Files
WebinarNotes/wiki/concepts/context-as-scarce-resource.md

42 lines
3.2 KiB
Markdown
Raw Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
# Context as the Scarce Resource
#concept
## Summary
Across sources, the binding constraint on agents is **context**, not model IQ. Managing it — what you load, when, and how long the agent stays sharp — is the core engineering discipline. Konstantin: the model has a **"smart zone"** (roughly the first third of context) where it's sharpest; beyond that it dulls, even with a million-token window.
## Current Understanding
Context pressure explains several otherwise-separate design choices:
- **Tool ceilings** — every injected tool costs context, so harnesses cap at ~3040 tools and >100 confuses even Fable 5. See [[harness]].
- **Two-stage skill loading** — short descriptions always visible, long `SKILL.md` loaded on demand — is *the* trick that lets hundreds of [[skills-as-memory|skills]] coexist. See [[evolution-of-agent-tooling]].
- **Ralph loop** keeps the agent in the smart zone by restarting instead of letting context grow → summarize → decay. See [[agentic-loops]].
- **Skills-as-memory > RAG** — the harness decides what to load *when a skill activates*, rather than RAG pre-injecting facts before the model even starts.
- **Context engineering** (Allie) — "feeding the system who you are" via foundation docs — is the same idea from the user side. See [[personal-ai-operating-system]].
The human role has climbed prompt-engineer → **context-engineer** → harness-builder → loop-engineer, tracking exactly this concern.
**The supply-side facet** ([[2026-07-22-ai-is-stupid]]): before context is *scarce* it is usually *absent*. "Intelligence without context loses to context without intelligence" — ten Nobel laureates asked about your sales month can only cite industry averages, while your rank-and-file employee answers better because they see your funnel, clients, and deals. The default "stupid AI" experience is a strong model given neither business context nor a [[harness]]; the fix is investing in context infrastructure (data, memory, integrations) before reaching for a bigger model.
## Evidence
- Smart zone, summarization decay, "context is the most valuable resource," tool/skill loading mechanics — [[2026-07-14-skills-based-on-git]].
- Context engineering vs prompt engineering; foundation docs as durable context — [[2026-07-14-gap-between-ai-users-irreversible]].
- "Intelligence without context loses"; Nobel-vs-employee analogy; invest in context before model upgrades — [[2026-07-22-ai-is-stupid]].
## Related Pages
- Concepts: [[harness]], [[skills-as-memory]], [[agentic-loops]], [[evolution-of-agent-tooling]], [[personal-ai-operating-system]]
- Entities: [[konstantin]], [[allie-miller]]
## Contradictions / Uncertainty
- "First third = smart zone" is a heuristic, not a measured boundary; likely model-dependent. Status: tentative.
- [[2026-07-22-ai-is-stupid]] names **RAG** and long-term assistant memory as the practical context mechanisms; [[2026-07-14-skills-based-on-git]] argues [[skills-as-memory|skills]] beat RAG (load-on-activation vs pre-injection). Possibly audience-driven (business data vs procedures) rather than a real disagreement. Status: tentative.
## Next Questions
- How do you measure where a given model's smart zone actually ends?