio 21:9
Render a dark expressive 21:9 cinematic closing banner for "When Execution Gets Cheap, Advantage Moves." Purpose: close the artifact with a sober, reference-grade strategy image. Composition: three connected pillars read left to right: execution abundance as flowing task cards, selection as a clear chosen path through many options, and frontier context as a radar-blueprint map discovering new work. Visual hierarchy: the chosen path is the spine, amber verification marks anchor trust, and blue discovery lines carry the eye to the frontier. Palette: black, graphite, near-white, muted electric blue, amber, and restrained gray. Objects: task-card flow, decision path, blueprint map, radar sweep, context packet, verification gate. Output intent: a dark closing synthesis banner. Negative constraints: no logos, robots, fake product UI, neon sci-fi, raw source material, source packet files, exact model claims, benchmark charts, or vendor rankings.

Capstone prompt

Use this on one real workflow

Capstone operating prompt
Take one workflow your team already runs through AI. Do not optimize it yet.

First, split the workflow into two layers.

Layer 1: Cheap execution

* What parts are known, repeatable, and low-context?
* Which steps can safely route to cheaper models?
* What outputs are easy to verify?
* What cost, latency, or throughput gains matter?

Layer 2: Frontier scouting

* What question was not on the task list before frontier models improved?
* Who has enough domain context to ask that question well?
* What budget and permission do they need to test it?
* What failure would teach something useful?
* What verification gate must exist before scaling?

Then produce:

1. A revised task list.
2. A frontier scouting experiment.
3. A verification plan.
4. A routing plan for moving proven repeatable pieces back to cheap execution.
5. One sentence explaining what new work became possible.

Do not count time saved until you can name the new work discovered.

Closing synthesis panel

Advantage moves to selection

The question is not whether execution gets cheaper. It does. The question is who uses that abundance to discover better work.

Execution gets cheap

Known workflows can be routed, compressed, repeated, and cost-optimized.

Selection gets valuable

The scarce decision becomes which problems deserve frontier budget and expert attention.

Context decides the frontier

The best new work comes from people with enough domain context to ask non-obvious questions.

Cheap models make execution abundant. Frontier scouting decides what is worth executing.