Wiki source code of POC Summary (POC1 & POC2)

Last modified by Robert Schaub on 2026/02/08 08:23

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2.1	1	= POC Summary (POC1 & POC2) =
1.1	2
	3
2.1	4	{{info}}
	5	This page describes POC1 v0.4+ (3-stage pipeline with caching).
1.1	6
2.4	7	For complete implementation details, see [[POC1 API & Schemas Specification>>Archive.FactHarbor 2026\.01\.20.Specification.POC.API-and-Schemas.WebHome]].
2.1	8	{{/info}}
	9
	10
	11
	12	== 1. POC Specification ==
	13
	14	=== POC Goal
2.2	15	Prove that AI can extract claims and determine verdicts automatically without human intervention. ===
1.1	16
2.2	17	=== POC Output (4 Components Only) ===
1.1	18
2.4	19	* \\
	20	** \\
1.1	21	1. ANALYSIS SUMMARY
	22	- 3-5 sentences
	23	- How many claims found
2.1	24	- Distribution of verdicts
2.2	25	- Overall assessment**
1.1	26
	27	2. CLAIMS IDENTIFICATION
	28	- 3-5 numbered factual claims
	29	- Extracted automatically by AI
	30
	31	3. CLAIMS VERDICTS
	32	- Per claim: Verdict label + Confidence % + Brief reasoning (1-3 sentences)
	33	- Verdict labels: WELL-SUPPORTED / PARTIALLY SUPPORTED / UNCERTAIN / REFUTED
	34
	35	4. ARTICLE SUMMARY (optional)
	36	- 3-5 sentences
	37	- Neutral summary of article content
	38
2.2	39	Total output: 200-300 words
1.1	40
2.2	41	=== What's NOT in POC ===
1.1	42
2.1	43	❌ Scenarios (multiple interpretations)
	44	❌ Evidence display (supporting/opposing lists)
	45	❌ Source links
	46	❌ Detailed reasoning chains
	47	❌ User accounts, history, search
	48	❌ Browser extensions, API
	49	❌ Accessibility, multilingual, mobile
	50	❌ Export, sharing features
1.1	51	❌ Any other features
	52
2.2	53	=== Critical Requirement ===
1.1	54
	55	FULLY AUTOMATED - NO MANUAL EDITING
	56
	57	This is non-negotiable. POC tests whether AI can do this without human intervention.
	58
2.2	59	=== POC Success Criteria ===
1.1	60
	61	Passes if:
	62	- ✅ AI extracts 3-5 factual claims automatically
	63	- ✅ AI provides reasonable verdicts (≥70% make sense)
	64	- ✅ Output is comprehensible
	65	- ✅ Team agrees approach has merit
	66	- ✅ Minimal or no manual editing needed
	67
	68	Fails if:
	69	- ❌ Claim extraction poor (< 60% accuracy)
	70	- ❌ Verdicts nonsensical (< 60% reasonable)
	71	- ❌ Requires manual editing for most analyses (> 50%)
	72	- ❌ Team loses confidence in approach
	73
2.2	74	=== POC Architecture ===
1.1	75
2.1	76	Frontend: Simple input form + results display
	77	Backend: Single API call to Claude (Sonnet 4.5)
	78	Processing: One prompt generates complete analysis
1.1	79	Database: None required (stateless)
	80
2.2	81	=== POC Philosophy ===
1.1	82
	83	> "Build less, learn more, decide faster. Test the hardest part first."
	84
2.1	85	=== Context-Aware Analysis (Experimental POC1 Feature) ===
1.1	86
2.1	87	Problem: Article credibility ≠ simple average of claim verdicts
1.1	88
2.1	89	Example: Article with accurate facts (coffee has antioxidants, antioxidants fight cancer) but false conclusion (therefore coffee cures cancer) would score as "mostly accurate" with simple averaging, but is actually MISLEADING.
1.1	90
2.1	91	Solution (POC1 Test): Approach 1 - Single-Pass Holistic Analysis
2.2	92
2.1	93	* Enhanced AI prompt to evaluate logical structure
	94	* AI identifies main argument and assesses if it follows from evidence
	95	* Article verdict may differ from claim average
	96	* Zero additional cost, no architecture changes
1.1	97
2.1	98	Testing:
2.2	99
2.1	100	* 30-article test set
	101	* Success: ≥70% accuracy detecting misleading articles
	102	* Marked as experimental
1.1	103
2.1	104	See: [[Article Verdict Problem>>FactHarbor.Specification.POC.Article-Verdict-Problem]] for full analysis and solution approaches.
1.1	105
2.1	106	== 2. POC2 Specification ==
1.1	107
2.1	108	=== POC2 Goal ===
2.2	109
2.1	110	Prove that AKEL produces high-quality outputs consistently at scale with complete quality validation.
1.1	111
2.1	112	=== POC2 Enhancements (From POC1) ===
1.1	113
2.4	114	* \\
	115	** \\
2.2	116	**1. COMPLETE QUALITY GATES (All 4)
2.1	117	* Gate 1: Claim Validation (from POC1)
	118	* Gate 2: Evidence Relevance ← NEW
	119	* Gate 3: Scenario Coherence ← NEW
	120	* Gate 4: Verdict Confidence (from POC1)
1.1	121
2.1	122	2. EVIDENCE DEDUPLICATION (FR54)
2.2	123
2.1	124	* Prevent counting same source multiple times
	125	* Handle syndicated content (AP, Reuters)
	126	* Content fingerprinting with fuzzy matching
	127	* Target: >95% duplicate detection accuracy
1.1	128
2.1	129	3. CONTEXT-AWARE ANALYSIS (Conditional)
2.2	130
2.1	131	* If POC1 succeeds (≥70%): Implement as standard feature
	132	* If POC1 promising (50-70%): Try weighted aggregation approach
	133	* If POC1 fails (<50%): Defer to post-POC2
	134	* Detects articles with accurate claims but misleading conclusions
1.1	135
2.1	136	4. QUALITY METRICS DASHBOARD (NFR13)
2.2	137
2.1	138	* Track hallucination rates
	139	* Monitor gate performance
	140	* Evidence quality metrics
	141	* Processing statistics
1.1	142
2.1	143	=== What's Still NOT in POC2 ===
1.1	144
2.1	145	❌ User accounts, authentication
	146	❌ Public publishing interface
	147	❌ Social sharing features
	148	❌ Full production security (comes in Beta 0)
	149	❌ In-article claim highlighting (comes in Beta 0)
1.1	150
2.1	151	=== Success Criteria ===
1.1	152
2.1	153	Quality:
2.2	154
2.1	155	* Hallucination rate <5% (target: <3%)
	156	* Average quality rating ≥8.0/10
	157	* Gates identify >95% of low-quality outputs
1.1	158
2.1	159	Performance:
2.2	160
2.1	161	* All 4 quality gates operational
	162	* Evidence deduplication >95% accurate
	163	* Quality metrics tracked continuously
1.1	164
2.1	165	Context-Aware (if implemented):
2.2	166
2.1	167	* Maintains ≥70% accuracy detecting misleading articles
	168	* <15% false positive rate
1.1	169
2.2	170	Total Output Size: Similar to POC1 (220-350 words per analysis)
1.1	171
2.2	172	== 2. Key Strategic Recommendations ==
1.1	173
2.2	174	=== Immediate Actions ===
1.1	175
	176	For POC:
2.2	177
1.1	178	1. Focus on core functionality only (claims + verdicts)
	179	2. Create basic explainer (1 page)
	180	3. Test AI quality without manual editing
	181	4. Make GO/NO-GO decision
	182
	183	Planning:
2.2	184
1.1	185	1. Define accessibility strategy (when to build)
	186	2. Decide on multilingual priorities (which languages first)
	187	3. Research media verification options (partner vs build)
	188	4. Evaluate browser extension approach
	189
2.2	190	=== Testing Strategy ===
1.1	191
2.1	192	POC Tests: Can AI do this without humans?
	193	Beta Tests: What do users need? What works? What doesn't?
1.1	194	Release Tests: Is it production-ready?
	195
	196	Key Principle: Test assumptions before building features.
	197
2.2	198	=== Build Sequence (Priority Order) ===
1.1	199
	200	Must Build:
2.2	201
1.1	202	1. Core analysis (claims + verdicts) ← POC
	203	2. Educational resources (basic → comprehensive)
	204	3. Accessibility (WCAG 2.1 AA) ← Legal requirement
	205
	206	Should Build (Validate First):
	207	4. Browser extensions ← Test demand
	208	5. Media verification ← Pilot with existing tools
	209	6. Multilingual ← Start with 2-3 languages
	210
	211	Can Build Later:
	212	7. Mobile apps ← PWA first
	213	8. ClaimReview schema ← After content library
	214	9. Export features ← Based on user requests
	215	10. Everything else ← Based on validation
	216
2.2	217	=== Decision Framework ===
1.1	218
	219	For each feature, ask:
2.2	220
1.1	221	1. Importance: Risk + Impact + Strategy alignment?
	222	2. Urgency: Fail fast + Legal + Promises?
	223	3. Validation: Do we know users want this?
	224	4. Priority: When should we build it?
	225
	226	Don't build anything without answering these questions.
	227
2.2	228	== 4. Critical Principles ==
1.1	229
2.1	230	=== Automation First
1.1	231	- AI makes content decisions
	232	- Humans improve algorithms
2.2	233	- Scale through code, not people ===
1.1	234
2.1	235	=== Fail Fast
1.1	236	- Test assumptions quickly
	237	- Don't build unvalidated features
	238	- Accept that experiments may fail
2.2	239	- Learn from failures ===
1.1	240
2.1	241	=== Evidence Over Authority
1.1	242	- Transparent reasoning visible
	243	- No single "true/false" verdicts
	244	- Multiple scenarios shown
2.2	245	- Assumptions made explicit ===
1.1	246
2.1	247	=== User Focus
1.1	248	- Serve users' needs first
	249	- Build what's actually useful
	250	- Don't build what's just "cool"
2.2	251	- Measure and iterate ===
1.1	252
2.1	253	=== Honest Assessment
1.1	254	- Don't cherry-pick examples
	255	- Document failures openly
	256	- Accept limitations
2.2	257	- No overpromising ===
1.1	258
2.2	259	== 5. POC Decision Gate ==
1.1	260
2.2	261	=== After POC, Choose: ===
1.1	262
	263	GO (Proceed to Beta):
	264	- AI quality ≥70% without editing
	265	- Approach validated
	266	- Team confident
	267	- Clear path to improvement
	268
	269	NO-GO (Pivot or Stop):
	270	- AI quality < 60%
	271	- Requires manual editing for most
	272	- Fundamental flaws identified
	273	- Not feasible with current technology
	274
	275	ITERATE (Improve & Retry):
	276	- Concept has merit
	277	- Specific improvements identified
	278	- Addressable with better prompts
	279	- Test again after changes
	280
2.2	281	== 6. Key Risks & Mitigations ==
1.1	282
2.1	283	=== Risk 1: AI Quality Not Good Enough
	284	Mitigation: Extensive prompt testing, use best models
2.2	285	Acceptance: POC might fail - that's what testing reveals ===
1.1	286
2.1	287	=== Risk 2: Users Don't Understand Output
	288	Mitigation: Create clear explainer, test with real users
2.2	289	Acceptance: Iterate on explanation until comprehensible ===
1.1	290
2.1	291	=== Risk 3: Approach Doesn't Scale
	292	Mitigation: Start simple, add complexity only when proven
2.2	293	Acceptance: POC proves concept, beta proves scale ===
1.1	294
2.1	295	=== Risk 4: Legal/Compliance Issues
	296	Mitigation: Plan accessibility early, consult legal experts
2.2	297	Acceptance: Can't launch publicly without compliance ===
1.1	298
2.1	299	=== Risk 5: Feature Creep
	300	Mitigation: Strict scope discipline, say NO to additions
2.2	301	Acceptance: POC is minimal by design ===
1.1	302
2.2	303	== 7. Success Metrics ==
1.1	304
2.1	305	=== POC Success
1.1	306	- AI output quality ≥70%
	307	- Manual editing needed < 30% of time
	308	- Team confidence: High
2.2	309	- Decision: GO to beta ===
1.1	310
2.1	311	=== Platform Success (Later)
1.1	312	- User comprehension ≥80%
	313	- Return user rate ≥30%
	314	- Flag rate (user corrections) < 10%
	315	- Processing time < 30 seconds
2.2	316	- Error rate < 1% ===
1.1	317
2.1	318	=== Mission Success (Long-term)
1.1	319	- Users make better-informed decisions
	320	- Misinformation spread reduced
	321	- Public discourse improves
2.2	322	- Trust in evidence increases ===
1.1	323
2.2	324	== 8. What Makes FactHarbor Different ==
1.1	325
2.1	326	=== Not Traditional Fact-Checking
1.1	327	- ❌ No simple "true/false" verdicts
	328	- ✅ Multiple scenarios with context
	329	- ✅ Transparent reasoning chains
2.2	330	- ✅ Explicit assumptions shown ===
1.1	331
2.1	332	=== Not AI Chatbot
1.1	333	- ❌ Not conversational
	334	- ✅ Structured Evidence Models
	335	- ✅ Reproducible analysis
2.2	336	- ✅ Verifiable sources ===
1.1	337
2.1	338	=== Not Just Automation
1.1	339	- ❌ Not replacing human judgment
	340	- ✅ Augmenting human reasoning
	341	- ✅ Making process transparent
2.2	342	- ✅ Enabling informed decisions ===
1.1	343
2.2	344	== 9. Core Philosophy ==
1.1	345
	346	Three Pillars:
	347
2.4	348	* \\
	349	** \\
1.1	350	1. Scenarios Over Verdicts
	351	- Show multiple interpretations
	352	- Make context explicit
	353	- Acknowledge uncertainty
2.2	354	- Avoid false certainty**
1.1	355
	356	2. Transparency Over Authority
	357	- Show reasoning, not just conclusions
	358	- Make assumptions explicit
	359	- Link to evidence
	360	- Enable verification
	361
	362	3. Evidence Over Opinions
	363	- Ground claims in sources
	364	- Show supporting AND opposing evidence
	365	- Evaluate source quality
	366	- Avoid cherry-picking
	367
2.2	368	== 10. Next Actions ==
1.1	369
2.1	370	=== Immediate
	371	□ Review this consolidated summary
	372	□ Confirm POC scope agreement
	373	□ Make strategic decisions on key questions
2.4	374	□ Begin POC development ===
1.1	375
2.1	376	=== Strategic Planning
	377	□ Define accessibility approach
	378	□ Select initial languages for multilingual
	379	□ Research media verification partners
2.4	380	□ Evaluate browser extension frameworks ===
1.1	381
2.1	382	=== Continuous
	383	□ Test assumptions before building
	384	□ Measure everything
	385	□ Learn from failures
2.4	386	□ Stay focused on mission ===
1.1	387
2.2	388	== Summary of Summaries ==
1.1	389
2.1	390	POC Goal: Prove AI can do this automatically
2.2	391	POC Scope: 4 simple components, 200-300 words
2.1	392	POC Critical: Fully automated, no manual editing
	393	POC Success: ≥70% quality without human correction
1.1	394
2.1	395	Gap Analysis: 18 gaps identified, 2 critical (Accessibility + Education)
	396	Framework: Importance (risk + impact + strategy) + Urgency (fail fast + legal + promises)
	397	Key Insight: Context matters - urgency changes with milestones
1.1	398
2.1	399	Strategy: Test first, build second. Fail fast. Stay focused.
	400	Philosophy: Scenarios, transparency, evidence. No false certainty.
1.1	401
2.2	402	== Document Status ==
1.1	403
	404	This document supersedes all previous analysis documents.
	405
	406	All gap analysis, POC specifications, and strategic frameworks are consolidated here without timeline references.
	407
	408	For detailed specifications, refer to:
	409	- User Needs document (in project knowledge)
	410	- Requirements document (in project knowledge)
	411	- This summary (comprehensive overview)
	412
	413	Previous documents are archived for reference but this is the authoritative summary.
	414
	415	End of Consolidated Summary

Wiki source code of POC Summary (POC1 & POC2)

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