Wiki source code of Continuous Improvement

Last modified by Robert Schaub on 2025/12/22 14:37

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1 = Continuous Improvement =
2 **From Sociocracy 3.0**: Empirical approach to improving FactHarbor systems.
3 == 1. Philosophy ==
4 **Continuous improvement** means:
5 * We're never "done" - systems always improve
6 * Learn from data, not opinions
7 * Small experiments, frequent iteration
8 * Measure everything
9 * Build, measure, learn, repeat
10 **Inspired by**:
11 * Sociocracy 3.0 empiricism principle
12 * Agile/lean methodologies
13 * Scientific method
14 * DevOps continuous deployment
15 == 2. What We Improve ==
16 === 2.1 AKEL Performance ===
17 **Processing speed**:
18 * Faster claim parsing
19 * Optimized evidence extraction
20 * Efficient source lookups
21 * Reduced latency
22 **Quality**:
23 * Better evidence detection
24 * More accurate verdicts
25 * Improved source scoring
26 * Enhanced contradiction detection
27 **Reliability**:
28 * Fewer errors
29 * Better error handling
30 * Graceful degradation
31 * Faster recovery
32 === 2.2 Policies ===
33 **Risk tier definitions**:
34 * Clearer criteria
35 * Better domain coverage
36 * Edge case handling
37 **Evidence weighting**:
38 * More appropriate weights by domain
39 * Better peer-review recognition
40 * Improved recency handling
41 **Source scoring**:
42 * More nuanced credibility assessment
43 * Better handling of new sources
44 * Domain-specific adjustments
45 === 2.3 Infrastructure ===
46 **Performance**:
47 * Database optimization
48 * Caching strategies
49 * Network efficiency
50 * Resource utilization
51 **Scalability**:
52 * Handle more load
53 * Geographic distribution
54 * Cost efficiency
55 **Monitoring**:
56 * Better dashboards
57 * Faster alerts
58 * More actionable metrics
59 === 2.4 Processes ===
60 **Contributor workflows**:
61 * Easier onboarding
62 * Clearer documentation
63 * Better tools
64 **Decision-making**:
65 * Faster decisions
66 * Better documentation
67 * Clearer escalation
68 == 3. Improvement Cycle ==
69 === 3.1 Observe ===
70 **Continuously monitor**:
71 * Performance metrics dashboards
72 * User feedback patterns
73 * AKEL processing logs
74 * Error reports
75 * Community discussions
76 **Look for**:
77 * Metrics outside acceptable ranges
78 * Systematic patterns in errors
79 * User pain points
80 * Opportunities for optimization
81 === 3.2 Analyze ===
82 **Dig deeper**:
83 * Why is this metric problematic?
84 * Is this a systematic issue or one-off?
85 * What's the root cause?
86 * What patterns exist?
87 * How widespread is this?
88 **Tools**:
89 * Data analysis (SQL queries, dashboards)
90 * Code profiling
91 * A/B test results
92 * User interviews
93 * Historical comparison
94 === 3.3 Hypothesize ===
95 **Propose explanation**:
96 * "We believe X is happening because Y"
97 * "If we change Z, we expect W to improve"
98 * "The root cause is likely A, not B"
99 **Make testable**:
100 * What would prove this hypothesis?
101 * What would disprove it?
102 * What metrics would change?
103 === 3.4 Design Solution ===
104 **Propose specific change**:
105 * Algorithm adjustment
106 * Policy clarification
107 * Infrastructure upgrade
108 * Process refinement
109 **Consider**:
110 * Trade-offs
111 * Risks
112 * Rollback plan
113 * Success metrics
114 === 3.5 Test ===
115 **Before full deployment**:
116 * Test environment deployment
117 * Historical data validation
118 * A/B testing if feasible
119 * Load testing if infrastructure
120 **Measure**:
121 * Did metrics improve as expected?
122 * Any unexpected side effects?
123 * Is the improvement statistically significant?
124 === 3.6 Deploy ===
125 **Gradual rollout**:
126 * Deploy to small % of traffic first
127 * Monitor closely
128 * Increase gradually if successful
129 * Rollback if problems
130 **Deployment strategies**:
131 * Canary (1% → 5% → 25% → 100%)
132 * Blue-green (instant swap with rollback ready)
133 * Feature flags (enable for specific users first)
134 === 3.7 Evaluate ===
135 **After deployment**:
136 * Review metrics - did they improve?
137 * User feedback - positive or negative?
138 * Unexpected effects - any surprises?
139 * Lessons learned - what would we do differently?
140 === 3.8 Iterate ===
141 **Based on results**:
142 * If successful: Document, celebrate, move to next improvement
143 * If partially successful: Refine and iterate
144 * If unsuccessful: Rollback, analyze why, try different approach
145 **Document learnings**: Update RFC with actual outcomes.
146 == 4. Improvement Cadence ==
147 === 4.1 Continuous (Ongoing) ===
148 **Daily/Weekly**:
149 * Monitor dashboards
150 * Review user feedback
151 * Identify emerging issues
152 * Quick fixes and patches
153 **Who**: Technical Coordinator, Community Coordinator
154 === 4.2 Sprint Cycles (2 weeks) ===
155 **Every 2 weeks**:
156 * Sprint planning: Select improvements to tackle
157 * Implementation: Build and test
158 * Sprint review: Demo what was built
159 * Retrospective: How can we improve the improvement process?
160 **Who**: Core team + regular contributors
161 === 4.3 Quarterly Reviews (3 months) ===
162 **Every quarter**:
163 * Comprehensive performance review
164 * Policy effectiveness assessment
165 * Strategic improvement priorities
166 * Architectural decisions
167 **Who**: Governing Team + Technical Coordinator
168 **Output**: Quarterly report, next quarter priorities
169 === 4.4 Annual Planning (Yearly) ===
170 **Annually**:
171 * Major strategic direction
172 * Significant architectural changes
173 * Multi-quarter initiatives
174 * Budget allocation
175 **Who**: General Assembly
176 == 5. Metrics-Driven Improvement ==
177 === 5.1 Key Performance Indicators (KPIs) ===
178 **AKEL Performance**:
179 * Processing time (P50, P95, P99)
180 * Success rate
181 * Evidence completeness
182 * Confidence distribution
183 **Content Quality**:
184 * User feedback (helpful/unhelpful ratio)
185 * Contradiction rate
186 * Source diversity
187 * Scenario coverage
188 **System Health**:
189 * Uptime
190 * Error rate
191 * Response time
192 * Resource utilization
193 **See**: [[System Performance Metrics>>FactHarbor.Specification.System-Performance-Metrics]]
194 === 5.2 Targets and Thresholds ===
195 **For each metric**:
196 * Target: Where we want to be
197 * Acceptable range: What's OK
198 * Alert threshold: When to intervene
199 * Critical threshold: Emergency
200 **Example**:
201 * Processing time P95 * Target: 15 seconds * Acceptable: 10-18 seconds * Alert: >20 seconds * Critical: >30 seconds
202 === 5.3 Metric-Driven Decisions ===
203 **Improvements prioritized by**:
204 * Impact on metrics
205 * Effort required
206 * Risk level
207 * Strategic importance
208 **Not by**:
209 * Personal preferences
210 * Loudest voice
211 * Political pressure
212 * Gut feeling
213 == 6. Experimentation ==
214 === 6.1 A/B Testing ===
215 **When feasible**:
216 * Run two versions simultaneously
217 * Randomly assign users/claims
218 * Measure comparative performance
219 * Choose winner based on data
220 **Good for**:
221 * Algorithm parameter tuning
222 * UI/UX changes
223 * Policy variations
224 === 6.2 Canary Deployments ===
225 **Small-scale first**:
226 * Deploy to 1% of traffic
227 * Monitor closely for issues
228 * Gradually increase if successful
229 * Full rollback if problems
230 **Benefits**:
231 * Limits blast radius of failures
232 * Real-world validation
233 * Quick feedback loop
234 === 6.3 Feature Flags ===
235 **Controlled rollout**:
236 * Deploy code but disable by default
237 * Enable for specific users/scenarios
238 * Gather feedback before full release
239 * Easy enable/disable without redeployment
240 == 7. Retrospectives ==
241 === 7.1 Sprint Retrospectives (Every 2 weeks) ===
242 **Questions**:
243 * What went well?
244 * What could be improved?
245 * What will we commit to improving?
246 **Format** (30 minutes):
247 * Gather data: Everyone writes thoughts (5 min)
248 * Generate insights: Discuss patterns (15 min)
249 * Decide actions: Pick 1-3 improvements (10 min)
250 **Output**: 1-3 concrete actions for next sprint
251 === 7.2 Project Retrospectives (After major changes) ===
252 **After significant changes**:
253 * What was the goal?
254 * What actually happened?
255 * What went well?
256 * What went poorly?
257 * What did we learn?
258 * What would we do differently?
259 **Document**: Update project documentation with learnings
260 === 7.3 Incident Retrospectives (After failures) ===
261 **After incidents/failures**:
262 * Timeline: What happened when?
263 * Root cause: Why did it happen?
264 * Impact: What was affected?
265 * Response: How did we handle it?
266 * Prevention: How do we prevent this?
267 **Blameless**: Focus on systems, not individuals.
268 **Output**: Action items to prevent recurrence
269 == 8. Knowledge Management ==
270 === 8.1 Documentation ===
271 **Keep updated**:
272 * Architecture docs
273 * API documentation
274 * Operational runbooks
275 * Decision records
276 * Retrospective notes
277 **Principle**: Future you/others need to understand why decisions were made.
278 === 8.2 Decision Records ===
279 **For significant decisions, document**:
280 * What was decided?
281 * What problem does this solve?
282 * What alternatives were considered?
283 * What are the trade-offs?
284 * What are the success metrics?
285 * Review date?
286 **See**: [[Decision Processes>>FactHarbor.Organisation.Decision-Processes]]
287 === 8.3 Learning Library ===
288 **Collect**:
289 * Failed experiments (what didn't work)
290 * Successful patterns (what worked well)
291 * External research relevant to FactHarbor
292 * Best practices from similar systems
293 **Share**: Make accessible to all contributors
294 == 9. Continuous Improvement of Improvement ==
295 **Meta-improvement**: Improve how we improve.
296 **Questions to ask**:
297 * Is our improvement cycle effective?
298 * Are we measuring the right things?
299 * Are decisions actually data-driven?
300 * Is knowledge being captured?
301 * Are retrospectives actionable?
302 * Are improvements sustained?
303 **Annually review**: How can our improvement process itself improve?
304 == 10. Cultural Practices ==
305 === 10.1 Safe to Fail ===
306 **Encourage experimentation**:
307 * ✅ Try new approaches
308 * ✅ Test hypotheses
309 * ✅ Learn from failures
310 * ✅ Share what didn't work
311 **Not blame**:
312 * ❌ "Who broke it?"
313 * ❌ "Why didn't you know?"
314 * ❌ "This was a stupid idea"
315 **Instead**:
316 * ✅ "What did we learn?"
317 * ✅ "How can we prevent this?"
318 * ✅ "What will we try next?"
319 === 10.2 Data Over Opinions ===
320 **Settle debates with**:
321 * ✅ Metrics and measurements
322 * ✅ A/B test results
323 * ✅ User feedback data
324 * ✅ Performance benchmarks
325 **Not with**:
326 * ❌ "I think..."
327 * ❌ "In my experience..."
328 * ❌ "I've seen this before..."
329 * ❌ "Trust me..."
330 === 10.3 Bias Toward Action ===
331 **Good enough for now, safe enough to try**:
332 * Don't wait for perfect solution
333 * Test and learn
334 * Iterate quickly
335 * Prefer reversible decisions
336 **But not reckless**:
337 * Do test before deploying
338 * Do monitor after deploying
339 * Do have rollback plan
340 * Do document decisions
341 == 11. Tools and Infrastructure ==
342 **Support continuous improvement with**:
343 **Monitoring**:
344 * Real-time dashboards
345 * Alerting systems
346 * Log aggregation
347 * Performance profiling
348 **Testing**:
349 * Automated testing (unit, integration, regression)
350 * Test environments
351 * A/B testing framework
352 * Load testing tools
353 **Deployment**:
354 * CI/CD pipelines
355 * Canary deployment support
356 * Feature flag system
357 * Quick rollback capability
358 **Collaboration**:
359 * RFC repository
360 * Decision log
361 * Knowledge base
362 * Retrospective notes **Remember**: Continuous improvement means we're always learning, always testing, always getting better.
363 == 12. Related Pages ==
364 * [[Automation Philosophy>>FactHarbor.Organisation.Automation-Philosophy]] - Why we automate
365 * [[System Performance Metrics>>FactHarbor.Specification.System-Performance-Metrics]] - What we measure
366 * [[Contributor Processes>>FactHarbor.Organisation.Contributor-Processes]] - How to propose improvements
367 * [[Governance>>FactHarbor.Organisation.Governance.WebHome]] - How improvements are approved