Contextually Aware

Episode 37: I maxed out my context window

Luis and Maya unpack the hidden bottleneck in agent-heavy work: the human approval queue. The fix is less clever tooling, fewer harnesses, one queue, and a daily count of real decisions.

Chapters

• 00:00 — Meet your host
• 00:42 — The setup
• 01:24 — What the article says
• 02:06 — The killer line
• 02:48 — The new way to think
• 03:30 — Concrete moves
• 04:12 — One thing to remember
• 04:54 — Where to find us
• 05:36 — Sign-off

Read the full article →

Moonshot paused new Kimi K3 subscriptions 48 hours after launch because GPU demand pushed them to capacity. They chose reliability over growth.

The open weights drop July 27. For builders: stop treating your model choice as a permanent commitment. Wrap it behind an interface. Treat it as a config value.

Read the full article: https://growthalchemylab.com/blog/kimi-k3-the-pause-that-tells-you-everything

Luis and Maya dig into the $700B hyperscaler capex bet and why falling AI model prices could leave a third of the S&P 500 mispriced. The math is falsifiable — and the clock is already running.

This episode is in DRAFT and has not been published yet.

Luis and Maya cut through OpenAI's Sol/Terra/Luna model catalog with one operator rule: pick a default, escalate effort before model, and stop treating the picker like a menu.

Read the full article: https://growthalchemylab.com/blog/openai-model-guide-confused-choices

An $8 multi-agent website build beat a $105 solo build on accessibility — and it proves hallucination isn't solved, it's routed. Luis and Maya break down the org-chart model for trustworthy AI.

Read the full article: https://growthalchemylab.com/blog/has-agi-arrived-send-in-the-misfits

This episode is in DRAFT and has not been published yet.

The production curve for generating code is steeper than understanding it. Teams that win store decisions, not commits—and specs are the moat.

This episode is in DRAFT and has not been published yet.

Why stuffing context into markdown files breaks production AI agents, and the six-layer memory architecture that actually works at scale.

This episode is in DRAFT and has not been published yet.

Production agents hit a wall around day 30: context drift, not retrieval, is the killer. Vector stores can't manage state across multi-agent workflows. The fix is treating memory like an operating system.

This episode is in DRAFT and has not been published yet.

Luis explores five conditions that should trigger a pause before deploying an AI agent—and why a queue, form, or policy often solves the problem faster than autonomy.

This episode is in DRAFT and has not been published yet.

Luis walks through five coordination failures that emerge when agent systems scale past single digits—memory contention, context bloat, skill drift, context corruption, and operator blindness. The fix: a memory OS layer that governs writes, gates context, standardizes skills, checkpoints state, and

This episode is in DRAFT and has not been published yet.