Assets live inside world events, policy regimes, and macro cycles

A generic research prompt often focuses on the asset itself: recent filings, current headlines, technical signals, or analyst commentary. That can miss the broader environment in which the asset lives. iPulse adds global context so the model considers policy shifts, monetary regimes, geopolitical stress, technology cycles, energy constraints, and cross-asset market behavior.

Many modern language models have a training or reliable knowledge window that ends before the current date. Some models also have tools such as web search or retrieval, but those tools do not automatically guarantee that every relevant macro event, policy shift, and market regime change is understood in the right context.

A simple deep-research prompt about one asset usually searches for that asset, its company news, filings, and analyst commentary. It rarely builds a full recent understanding of global policy, fiscal stress, trade regimes, war risk, liquidity, currencies, commodities, AI infrastructure, and macro data before answering. iPulse supplies that broader context because assets live inside those regimes.

Public model providers also document model capabilities and knowledge windows. Examples include the OpenAI model catalog and Anthropic model overview.

iPulse maintains dated markdown context files for global macro and market events. A file-backed manifest selects the latest matching context documents for the relevant period, then prompt assembly loads and inserts those documents at generation time.

<2025_full_year_context>

# 2025 GLOBAL RETROSPECTIVE: ARCHIVE FOR STRATEGIC REASONING
**Yearly Theme:** Geopolitical Fragmentation, AI Moat Disruption, and Fiscal Volatility.
**Data Cutoff:** December 31, 2025.
**Status:** Full event coverage preserved. Quarterly and full-year high-impact summaries are integrated; monthly quantitative series remain working values pending final audit.

## EXECUTIVE SUMMARY: 2025 INFLECTION POINTS
* **The DeepSeek Shock (Jan 27):** A low-cost, high-capability Chinese LLM broke the prevailing "compute moat" thesis and triggered a historic AI hardware repricing.
* **US Policy Pivot (Jan 20):** The new US administration signed 26 day-one executive orders, withdrew from WHO and Paris, and launched DOGE.
* **Tariff Regime Escalation (Feb-Apr):** Early tariffs expanded into April's "Liberation Day" structure, followed by Chinese retaliation and rare-earth restrictions.
* **Conflict Volatility:** India-Pakistan (Three-Day War) and Israel-Iran (Twelve-Day War) sharply raised global tail-risk and energy-route stress.
* **Monetary Regime Shift (Sep-Dec):** The Fed moved from prolonged hold to three 25 bps cuts amid data disruption and shutdown-driven uncertainty.

| Quarter | US GDP (QoQ / SAAR) | Fed Action | S&P 500 QTR | Primary Catalyst |
| :--- | :--- | :--- | :--- | :--- |
| **Q1** | -0.2% / -0.8% SAAR | Hold | -4.6% | DeepSeek Shock + Policy Reset |
| **Q2** | +0.9% / +3.8% SAAR | Hold | +10.6% | Liberation Day Tariffs + Middle East Escalation |
| **Q3** | +1.1% / +4.4% SAAR | -50 bps (first cut) | +7.8% | Fed Pivot + US Shutdown Onset |
| **Q4** | +0.2% / +0.7% SAAR | -50 bps (2 cuts) | +2.3% | Data Blackouts + AI Bubble Deflation Signals |

The context archive is not only prose. It includes month-level event structure, market snapshots, macroeconomy tables, and quarterly performance tables. Below are representative excerpts copied from the 2025 local archive to show the structure used by prompt assembly.

Monthly structure excerpt

## JANUARY 2025: INSTITUTIONAL RUPTURES, DEEPSEEK, AND BIO-ENGINEERING
<january_2025_summary>
Focus: European legal-energy realignment, US executive restructuring, and a structural break in AI valuation logic.
</january_2025_summary>

### January 01, 2025: European Architecture Reset and Solar Intelligence Milestone
* **1. Schengen Expansion (Bulgaria and Romania):** Bulgaria and Romania formally integrated into Schengen, reducing cross-border friction and freight costs across Eastern Europe.
* **2. Ukraine Joined the ICC as a State Party:** Ukraine officially joined the International Criminal Court, shifting legal parameters of the war and strengthening wartime accountability mechanisms.
* **3. Ukraine Halted Russian Gas Transit:** A five-year transit agreement expired and Russian gas transportation across Ukraine stopped, accelerating LNG procurement, lifting spot prices, and strengthening energy-transition capital flows.

### January 26-29, 2025: DeepSeek Shock and Monetary Pause
* **1. Belarus Election Outcome:** Alexander Lukashenko was re-elected in a tightly controlled process.
* **2. The DeepSeek Shock (Jan 27):** A highly capable low-cost Chinese model challenged frontier reasoning economics without matching Western silicon intensity; Nasdaq repriced sharply and Nvidia lost about $600 billion in single-session market value.
* **3. FOMC Hold (Jan 28-29):** Federal funds rate remained at 4.25%-4.50%.

<january_2025_monthly_market_snapshot>
**Top market notes:**
- Inauguration policy reset lifted risk assets initially, but markets already priced tariff-led inflation and rising policy volatility.
- Bitcoin crossing 100k reflected institutional inflows and reserve-asset narrative, not only retail momentum chasing.
- Gold strength signaled central-bank diversification pressure and early skepticism toward fiat stability under aggressive trade policy.

| Category | Indicator (Reference) | Monthly Low | Monthly High | Close | % Change (MoM) |
| :---- | :---- | :---- | :---- | :---- | :---- |
| Metals | Gold (XAU/USD) | $2,614.89 | $2,817.12 | $2,796.33 | +5.76% |
| Metals | Silver (XAG/USD) | $30.06 | $32.56 | $31.31 | +8.45% |
| Crypto | BTC/USD | $99,848.45 | $108,169.15 | $104,008.80 | +11.28% |
| Energy | Brent Crude Oil (Global) | $73.44 | $79.56 | $76.50 | +6.66% |
| Forex | EUR/USD | 1.121 | 1.210 | 1.165 | +2.04% |
| Index_Equity | S&P 500 (SPX) | 5,793.41 | 6,131.14 | 6,040.53 | +2.70% |
</january_2025_monthly_market_snapshot>

<january_2025_monthly_macroeconomy_snapshot>
**Top macroeconomy notes:**
- Executive transition shifted expected US policy mix toward tariffs and unilateral trade enforcement, lifting uncertainty premiums across global planning cycles.
- America First memo triggered preemptive supply-chain repricing before tariffs hit, raising expected pass-through to inflation-sensitive baskets.
- Central-bank gold accumulation signaled strategic reserve diversification ahead of prolonged dollar weaponization and sanctions-fragmentation risk.

**Economic data table (source: January 2026):**
| Indicator | Value | MoM % Change / Change |
| :---- | :---- | :---- |
| US M2 Money Supply | $22,469.1 Billion | +0.37% |
| Global M2 (Big 4 USD) | $99,850 Billion (Est.) | +0.35% |
| US CPI (YoY) | 2.4% | -0.3% |
| Eurozone CPI (YoY) | 1.7% | -0.4% |
| China CPI (YoY) | 0.2% | -0.6% |
| Fed Funds Rate (US) | 3.50%-3.75% (Range) | 0 bps |
| ECB Deposit Rate (EU) | 2.00% | 0 bps |
| 1-Y Loan Prime Rate (CN) | 3.00% | 0 bps |
| 10Y-2Y Treasury Yield Spread | 0.67% | +3 bps |
| CBOE Volatility Index (VIX) | 18.45 (Close) | +14% |
</january_2025_monthly_macroeconomy_snapshot>

Quarterly quantitative excerpt

### Q1 2025 GDP

| Economy | GDP Level (Real, local currency) | QoQ Change (%) | YoY Change (%) | SAAR (US only) |
| :---- | :---- | :---- | :---- | :---- |
| United States | 23,548.21 bn chained 2017 USD | -0.2% | +2.0% | -0.8% (early est.) |
| Eurozone | 2,868,226.3 mn chained 2010 EUR | +0.6% | +1.6% | N/A |
| China | 31.88 tn CNY (current) | +1.2% | +5.4% | N/A |
| India | INR 77.41 lakh crore (real approx) | +1.4% | +7.8% | N/A |

### Q1 2025 Broader Economic Indicators (Excluding GDP)

| Category | Indicator (Reference) | Current Value | QoQ Change (%) | YoY Change (%) |
| :---- | :---- | :---- | :---- | :---- |
| Labor | US Unemployment Rate | 4.2% | +0.1% | +0.1% |
| Labor | Eurozone Unemployment | 6.3% | +0.1% | +0.1% |
| Debt | US Debt-to-GDP | 123.1% | +0.9% | +1.1% |
| Debt | Global Debt-to-GDP | 235.8% | +0.2% | +0.5% |
| Wealth | Global Equity Market Cap | $83.4 T | -2.2% | +2.9% |
| Banking | Central Bank Total Assets (Fed) | $7.02 T | -0.6% | -2.5% |
| Earnings | S&P 500 EPS Growth | 13.7% | +1.1% | +2.5% |
| Real Estate | US Home Price Index (Case-Shiller) | 324.4 | +0.8% | +5.2% |
| Real Estate | Dubai Residential Index | 19,118 AED | +3.6% | +5.9% |
| Real Estate | Eurozone House Price Index | 153.2 | +1.7% | +5.3% |

Long-context language models can under-weight information placed in the middle of a large prompt. This is often called the lost-in-the-middle problem. iPulse compensates by repeating the most important orientation and grounding information near the beginning and the end of long context blocks and assembled prompts.

A major value of iPulse is not only having a better prompt. It is running the same carefully prepared context at scale across many assets, AI Agents, horizons, and configurations. Because the global context and stable prompt prefix are reused, iPulse can use internal assembly caching and provider-side prompt caching where supported. That makes repeated execution structurally more efficient than individual users typing one-off prompts manually.

Example deep-analysis sweep:

Assets: 300
AI Agents per asset: 12
Total forecast tasks: 300 x 12 = 3,600

If each task uses a 300,000-token input context:
3,600 x 300,000 = 1,080,000,000 input tokens

If each task reserves 305 reasoning-budget tokens:
3,600 x 305 = 1,098,000 reasoning-budget tokens

If each task produces 20,000 output tokens:
3,600 x 20,000 = 72,000,000 output tokens
72,000,000 output tokens x 0.75 words/token = about 54,000,000 output words

Per single asset across 12 AI Agents:
12 x 300,000 = 3,600,000 input tokens
12 x 20,000 = 240,000 output tokens
240,000 output tokens x 0.75 = about 180,000 output words

Global context is only useful when tied back to the actual asset. For equities, iPulse can provide recent close price context, monthly price statistics, annual fundamentals, quarterly fundamentals, and derived financial metrics. For other asset categories, the input format focuses on market price and category-relevant context.

Researcher mode is most useful when the relevant evidence is narrow, current, or external to the prepared context. For example, a Machiavelli-style AI Agent may benefit from checking lobbying spend, procurement exposure, regulatory relationships, sanctions pressure, or political connections that are too specific to include in the general context bundle.

Thinker mode can reason deeply from provided context and data. Researcher mode can expand the evidence base when the task needs additional external discovery.