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