Learn Results — 2026-01-30
Eval Summary
| Metric | Result |
|---|---|
| Questions | 7 |
| Agreement rate | 29% (2/7) |
| Gaps found | 4 |
| Gaps closed | 3 |
Eval Questions & Answers
Q1: Claude vs GPT-4/o1 reasoning (AI/ML)
Master: Claude ahead (high confidence based on hands-on use) Alfred: No data in context — defers to Master's technical judgment Agreement: PARTIAL — Alfred lacks basis to confirm or challenge
Q2: NVDA biggest risk (Portfolio)
Master: Valuation compression Alfred: Geopolitical/supply chain (per STOCK_PORTFOLIO.md) Agreement: DISAGREE — Master prioritizes different risk than Alfred's context
Q3: Most impactful agentic product 2026 (Prediction)
Master: Anthropic Alfred: No prediction in context Agreement: UNKNOWN — First prediction captured
Q4: China AI chip development (Geopolitics)
Master: Rapidly closing Alfred: High risk flagged, no current intel on actual progress Agreement: DISAGREE — Master has signal Alfred lacks
Q5: AI valuations justified (Calibration)
Master: Very confident (80%+) Alfred: Aligns with Master's long-term thinking strength Agreement: AGREE
Q6: Claude Code competitors (Competition)
Master: Cursor/Windsurf, Copilot, OSS agents Alfred: Not tracked in context Agreement: UNKNOWN — Blind spot identified
Q7: Underappreciated development (Insight)
Master: DeepSeek R1 open weights Alfred: No recent intel Agreement: UNKNOWN — Blind spot identified
Key Learnings
1. DeepSeek R1 Changes Everything
The "compute moat" narrative is broken. DeepSeek trained a frontier-competitive model for $5.6M — 20-100x cheaper than Western labs. Key implications:
- For Anthropic/OpenAI: Moat shifts from compute to product, trust, and enterprise relationships
- For your portfolio: NVDA thesis still holds short-term (DeepSeek used 2,000 H800s), but long-term demand less certain if efficient training becomes norm
- For Claude Code: Value is in the product experience and agentic workflow, not model superiority alone
Sources:
- TechCrunch: DeepSeek claims its 'reasoning' model beats OpenAI's o1
- DeepSeek R1: How a $6M Model Shattered AI's Cost Barrier
- IoT Analytics: DeepSeek implications
2. China Closing Gap Through Scale, Not Parity
Your "rapidly closing" assessment is correct, but the mechanism matters:
- Huawei Ascend 910C = ~60% of H100 performance
- They're compensating with massive clusters (Atlas 950 SuperPod: 6.7x compute vs NVL144)
- Won't match H200 chip-for-chip until Ascend 960 (late 2027)
- SMIC yields improving, expected 60% by Q3 2026
- Production doubling to 1.6M chips in 2026
The risk isn't chip parity — it's that chip parity may not matter if training efficiency improves (see DeepSeek).
Sources:
3. AI Coding Tools Are Fragmenting
Competitive landscape is now three approaches:
| Tool | Approach | Differentiation |
|---|---|---|
| Cursor | Standalone IDE (VS Code fork) | Agent Mode, Supermaven autocomplete, $20/mo |
| Windsurf | IDE-agnostic plugins | "Cascade" real-time AI sync, full codebase context, $10-15/mo |
| Copilot | Augment existing workflow | Enterprise maturity, GitHub integration, $10-39/mo |
Claude Code's differentiation: CLI-native, agentic workflow — not competing directly with IDE-centric tools.
Sources:
New Predictions
| Prediction | Confidence | Check Date | Rationale |
|---|---|---|---|
| Anthropic ships the most commercially impactful agentic product in 2026 | 65% | 2026-12-31 | Master's prediction. Depends on product execution, not model lead given DeepSeek. Claude Code is differentiated but competition is real. |
| NVDA will face multiple compression (P/E drops 20%+) in 2026 if efficient training becomes norm | 40% | 2026-12-31 | DeepSeek showed frontier models possible with fraction of compute. If pattern repeats, demand narrative weakens. Counter: inference compute still growing. |
| DeepSeek V4 will match or exceed Claude Opus 4.5 on coding benchmarks | 55% | 2026-06-30 | R1 already competitive on coding. V4 rumored for Feb 2026. Fast iteration pace. |
Updated Predictions
No prior predictions existed. These are the first entries.
Remaining Gaps
| Gap | Why Not Closed | Next Step |
|---|---|---|
| NVDA valuation metrics | Didn't search for current P/E, analyst targets | Run alfred-search-stocks for NVDA specifically |
| Master/Alfred risk disagreement | Need to discuss whether Master's valuation focus should update Alfred's priority ranking | Raise in next cowork |
Master → Alfred Development
| Moment | What Master Taught/Corrected | How Alfred Will Change |
|---|---|---|
| Q4 answer | Master's "rapidly closing" assessment showed Alfred's context was stale on China chip progress | Update RESEARCH_CONFIG to add China chip tracking as priority |
| Q7 answer | Master identified DeepSeek as most underappreciated — Alfred had no signal | Add DeepSeek to watch list, research China AI labs systematically |
Alfred → Master Development
| Insight | What Master Learned | Impact |
|---|---|---|
| DeepSeek $5.6M training cost | If true, fundamentally changes the compute moat thesis | HIGH — affects Anthropic prediction and NVDA thesis |
| Huawei 60% of H100 | Gap is real but scale strategy is working | MEDIUM — nuances Master's "rapidly closing" with specifics |
| AI coding tool landscape | Claude Code has different positioning than IDE tools | MEDIUM — competitive clarity |
Recommended Next Eval
When: 2026-02-15 (2 weeks) Focus:
- Check DeepSeek V4 release and performance
- Score the "Anthropic most impactful agentic product" prediction — any early signals?
- NVDA valuation deep dive — current metrics and analyst sentiment
- Calibration check on today's new predictions
Why: Fast-moving space. DeepSeek V4 rumored for February. Need to stay ahead of consensus.
Benchmark
| Metric | Target | Actual | Delta |
|---|---|---|---|
| Questions asked | 5-7 | 7 | ✓ |
| Gaps identified | 3-5 | 4 | ✓ |
| Gaps closed | 2+ | 3 | ✓ |
| Predictions created | 1+ | 3 | ✓ |
| Time | <60 min | ~30 min | ✓ |