# Kairos Design Partner Brief — 2026-09-26

*Generated 2026-09-26T08:00:01Z — every number below is measured, carries its source and as-of time, and can be re-derived from the live API. Windows are stated; nothing is interpolated or forecast.*

## The verdict

**What is scarce here.** Both halves of a utilisation ratio — capacity AND consumption — on 6 networks: AKT, FIL, FLUX, IO, SC, TFT. Node counts are public everywhere; the denominator is not. This is the entire reason the ledger below can exist, and it is why coverage, not commentary, is what we sell.

**The sharpest thing the data says this week.** AKT compute_cores: utilisation 20.55% → 38.12%, with demand growing 72.75pp faster than capacity over the window.

Recorded use grew faster than capacity over this window. This does not establish a capacity bottleneck, paid demand, or an onboarding constraint.

**Also this week:** 12 metric-name candidates with unchanged stored observations (cause unverified); 159 of 230 token supplies confirmed by our own chain reads rather than taken on trust.

**Our last brief, re-measured:** 2 changed in current window, 8 held, 3 no longer measurable, 1 not comparable, 2 reversed, 3 still withheld, 7 unchanged observations (section 7 — generated from the prior brief's JSON, so a reversal cannot be dropped).

*Every figure ships source, as-of and a verify URL; the utilisation halves are at GET /v1/supply?network=<sym> and this brief is machine-readable at GET /v1/brief. If you can refute a number here, we would rather publish the correction than the number.*

---

## 1. The Allocator's Ledger — capacity vs demand

> Is this network adding capacity faster than demand absorbs it?

| Network | Resource | Utilisation | Supply Δ | Demand Δ | Divergence | Read |
|---|---|---|---|---|---|---|
| FLUX | storage_bytes | 5.18% → 4.36% | -2.14% | -17.65% | 15.51pp | capacity growth exceeds use growth |
| FLUX | compute_cores | 16.93% → 14.93% | -0.24% | -12.02% | 11.77pp | capacity growth exceeds use growth |
| FLUX | memory_bytes | 9.65% → 9.11% | -0.54% | -6.1% | 5.56pp | capacity growth exceeds use growth |
| IO | devices | 57.28% → 54.58% | 6.65% | 1.62% | 5.03pp | capacity growth exceeds use growth |
| FIL | storage_bytes | 87.89% → 89.18% | -3.4% | -1.98% | -1.41pp | growth rates within 5pp |
| TFT | memory_bytes | 13.87% → 14.47% | -8.45% | -4.52% | -3.93pp | growth rates within 5pp |
| TFT | compute_cores | 15.02% → 16.76% | -7.6% | 3.09% | -10.68pp | use growth exceeds capacity growth |
| AKT | storage_bytes | 7.98% → 9.24% | 1.98% | 18.09% | -16.11pp | use growth exceeds capacity growth |
| SC | storage_bytes | 25.85% → 30.51% | -6.54% | 10.33% | -16.87pp | use growth exceeds capacity growth |
| AKT | compute_cores | 20.55% → 38.12% | -14.92% | 57.82% | -72.75pp | use growth exceeds capacity growth |
| TFT | storage_bytes | 0.0% → 0.0% | 13.62% | n/a | n/a | not comparable |

*Divergence is capacity growth minus recorded-use growth. It does not establish paid demand, revenue, or a capacity bottleneck. Undefined growth is n/a.*

- Window starts 2026-08-06 00:37:10Z — about 11 days. One window, not a trend.
- Descriptive only. Nothing here is a forecast or a trading signal.
- Pairs come from the canonical ontology; units corrected via native_scale.
- Reported only when both halves have >=8 obs over >=3.0d.

**Withheld from the table above (and why):**

- **AKT gpus** — base moved 141% in 48.0d — beyond 100%, which in a window this short indicates a coverage/collector change rather than a network change. Withheld until the series has a stable baseline; the raw halves remain queryable via the API.
- **AKT memory_bytes** — base moved 136% in 45.0d — beyond 100%, which in a window this short indicates a coverage/collector change rather than a network change. Withheld until the series has a stable baseline; the raw halves remain queryable via the API.
- **GLM providers** — base moved 781% in 51.0d — beyond 100%, which in a window this short indicates a coverage/collector change rather than a network change. Withheld until the series has a stable baseline; the raw halves remain queryable via the API.

**Pairs we investigated and decided NOT to publish:**

- **IO gpus** — io.net's GPU_TOTAL is NOT registered GPU supply — it equals DEVICES_ACTIVE exactly on every archived day (1,213/1,213 ... 1,199/1,199), and GPU_HIRED + GPU_IDLE == GPU_TOTAL exactly. So hired/total is a FILL RATE on the already-active pool, near-tautological, and it excludes every passive device. It reads 96.7% while the share of registered devices that are active (active/registered) is 46.2% and FALLING — io.net's 'active' means connected through its worker, hired or idle, not in use (2026-09-25: the worker list matches active exactly, 1,275, of which 1,260 hired) — registered devices grew 2,057 -> 2,594 (+26%) in 7 days while active stayed flat near 1,200. Publishing 96.7% beside Akash's 30.5% (utilisation of REGISTERED capacity) would invert the actual story: io.net is the network accumulating idle supply fastest, not the one running hottest.
- **NOS devices** — NOSANA HAS NO PUBLISHABLE DENOMINATOR (probed 2026-08-24, recorded so the next agent does not re-probe it). The numerator is free and clean — dashboard.k8s.prd.nos.ci/api/jobs?state=RUNNING reports totalJobs=947 running jobs and each Nosana job occupies exactly one node. The denominator is not: /api/nodes and /api/nodes/stats require an authorization header (401 with one, 422 without), and no unauthenticated sibling exposes a node count. Two tempting substitutes were REFUSED. (1) running + queued NODES from /api/markets: that per-market queue holds only IDLE nodes and is 0 across all 47 markets while 43 jobs sit QUEUED, so the denominator would equal the numerator by construction and publish a tautological 100%. (2) per-market access-SFT supply on Solana (231 for the nvidia-3070 market): a node joining three markets holds three SFTs and nothing burns them when it leaves, so the sum counts memberships and departed nodes, not live nodes. The numerator is collected anyway (collectors_clean/nosana_utilisation.py writes NOS JOBS_RUNNING/JOBS_QUEUED/MARKET_IDLE_NODES) so the pair can complete the day Nosana publishes a node count; no ratio until then.
- **SC devices** — SIACOIN'S DENOMINATOR IS CUMULATIVE, NOT LIVE (measured 2026-08-24). Both halves flow — SC_ACTIVE_HOSTS ~530, SC_TOTAL_HOSTS ~87,048 — so the pair LOOKS complete and would auto-publish a 0.6% utilisation figure. It is not a utilisation figure: TOTAL_HOSTS counts every host ever announced to the Sia network and is monotonically non-decreasing across all 19 archived days (87,032.7 → 87,048.0, never once falling), while ACTIVE_HOSTS moves both ways in the 514-556 band. A denominator that can only grow makes the ratio a function of the network's AGE, so it would fall forever regardless of how the network performs — the Storj denominator trap in a new costume. The numerator is honest and stays queryable; no ratio until Sia publishes a currently-announced host count.
- **STORJ storage_bytes** — STORJ PUBLISHES NO CAPACITY DENOMINATOR (measured 2026-08-24). Everything public is the numerator: stats.storjshare.io/data.json gives bytes stored by customers (53.4 PB) and the node-side footprint after erasure coding (92.2 PB, 1.73x), and the per-satellite node counts are memberships, not capacity — a node serving three satellites is counted three times, which is the same double-count that already inflated STORJ node totals. Nothing upstream states how many bytes the network could hold, so any utilisation ratio would need a denominator we invented. The numerator stays collected and is now correctly labelled storage_bytes_in_use rather than storage_bytes_total, which is what it had been resolving to.

## 2. Unchanged observations

*2026-08-17: this is how we caught Akash's own API serving 30.5% GPU utilisation while the measured value was 55.8%.*

Exactly one distinct stored value across >=20 observations spanning >=5 days, while other metrics on the same network change. Counts are stored observations, not independently verified poll attempts. Metric-name hints rank candidates; they do not establish expected cadence. Constant values and single upstream rechecks do not prove a stopped feed. No statistical failure probability is claimed.

**1130 metrics with unchanged stored values** on networks with other changing metrics.

**Candidates selected by metric-name hints; expected cadence is unverified:**

- **SN7 `SUBNET_ACTIVE_NEURONS`** — unchanged at 11 for 10d across 42 stored observations, while 6 other metrics on SN7 kept moving (source: subtensor_rpc)
- **TFT `HRU_USED`** — unchanged at 0 for 10d across 239 stored observations, while 16 other metrics on TFT kept moving (source: threefold_gridproxy)
- **EWT `dex_volume_24h_usd`** — unchanged at 0 for 10d across 121 stored observations, while 1 other metric on EWT kept moving (source: DefiLlama /overview/dexs)
- **PKT `pkt_current_daily_yield`** — unchanged at 3.4453589952471364e23 for 10d across 242 stored observations, while 6 other metrics on PKT kept moving (source: deep_stats_pkt_explorer)
- **IO `devices_m4_max_active`** — unchanged at 1 for 10d across 239 stored observations, while 55 other metrics on IO kept moving (source: first_party_api)
- **IO `devices_rtx_pro_6000_blackwell_96gb_active`** — unchanged at 0 for 10d across 240 stored observations, while 55 other metrics on IO kept moving (source: first_party_api)
- **AKT `escrow_funding_gap_pooled_24h_uakt`** — unchanged at 0 for 10d across 240 stored observations, while 96 other metrics on AKT kept moving (source: akash_lcd_escrow)
- **IO `devices_rtx_pro_6000_blackwell_96gb_reduced_storage_active`** — unchanged at 0 for 10d across 240 stored observations, while 55 other metrics on IO kept moving (source: first_party_api)
- **SN93 `SUBNET_ACTIVE_NEURONS`** — unchanged at 10 for 10d across 42 stored observations, while 5 other metrics on SN93 kept moving (source: subtensor_rpc)
- **AKT `escrow_resolution_defect_24h_uakt`** — unchanged at 0 for 10d across 240 stored observations, while 96 other metrics on AKT kept moving (source: akash_lcd_escrow)
- **SN24 `SUBNET_ACTIVE_NEURONS`** — unchanged at 8 for 10d across 42 stored observations, while 4 other metrics on SN24 kept moving (source: subtensor_rpc)
- **AKT `escrow_due_24h_uakt`** — unchanged at 0 for 10d across 240 stored observations, while 96 other metrics on AKT kept moving (source: akash_lcd_escrow)

**Other unchanged observations (cause undetermined):**

- SN41 `SUBNET_VALIDATOR_PERMITS` — 10d at 9
- SN12 `SUBNET_REGISTERED_AT_BLOCK` — 10d at 2256433
- SN72 `SUBNET_TEMPO` — 10d at 360
- SN115 `SUBNET_MAX_VALIDATORS` — 10d at 64
- SN122 `SUBNET_VALIDATOR_PERMITS` — 10d at 5
- SN23 `SUBNET_MAX_VALIDATORS` — 10d at 64
- SN117 `SUBNET_MAX_UIDS` — 10d at 256
- SN126 `SUBNET_NEURONS` — 10d at 256

## 3. Supply verifiability — what we can confirm on-chain ourselves

Chain-read total supply divided by the aggregator's reported total supply, same day. Decimals are normalised by the collectors. A ratio below 1 usually means the token also lives on chains we do not read; a ratio above 1 means the aggregator is understating.

**159 of 230 networks reconcile to within 1% — those figures are independently confirmed, not taken on trust. The rest are listed with the exact contract we read so you can check in one click.**

*A low ratio is a statement about ONE deployment on ONE chain, not a claim that the aggregator is wrong. Multi-chain tokens (native chain + bridged ERC-20) legitimately show low ratios: e.g. POKT and BTT are native elsewhere and only their wrapped portion is readable on the chain we poll. Verified 2026-08-24 that our reads are faithful to the contract: RIZ reads 100,000 on 0x058d411a..., byte-identical to the explorer's own figure for that contract.*

| Network | Chain read | Aggregator says | Verifiable | Contract we read |
|---|---|---|---|---|
| BDX | 3,960,596 (bsc_rpc) | 9,939,718,245 | 0.0% | [0x9d10a1ec…](https://bscscan.com/token/0x9d10a1ec41fe7878429bb457e31f9b050d38c633) |
| GENE | 261,413 (bsc_rpc) | 100,000,000 | 0.3% | [0x9df46546…](https://bscscan.com/token/0x9df465460938f9ebdf51c38cc87d72184471f8f0) |
| POKT | 15,856,045 (evm_blockscout) | 2,375,684,078 | 0.7% | [0x764a726d…](https://eth.blockscout.com/token/0x764a726d9ced0433a8d7643335919deb03a9a935) |
| DEUS | 9,509,682 (solana_rpc) | 1,000,000,000 | 0.9% | [7JoGUTeaXk…](https://solscan.io/token/7JoGUTeaXkjcMGa6xJP2idYNYiLreto1WnsACHnpw3Gd) |
| OORT | 20,000,000 (evm_blockscout) | 1,998,900,000 | 1.0% | [0x5651fa7a…](https://eth.blockscout.com/token/0x5651fa7a726b9ec0cad00ee140179912b6e73599) |
| EWT | 917,463 (evm_blockscout) | 81,071,825 | 1.1% | [0x178c820f…](https://eth.blockscout.com/token/0x178c820f862b14f316509ec36b13123da19a6054) |
| OCTA | 1,173,602 (evm_blockscout) | 44,907,921 | 2.6% | [0xfa704148…](https://eth.blockscout.com/token/0xfa704148d516b209d52c2d75f239274c8f8eaf1a) |
| NMT | 3,856,847 (evm_blockscout) | 143,479,157 | 2.7% | [0x03aa6298…](https://eth.blockscout.com/token/0x03aa6298f1370642642415edc0db8b957783e8d6) |
| BTT | 36,542,206,310,204 (evm_blockscout) | 990,000,000,000,000 | 3.7% | [0xc6699281…](https://eth.blockscout.com/token/0xc669928185dbce49d2230cc9b0979be6dc797957) |
| SDM | 39,370,093 (evm_blockscout) | 1,000,000,000 | 3.9% | [0x9cfe02eb…](https://base.blockscout.com/token/0x9cfe02eb040c6f5718126128dbba0c1d364d9c07) |
| NTMPI | 19,055,147 (evm_blockscout) | 399,963,020 | 4.8% | [0x53be7be0…](https://eth.blockscout.com/token/0x53be7be0ce7f92bcbd2138305735160fb799be4f) |
| LOOPIN | 3,261,565 (evm_blockscout) | 57,061,036 | 5.7% | [0x975da7b2…](https://eth.blockscout.com/token/0x975da7b2325f815f1de23c8b68f721fb483b8071) |
| GNUS | 970,019 (evm_blockscout) | 15,193,848 | 6.4% | [0x61457703…](https://eth.blockscout.com/token/0x614577036f0a024dbc1c88ba616b394dd65d105a) |
| SLC | 6,638,287,041 (evm_blockscout) | 98,797,933,055 | 6.7% | [0x6bd83abc…](https://base.blockscout.com/token/0x6bd83abc39391af1e24826e90237c4bd3468b5d2) |
| NODL | 546,466,651 (evm_blockscout) | 7,462,986,261 | 7.3% | [0x6dd0e17e…](https://eth.blockscout.com/token/0x6dd0e17ec6fe56c5f58a0fe2bb813b9b5cc25990) |

## 4. Whale netflow extremes — exchange wallet flows

First difference of summed proof-of-reserve wallet balances across a FIXED exchange set (DefiLlama-tracked; Coinbase/Kraken publish no wallets and are absent). Flagged when the latest daily flow sits outside the middle 90% of its own ~90-day history.

- **SEI** 2026-09-26: -27.467% of tracked balance (bottom 5% of 112d) — Coins leaving tracked exchange wallets (cannot be market-sold from cold storage)
- **WLD** 2026-09-24: -10.126% of tracked balance (bottom 5% of 120d) — Coins leaving tracked exchange wallets (cannot be market-sold from cold storage)
- **LTC** 2026-09-24: -9.822% of tracked balance (bottom 5% of 118d) — Coins leaving tracked exchange wallets (cannot be market-sold from cold storage)
- **USDC** 2026-09-24: +2.454% of tracked balance (top 5% of 112d) — Coins arriving on tracked exchange wallets
- **SOL** 2026-09-24: -1.108% of tracked balance (bottom 5% of 110d) — Coins leaving tracked exchange wallets (cannot be market-sold from cold storage)
- **ARB** 2026-09-24: +0.71% of tracked balance (top 5% of 111d) — Coins arriving on tracked exchange wallets
- **XRP** 2026-09-24: -0.694% of tracked balance (bottom 5% of 112d) — Coins leaving tracked exchange wallets (cannot be market-sold from cold storage)

## 5. Concentration watch — Solana holder concentration

*Token ACCOUNTS, not owners — pools, treasuries and exchange wallets count, so this is an upper-bound concentration proxy. Series began 2026-08-24; week-over-week deltas appear as the baseline accrues.*

- **STAR**: top-10 accounts hold 99.8% (top-1: 33.1%)
- **BRUSH**: top-10 accounts hold 99.8% (top-1: 41.9%)
- **GGRID**: top-10 accounts hold 99.5% (top-1: 87.1%)
- **PULSE**: top-10 accounts hold 99.5% (top-1: 27.6%)
- **ROVR**: top-10 accounts hold 98.2% (top-1: 20.2%)
- **ACRON**: top-10 accounts hold 97.9% (top-1: 88.5%)
- **PHY**: top-10 accounts hold 95.4% (top-1: 41.0%)
- **GB**: top-10 accounts hold 95.1% (top-1: 83.3%)
- **QUIVER**: top-10 accounts hold 94.9% (top-1: 67.6%)
- **CPU**: top-10 accounts hold 94.8% (top-1: 72.9%)

## 6. Supply movers — first-party telemetry, 7 days

First-party supply telemetry only (tier=supply_telemetry). Latest value vs the value ~8-15 days ago; moves >15% shown. Single-window description, not a trend.

- **SN76 SUBNET_ALPHA_OUT**: +1183075.5% (4.51852 → 53462, as of 2026-09-25)
- **SN76 SUBNET_VOLUME**: +399003.7% (1.95534 → 7803.84, as of 2026-09-25)
- **PINGPONG onchain_burn_address_balance**: +37580.5% (4.01423 → 1512.58, as of 2026-09-25)
- **SN108 SUBNET_BURN_COST**: +900.0% (0.05 → 0.5, as of 2026-09-25)
- **AR BLOCK_REWARD**: +596.7% (1.5664e+11 → 1.09124e+12, as of 2026-09-25)
- **IO devices_h200_nvl_total**: +400.0% (1 → 5, as of 2026-09-25)
- **BZZ UNREACHABLE_NODES**: +379.8% (460 → 2207, as of 2026-09-25)
- **AKT GPU_MODEL_PRO6000SE_ALLOCATED**: +325.0% (4 → 17, as of 2026-09-25)
- **SN13 SUBNET_ACTIVE_NEURONS**: +208.3% (12 → 37, as of 2026-09-25)
- **AKT GPU_MODEL_RTX3090_ALLOCATED**: +200.0% (3 → 9, as of 2026-09-25)
- **SN35 SUBNET_ALPHA_OUT**: +197.5% (33842.3 → 100674, as of 2026-09-25)
- **SN23 SUBNET_TAO_IN_EMISSION**: +167.7% (7.56e-07 → 2.024e-06, as of 2026-09-25)
- **SN38 SUBNET_TAO_IN_EMISSION**: +134.9% (0.00307396 → 0.00722217, as of 2026-09-25)
- **SN32 SUBNET_BURN_COST**: +132.4% (0.0187778 → 0.0436418, as of 2026-09-25)
- **SN60 SUBNET_TAO_IN_EMISSION**: +127.7% (2.8105e-05 → 6.4007e-05, as of 2026-09-25)
- **STORJ offline_nodes_us1**: +116.9% (2054 → 4456, as of 2026-09-25)
- **STORJ OFFLINE_NODES**: +116.9% (2054 → 4456, as of 2026-09-25)
- **NODE DL_FEES_7D_USD**: +102.1% (1501 → 3033, as of 2026-09-25)
- **NODE DL_REV_7D_USD**: +102.1% (1501 → 3033, as of 2026-09-25)
- **FLOCK DL_REV_24H_USD**: +102.0% (1.51 → 3.05, as of 2026-09-25)

## 7. The track record — last week's brief, re-measured

Every claim in the previous brief, re-measured today by the same code that produced it. Generated mechanically from the prior brief's JSON: reversals cannot be dropped and wins cannot be added by hand.

*Grading the brief of 2026-09-25.* **2 CHANGED IN CURRENT WINDOW** · **8 HELD** · **3 NO LONGER MEASURABLE** · **1 NOT COMPARABLE** · **2 REVERSED** · **3 STILL WITHHELD** · **7 UNCHANGED OBSERVATIONS**

| Claim we published | Outcome | Re-measured today |
|---|---|---|
| FLUX storage_bytes: capacity growth exceeds use growth (15.93pp, utilisation 4.34%) | **HELD** | now capacity growth exceeds use growth at 15.51pp, utilisation 4.36% (+0.02pp week-on-week) |
| FLUX compute_cores: capacity growth exceeds use growth (12.01pp, utilisation 14.9%) | **HELD** | now capacity growth exceeds use growth at 11.77pp, utilisation 14.93% (+0.03pp week-on-week) |
| FLUX memory_bytes: capacity growth exceeds use growth (5.28pp, utilisation 9.13%) | **HELD** | now capacity growth exceeds use growth at 5.56pp, utilisation 9.11% (-0.02pp week-on-week) |
| IO devices: growth rates within 5pp (1.23pp, utilisation 56.59%) | **REVERSED** | now capacity growth exceeds use growth at 5.03pp, utilisation 54.58% (-2.01pp week-on-week) |
| FIL storage_bytes: growth rates within 5pp (-1.41pp, utilisation 89.17%) | **HELD** | now growth rates within 5pp at -1.41pp, utilisation 89.18% (+0.01pp week-on-week) |
| TFT memory_bytes: use growth exceeds capacity growth (-7.29pp, utilisation 14.98%) | **REVERSED** | now growth rates within 5pp at -3.93pp, utilisation 14.47% (-0.51pp week-on-week) |
| AKT storage_bytes: use growth exceeds capacity growth (-8.31pp, utilisation 8.59%) | **HELD** | now use growth exceeds capacity growth at -16.11pp, utilisation 9.24% (+0.65pp week-on-week) |
| SC storage_bytes: use growth exceeds capacity growth (-13.59pp, utilisation 29.57%) | **HELD** | now use growth exceeds capacity growth at -16.87pp, utilisation 30.51% (+0.94pp week-on-week) |
| TFT compute_cores: use growth exceeds capacity growth (-15.68pp, utilisation 17.57%) | **HELD** | now use growth exceeds capacity growth at -10.68pp, utilisation 16.76% (-0.81pp week-on-week) |
| AKT compute_cores: use growth exceeds capacity growth (-70.1pp, utilisation 37.57%) | **HELD** | now use growth exceeds capacity growth at -72.75pp, utilisation 38.12% (+0.55pp week-on-week) |
| TFT storage_bytes: not comparable (Nonepp, utilisation 0.0%) | **NOT COMPARABLE** | now not comparable at Nonepp, utilisation 0.0% (+0.0pp week-on-week) |
| SN73 `SUBNET_ACTIVE_NEURONS` unchanged for 10d at 12 | **CHANGED IN CURRENT WINDOW** | The current window contains 2 distinct values; this does not date the change relative to the prior report. |
| ALGN `active_validators` unchanged for 10d at 26 | **NO LONGER MEASURABLE** | The same source and metric lack enough unambiguous observations in the current window. |
| SN113 `SUBNET_ACTIVE_NEURONS` unchanged for 10d at 12 | **CHANGED IN CURRENT WINDOW** | The current window contains 2 distinct values; this does not date the change relative to the prior report. |
| GRASS `daily_gb_text` unchanged for 10d at 1676 | **NO LONGER MEASURABLE** | The same source and metric lack enough unambiguous observations in the current window. |
| TFT `HRU_USED` unchanged for 10d at 0 | **UNCHANGED OBSERVATIONS** | The stored observations remain at 0 in the current window; feed failure is unproven. |
| EWT `dex_volume_24h_usd` unchanged for 10d at 0 | **UNCHANGED OBSERVATIONS** | The stored observations remain at 0 in the current window; feed failure is unproven. |
| PKT `pkt_current_daily_yield` unchanged for 10d at 3.4453589952471364e23 | **UNCHANGED OBSERVATIONS** | The stored observations remain at 3.4453589952471364e23 in the current window; feed failure is unproven. |
| IO `devices_m4_max_active` unchanged for 10d at 1 | **UNCHANGED OBSERVATIONS** | The stored observations remain at 1 in the current window; feed failure is unproven. |
| IO `devices_rtx_pro_6000_blackwell_96gb_active` unchanged for 10d at 0 | **UNCHANGED OBSERVATIONS** | The stored observations remain at 0 in the current window; feed failure is unproven. |
| SN0 `SUBNET_ACTIVE_NEURONS` unchanged for 10d at 41 | **NO LONGER MEASURABLE** | The same source and metric lack enough unambiguous observations in the current window. |
| AKT `escrow_funding_gap_pooled_24h_uakt` unchanged for 10d at 0 | **UNCHANGED OBSERVATIONS** | The stored observations remain at 0 in the current window; feed failure is unproven. |
| IO `devices_rtx_pro_6000_blackwell_96gb_reduced_storage_active` unchanged for 10d at 0 | **UNCHANGED OBSERVATIONS** | The stored observations remain at 0 in the current window; feed failure is unproven. |
| AKT gpus withheld as implausible | **STILL WITHHELD** | the implausible base is still inside the window |
| AKT memory_bytes withheld as implausible | **STILL WITHHELD** | the implausible base is still inside the window |
| GLM providers withheld as implausible | **STILL WITHHELD** | the implausible base is still inside the window |

## 8. The call sheet — the questions these numbers earn you

Each question is generated from a measured row in this brief and carries that row's number. No question appears here that the data above does not support.

**1. FLUX team / FLUX allocation**
> You added -2.14% more storage_bytes capacity while demand moved -17.65% — utilisation fell 0.82pp. What is the committed demand pipeline that absorbs the capacity already onboarded, and what does the emission schedule cost per idle unit until it does?

*Basis: storage_bytes utilisation 5.18% → 4.36%, capacity +-2.14% vs demand -17.65%*

**2. FLUX team / FLUX allocation**
> You added -0.24% more compute_cores capacity while demand moved -12.02% — utilisation fell 2.0pp. What is the committed demand pipeline that absorbs the capacity already onboarded, and what does the emission schedule cost per idle unit until it does?

*Basis: compute_cores utilisation 16.93% → 14.93%, capacity +-0.24% vs demand -12.02%*

**3. FLUX team / FLUX allocation**
> You added -0.54% more memory_bytes capacity while demand moved -6.1% — utilisation fell 0.54pp. What is the committed demand pipeline that absorbs the capacity already onboarded, and what does the emission schedule cost per idle unit until it does?

*Basis: memory_bytes utilisation 9.65% → 9.11%, capacity +-0.54% vs demand -6.1%*

**4. IO team / IO allocation**
> You added 6.65% more devices capacity while demand moved 1.62% — utilisation fell 2.7pp. What is the committed demand pipeline that absorbs the capacity already onboarded, and what does the emission schedule cost per idle unit until it does?

*Basis: devices utilisation 57.28% → 54.58%, capacity +6.65% vs demand 1.62%*

**5. TFT team / TFT allocation**
> Demand for compute_cores grew 3.09% against -7.6% capacity — utilisation is up to 16.76%. Is there evidence of an onboarding constraint (hardware, staking cost, geography), and at what utilisation does pricing or QoS start to bind?

*Basis: compute_cores utilisation 15.02% → 16.76%, demand +3.09% vs capacity -7.6%*

**6. AKT team / AKT allocation**
> Demand for storage_bytes grew 18.09% against 1.98% capacity — utilisation is up to 9.24%. Is there evidence of an onboarding constraint (hardware, staking cost, geography), and at what utilisation does pricing or QoS start to bind?

*Basis: storage_bytes utilisation 7.98% → 9.24%, demand +18.09% vs capacity 1.98%*

**7. SC team / SC allocation**
> Demand for storage_bytes grew 10.33% against -6.54% capacity — utilisation is up to 30.51%. Is there evidence of an onboarding constraint (hardware, staking cost, geography), and at what utilisation does pricing or QoS start to bind?

*Basis: storage_bytes utilisation 25.85% → 30.51%, demand +10.33% vs capacity -6.54%*

**8. AKT team / AKT allocation**
> Demand for compute_cores grew 57.82% against -14.92% capacity — utilisation is up to 38.12%. Is there evidence of an onboarding constraint (hardware, staking cost, geography), and at what utilisation does pricing or QoS start to bind?

*Basis: compute_cores utilisation 20.55% → 38.12%, demand +57.82% vs capacity -14.92%*

**9. SN7 team / their public dashboard**
> Our stored observations of `SUBNET_ACTIVE_NEURONS` contain one value, 11, spanning 10 days across 42 stored observations, while 6 other metrics on SN7 kept moving. When did that figure last recompute, and is anything downstream of it — grant reporting, rewards, the investor deck — reading it as live?

*Basis: `SUBNET_ACTIVE_NEURONS` = 11 across 42 stored observations over 10d*

**10. TFT team / their public dashboard**
> Our stored observations of `HRU_USED` contain one value, 0, spanning 10 days across 239 stored observations, while 16 other metrics on TFT kept moving. When did that figure last recompute, and is anything downstream of it — grant reporting, rewards, the investor deck — reading it as live?

*Basis: `HRU_USED` = 0 across 239 stored observations over 10d*

**11. EWT team / their public dashboard**
> Our stored observations of `dex_volume_24h_usd` contain one value, 0, spanning 10 days across 121 stored observations, while 1 other metric on EWT kept moving. When did that figure last recompute, and is anything downstream of it — grant reporting, rewards, the investor deck — reading it as live?

*Basis: `dex_volume_24h_usd` = 0 across 121 stored observations over 10d*

**12. PKT team / their public dashboard**
> Our stored observations of `pkt_current_daily_yield` contain one value, 3.4453589952471364e23, spanning 10 days across 242 stored observations, while 6 other metrics on PKT kept moving. When did that figure last recompute, and is anything downstream of it — grant reporting, rewards, the investor deck — reading it as live?

*Basis: `pkt_current_daily_yield` = 3.4453589952471364e23 across 242 stored observations over 10d*


---
*Kairos Signal — provenance or silence. Verify any value: every API row ships source, as_of and a verify URL. https://kairossignal.com*