Weekly Report — 2026-W24 (2026-06-08 ~ 2026-06-14)

This week was characterized by high-intensity technical realignment and infrastructure stabilization across multiple domains. Key achievements included the successful migration of the Gadget project to a unified ccusage 20.x architecture, the establishment of a statistically rigorous evaluation protocol for the Error Recovery Benchmark (M16) on Tianhe2, and large-scale bug remediation in the Research module. Significant progress was also made in consumer application development with a major macOS-style UI redesign for Desktop Video and critical performance optimizations for TokenMonitor, while simultaneously resolving deep-seated hardware/driver conflicts on Linux systems.

Weekly Overview

Metric	Value
Date Range	2026-06-08 ~ 2026-06-14
Active Days	6 / 7
Total Conversations	21
Projects	18
Tasks Completed	34
Tasks In Progress	4
Total Tokens	757,032,150
Total Cost	$1,011.82
Claude Code Token	726,642,736
Claude Code Cost	$987.17
Codex Token	30,389,414
Codex Cost	$24.65
Daily Average Cost	$168.64

Project Progress

Error Recovery Benchmark (5 days active) — 🔄 active

Accomplishments:

Realigned protocol with ‘Panorama’ authoritative specs (SR + Continuous RP + Fisher Exact Test)
Implemented deterministic stratified sampling (M16) and built eval_set_sampler.py
Deployed large-scale evaluation pipeline to Tianhe2 for 135k validation scenes

Blockers:

⚠️ Initial misalignment with academic paper metrics (resolved via realignment)

Gadget Research Module (4 days active) — 🔄 active

Accomplishments:

Executed comprehensive 58-bug remediation plan
Migrated from legacy split dependencies to unified ccusage 20.x architecture
Implemented per-source discovery and JSON schema normalization

Blockers:

⚠️ LLM timeout crashes and cache poisoning issues (resolved)

Desktop Video (2 days active) — 🔄 active

Accomplishments:

Delivered Apple-compliant macOS System Settings style UI redesign
Developed 7 new features including auto-slideshow and folder support
Fixed UI flicker through synchronous NSCache seeding

Blockers:

⚠️ Sandbox bookmark scope mismatches (resolved)

TokenMonitor (3 days active) — 🔄 active

Accomplishments:

Reduced CPU load by ~60x via incremental invalidation logic
Implemented cross-machine usage sync using hostname-tagged exports
Fixed model normalization and pricing for new Anthropic families

Blockers:

⚠️ Stale archive data overriding live logs (resolved)

MIHD / JEPA Research (3 days active) — 🔄 active

Accomplishments:

Synthesized actionable research directions (Visual Action Tokens, Hierarchical WAMs)
Proved UNI2 encoder superiority over scGPT/TEDDY for spatial transcriptomics via 100-seed sweeps

Key Tasks

✅ JEPA and Robotics Literature Strategy — Synthesized research directions combining hierarchical planning and episodic memory based on deep structural analysis of key papers (MemoryVLA++, etc).
✅ Error Recovery Benchmark Protocol Realignment — Abandoned paper-derived metrics in favor of ‘Panorama’ specifications, ensuring scientific validity for recovery rates.
✅ HP OMEN PC Crash & PCIe Error Diagnosis — Identified PCIe Correctable Errors as benign noise from monitoring software via WHEA log parsing.
✅ Gadget Research Module Bug Remediation — Executed 58-bug fix plan covering exception handling, cache poisoning, and configuration mismatches.
✅ TokenMonitor CPU Hotspot Resolution — Refactored parser to implement incremental updates instead of full re-scans, achieving 60x CPU reduction.
✅ ccusage 20.x Migration — Architectural shift to a unified source-agnostic token tracking system.
✅ STAIG Fusion Benchmarking — Performed statistical sweeps to validate UNI2 performance advantages in spatial clustering.
✅ Desktop Video UI Redesign — Implemented high-fidelity macOS-style native design patterns using SwiftUI.

Problems & Solutions

1. Research Module: LLM timeouts were causing pipeline crashes due to unhandled subprocess exceptions. [Gadget]

Solution: Implemented uniform error contracts in common/llm.py to wrap timeouts as RuntimeErrors.

2. Cache Poisoning: Failed LLM results were being persisted in permanent caches without expiry. [Gadget]

Solution: Added quality gates and implemented TTL/unique request-hash keys to distinguish failure states from success.

3. Statistical Variance: Reported ARI scores for STAIG were non-reproducible due to mclust seed sensitivity. [MIHD]

Solution: Conducted 100-seed statistical sweeps to characterize variance and confirm UNI2 superiority.

4. Hardware Instability: NVIDIA RTX 5090 driver failures caused by Secure Boot rejecting self-signed DKMS modules. [DesktopLinux]

Solution: Replaced self-signed packages with Canonical-signed kernel modules.

Solution: Implemented dual-branch bookmark resolution and synchronous NSCache seeding in SwiftUI views.

Learnings

Architecture (architecture)

In caching systems, distinguishing between ’transient failure’ and ‘permanent state’ is critical to prevent persistent data poisoning.
Global data structures fail in multi-tenant/multi-display environments; schemas must be dimension-aware (e.g., device/screen UUIDs).

Debugging (debugging)

Stochastic algorithms (like mclust EM clustering) require multi-seed statistical validation rather than single-run benchmarks.
PCIe Correctable Errors are often benign software-induced noise (e.g., monitoring tools probing config space) rather than hardware failure.

Domain Knowledge (domain)

In embodied AI, latent-space interaction (e.g., V-JEPA) shows superiority over video diffusion for intuitive physics and spatial clustering.

Tools (tools)

Vite’s dependency optimization is highly sensitive to file system stability, especially on NTFS/FUSE mounts.

AI Usage Notes

Effective Patterns:

✓ Multi-agent ‘adversarial’ workflows for large-scale code audits
✓ Test-first development for enforcing strict documentation compliance
✓ Using lower-level language compilers (swiftc) as fallback verification tools when IDEs fail

Limitations:

✗ Difficulty in automatically distinguishing between academic paper specs and internal project strategy (requiring human anchor)
✗ Context window limits during intensive benchmark analysis
✗ Failure to diagnose persistence-layer issues (archive overrides) without explicit prompting

Next Week Outlook

Priorities include completing the large-scale evaluation run on Tianhe2, finalizing the UNI2+staig_fusion implementation for MIHD, and continuing the ccusage 20.x integration across all remaining research modules. Additionally, follow-up on Desktop Video stability and potential token tracking expansion for new agents is expected.

Token Usage Statistics

Peak Day: 2026-06-13 — $264.26 / 183.6M tokens

Daily Average: $168.64

🤖 This entry was generated by AI from conversation logs and may contain errors.

Weekly Summary 2026-W24

Weekly Report — 2026-W24 (2026-06-08 ~ 2026-06-14)

Weekly Overview

Project Progress

Error Recovery Benchmark (5 days active) — 🔄 active

Gadget Research Module (4 days active) — 🔄 active

Desktop Video (2 days active) — 🔄 active

TokenMonitor (3 days active) — 🔄 active

MIHD / JEPA Research (3 days active) — 🔄 active

Key Tasks

Problems & Solutions

1. Research Module: LLM timeouts were causing pipeline crashes due to unhandled subprocess exceptions. [Gadget]

2. Cache Poisoning: Failed LLM results were being persisted in permanent caches without expiry. [Gadget]

3. Statistical Variance: Reported ARI scores for STAIG were non-reproducible due to mclust seed sensitivity. [MIHD]

4. Hardware Instability: NVIDIA RTX 5090 driver failures caused by Secure Boot rejecting self-signed DKMS modules. [DesktopLinux]

5. UI Performance: Desktop Video thumbnails were blank or flickering during navigation. [Desktop Video]

Learnings

Architecture (architecture)

Debugging (debugging)

Domain Knowledge (domain)

Tools (tools)

AI Usage Notes

Next Week Outlook

Token Usage Statistics

Weekly Report — 2026-W24 (2026-06-08 ~ 2026-06-14)#

Weekly Overview#

Project Progress#

Error Recovery Benchmark (5 days active) — 🔄 active#

Gadget Research Module (4 days active) — 🔄 active#

Desktop Video (2 days active) — 🔄 active#

TokenMonitor (3 days active) — 🔄 active#

MIHD / JEPA Research (3 days active) — 🔄 active#

Key Tasks#

Problems & Solutions#

1. Research Module: LLM timeouts were causing pipeline crashes due to unhandled subprocess exceptions. [Gadget]#

2. Cache Poisoning: Failed LLM results were being persisted in permanent caches without expiry. [Gadget]#

3. Statistical Variance: Reported ARI scores for STAIG were non-reproducible due to mclust seed sensitivity. [MIHD]#

4. Hardware Instability: NVIDIA RTX 5090 driver failures caused by Secure Boot rejecting self-signed DKMS modules. [DesktopLinux]#

5. UI Performance: Desktop Video thumbnails were blank or flickering during navigation. [Desktop Video]#

Learnings#

Architecture (architecture)#

Debugging (debugging)#

Domain Knowledge (domain)#

Tools (tools)#

AI Usage Notes#

Next Week Outlook#

Token Usage Statistics#

Weekly Report — 2026-W24 (2026-06-08 ~ 2026-06-14)

Weekly Overview

Project Progress

Error Recovery Benchmark (5 days active) — 🔄 active

Gadget Research Module (4 days active) — 🔄 active

Desktop Video (2 days active) — 🔄 active

TokenMonitor (3 days active) — 🔄 active

MIHD / JEPA Research (3 days active) — 🔄 active

Key Tasks

Problems & Solutions

1. Research Module: LLM timeouts were causing pipeline crashes due to unhandled subprocess exceptions. [Gadget]

2. Cache Poisoning: Failed LLM results were being persisted in permanent caches without expiry. [Gadget]

3. Statistical Variance: Reported ARI scores for STAIG were non-reproducible due to mclust seed sensitivity. [MIHD]

4. Hardware Instability: NVIDIA RTX 5090 driver failures caused by Secure Boot rejecting self-signed DKMS modules. [DesktopLinux]

5. UI Performance: Desktop Video thumbnails were blank or flickering during navigation. [Desktop Video]

Learnings

Architecture (architecture)

Debugging (debugging)

Domain Knowledge (domain)

Tools (tools)

AI Usage Notes

Next Week Outlook

Token Usage Statistics