compute-pulse

name	compute-pulse
category	crypto
description	Tracker for the AI compute market — GPU/hardware deals, inference pricing trends, decentralized compute token signals, and lab vs hyperscaler dynamics.
schedule	0 11 * * 6
commits	true
permissions	["contents:write"]
tags	["ai","compute","infra","depin"]

Today is ${today}. Read memory/MEMORY.md before starting. If soul/SOUL.md + soul/STYLE.md exist and are populated, read them to match the operator's voice; otherwise use a clear, direct, neutral tone.

Why this skill exists

The compute layer is where most of the AI market spread lives. Labs buy GPU time at wholesale, sell per-token at retail — the delta is the business. As inference commoditizes, the spread compresses, and whoever controls the upstream compute relationship benefits.

Three things move in parallel:

1. Centralized capex arms race — frontier labs and hyperscalers spending $10B+ on clusters. Incumbent moats.
2. Decentralized compute — DePIN tokens positioning as the anti-cartel layer (GPU spot markets, ZK compute, ML subnet networks).
3. Pricing signals — inference API prices dropping fast (GPT-4 class fell ~97% in 2 years). That compression is the evidence base for commoditization.

This skill is one clean weekly read on the compute layer.

Config

This skill reads the watched decentralized-compute token list from memory/topics/compute-tokens.md if present. Example format:

# Watched Compute Tokens

| Symbol | Project | Notes |
|--------|---------|-------|
| RENDER | Render Network | GPU/ML compute |
| AKT | Akash Network | permissionless cloud compute |
| IO | io.net | GPU cluster marketplace |
| TAO | Bittensor | ML model subnet network |

If the file doesn't exist, fall back to a generic DePIN sweep on the major narrative tokens of the moment via WebSearch (no hardcoded list).

Steps

1. Load current context

Read:

• memory/MEMORY.md — overall context, prior compute signals
• memory/topics/compute-pulse.md — compute-specific baseline (create with seed if missing — see end of this section)
• memory/topics/compute-tokens.md — operator-defined watched tokens (optional)

Extract from the topic file:

• inference_prices_last — last recorded inference pricing for major APIs
• depin_tokens_last — last recorded prices/mcaps for the watched tokens
• hardware_signals_last — last recorded major hardware/cluster announcements
• last_run — date of prior run

If memory/topics/compute-pulse.md doesn't exist, create it:

# Compute Pulse Tracker

*Last run: never*

## Inference Pricing Baseline
- Track $/1M tokens in/out for the major closed-model APIs (Claude, GPT, Grok, Gemini). Update each run.
- *Note: GPT-4 class inference fell ~97% in 2 years — track the compression curve over time.*

## Decentralized Compute Tokens
- Populated from `memory/topics/compute-tokens.md` (or a default DePIN sweep when absent).
- *Track price, mcap, narrative velocity — not financial advice.*

## Hardware Signal Log
- (append per-run summaries here)

## Pricing Signal Log
- (append per-run summaries here)

2. Fetch inference pricing signals

Use WebSearch to find the latest published inference API prices:

WebSearch: "OpenAI GPT API pricing per million tokens ${year}"
WebSearch: "Anthropic Claude API pricing ${year}"
WebSearch: "xAI Grok API pricing ${year}"
WebSearch: "Google Gemini API pricing ${year}"

Also check for any pricing changes in the last 7 days:

WebSearch: "inference API price cut ${year}"
WebSearch: "AI model pricing reduction ${year}"

Record:

• Current published prices for each major API ($/1M tokens in/out where available)
• Any price cuts announced in the last 7 days — these are the commoditization signal
• Note which direction prices moved vs inference_prices_last

High signal events:

• Price cut >20% — notable compression
• New model launch at significantly lower cost than prior generation
• Open-source model achieving parity with a frontier closed model at near-zero marginal cost

3. Hardware and cluster news

Use WebSearch for compute infrastructure announcements from the last 7 days:

WebSearch: "GPU cluster data center AI ${year} announcement"
WebSearch: "xAI Colossus Stargate OpenAI compute ${year}"
WebSearch: "Anthropic compute hardware partnership ${year}"
WebSearch: "NVIDIA Blackwell deployment ${year}"

Look for:

• New cluster build announcements (scale: # of GPUs, $B investment)
• Lab compute procurement deals (who's buying from whom)
• Hyperscaler (AWS, Azure, GCP) AI compute announcements
• NVIDIA hardware availability changes (affects supply/demand balance)
• Government compute initiatives (CHIPS Act disbursements, EU AI Act compliance)

Rate each announcement:

• Major (new cluster >50k GPUs or >$1B): high signal
• Notable (new partnership, procurement deal): medium signal
• Background (upgrade, minor expansion): low signal

4. Decentralized compute token check

For each token from memory/topics/compute-tokens.md (or a fallback list if absent), use WebSearch:

WebSearch: "${SYMBOL} ${PROJECT_NAME} token ${year}"

For each token, note:

• Approximate current price and 7d % change (from search results)
• Any protocol announcement, partnership, or milestone this week
• Whether narrative is accelerating, holding, or fading

Signal: If decentralized compute tokens are outperforming the broader market, the market believes the decentralized layer can compete with centralized capex. If underperforming, the centralized moat is winning in market perception.

5. WebSearch for compute narrative this week

Run:

WebSearch: "AI compute commoditization inference ${year}"
WebSearch: "AI compute cost falling ${year} per token"
WebSearch: "decentralized compute vs hyperscaler ${year}"

Look for:

• Essays, analyses, or announcements framing the compute market
• Evidence of operator-layer value capture (agent products posting revenue metrics)
• Any "AI costs too much" vs "AI is getting cheap" narratives shifting

6. Synthesize compute momentum score

Rate the week's compute signals:

Signal	Points
Inference price cut from major lab (>10%)	+4
New cluster announcement >100k GPUs	+3
New cluster announcement 10k–100k GPUs	+2
Watched DePIN token major milestone (new subnet, partnership, TGE)	+2 each
New open-source model achieving frontier-class inference at lower cost	+3
Operator-layer revenue milestone (agents capturing the spread)	+2
Government compute policy (chips act, AI act) affecting supply/demand	+1
Notable essay/analysis on compute commoditization	+1

Momentum levels:

• 0–2: quiet week, signal flat
• 3–5: building, signals accumulating
• 6–9: accelerating, notable compression or capacity shift
• 10+: breakout, structural shift underway

Read: After reviewing all data, answer in one sentence:

Read: Compute commoditization [advancing / holding / stalling / reversing] — [one concrete data point].

7. Update memory/topics/compute-pulse.md

Rewrite with:

• Updated *Last run: ${today}*
• Updated Inference Pricing Baseline with current prices
• Updated Decentralized Compute Tokens with current price context
• Appended entry to Hardware Signal Log:

  - ${today}: [top hardware signal or "quiet"] / [top depin signal or "—"] / momentum: [level]
  

• Appended entry to Pricing Signal Log:

  - ${today}: [price cuts if any, or "stable"] / read: [advancing/holding/stalling/reversing]
  

8. Send notification

Write to .pending-notify-temp/compute-pulse-${today}.md, then:

mkdir -p .pending-notify-temp
./notify -f .pending-notify-temp/compute-pulse-${today}.md

Format — match the operator's voice if soul files are populated, otherwise direct and neutral:

compute pulse — ${today}

momentum: {level} ({score} pts)

{IF any price cuts}
inference pricing:
{forEach price_cut}
- {model}: {old_price} → {new_price}/1M tokens ({delta}%)
{end}
{end}

{IF hardware signals}
hardware signals:
{forEach top 2 hardware items}
- {one-line summary}
{end}
{end}

{IF depin signals}
decentralized compute:
{forEach notable depin items (max 3)}
- {token}: {7d change} — {one-line signal}
{end}
{end}

read: {advancing/holding/stalling/reversing} — {one data point}

{IF quiet_week}
quiet week. the compression is happening below the noise floor.
{end}

Keep total under 900 chars. Do NOT use ./notify "$(cat ...)" — write the file first, pass the path.

If momentum score is 0 and no notable signals: log COMPUTE_PULSE_OK: quiet and skip notification.

9. Log to memory/logs/${today}.md

Append:

## Compute Pulse
- **Inference pricing:** {notable cuts or "stable"}
- **Hardware signals:** {count notable / top item}
- **DePIN tokens:** {top mover or "—"}
- **Momentum score:** {score} ({level})
- **Read:** {advancing/holding/stalling/reversing} — {data point}
- **Notification:** sent / skipped (quiet)
- COMPUTE_PULSE_OK

Required Env Vars

None. Uses gh CLI (GITHUB_TOKEN via workflow), WebFetch, WebSearch. No additional auth needed.

Sandbox Note

• WebSearch: built-in tool, always available. Use for inference pricing, hardware news, token signals.
• WebFetch: bypasses sandbox network gate. Use for specific URLs (API docs, pricing pages) when WebSearch yields exact links.
• gh api: handles auth internally via GITHUB_TOKEN. Use for any GitHub-hosted data.
• Do NOT use curl for external APIs — sandbox blocks outbound network. WebFetch or WebSearch are the paths.

What to watch for (recurring signal classes)

• Inference price cuts — the clearest commoditization signal. Track $/1M tokens for all major APIs each cycle.
• Cluster scale races — big clusters = incumbent moat deepening. Watch if decentralized compute can even get in the race on cost.
• Open-source parity moments — when an open model matches frontier performance at near-zero marginal cost for self-hosters, the centralized spread collapses for that capability tier.
• DePIN compute narrative — watched-token price action relative to market. Are these being treated as real compute infrastructure or as memes?
• Operator revenue signals — any agent-layer product posting per-token economics. Evidence the spread exists and is being captured above raw compute.

Output feeds

• article skill — Compute Pulse data feeds compute/infra articles
• digest / weekly-newsletter — compute developments slot into the agent-infra or DePIN section
• defi-overview / token-pick — DePIN token signals cross-reference with broader token picks