agents

-module(self_reflection_system).
-behaviour(gen_statem).

-export([start_link/0, start_link/1]).
-export([initiate_self_reflection/1, assess_performance/1, evaluate_decisions/1,
         analyze_learning_progress/1, reflect_on_goals/1, examine_biases/1,
         update_self_model/2, get_self_assessment/1, trigger_metacognition/1]).
-export([init/1, callback_mode/0, terminate/3, code_change/4]).
-export([idle/3, self_assessment/3, metacognitive_analysis/3, bias_examination/3,
         decision_evaluation/3, learning_reflection/3, goal_alignment/3,
         self_model_update/3, insight_integration/3, wisdom_synthesis/3]).

-record(cognitive_profile, {
    strengths = [] :: [atom()],
    weaknesses = [] :: [atom()],
    learning_style = undefined :: undefined | atom(),
    decision_patterns = #{} :: #{atom() => term()},
    bias_tendencies = [] :: [atom()],
    metacognitive_awareness = 0.0 :: float(),
    self_efficacy = 0.0 :: float(),
    adaptability_score = 0.0 :: float(),
    emotional_intelligence = 0.0 :: float(),
    critical_thinking = 0.0 :: float()
}).

-record(reflection_insight, {
    type :: atom(),
    content :: term(),
    confidence = 0.0 :: float(),
    impact_level = low :: low | medium | high | critical,
    actionable_items = [] :: [term()],
    timestamp :: erlang:timestamp(),
    validation_status = pending :: pending | validated | rejected
}).

-record(self_reflection_data, {
    session_id :: term(),
    cognitive_profile = #cognitive_profile{} :: #cognitive_profile{},
    historical_profiles = [] :: [#cognitive_profile{}],
    current_insights = [] :: [#reflection_insight{}],
    decision_history = [] :: [term()],
    learning_episodes = [] :: [term()],
    goal_evolution = [] :: [term()],
    performance_metrics = #{} :: #{atom() => number()},
    metacognitive_state = #{
        awareness_level => 0.0,
        confidence_level => 0.0,
        reflection_depth => shallow,
        cognitive_load => low
    } :: #{atom() => term()},
    self_model = #{
        identity => undefined,
        capabilities => [],
        limitations => [],
        values => [],
        beliefs => [],
        assumptions => []
    } :: #{atom() => term()},
    reflection_triggers = #{
        performance_threshold => 0.7,
        decision_complexity => medium,
        learning_plateau => true,
        goal_misalignment => true,
        bias_detection => true
    } :: #{atom() => term()},
    wisdom_accumulation = #{
        lessons_learned => [],
        principles_discovered => [],
        mental_models => [],
        heuristics => [],
        patterns => []
    } :: #{atom() => [term()]},
    self_improvement_plan = [] :: [term()],
    reflection_statistics = #{} :: #{atom() => term()},
    observers = [] :: [pid()],
    continuous_mode = false :: boolean(),
    reflection_interval = 10000 :: pos_integer(),
    start_time :: erlang:timestamp()
}).

start_link() ->
    gen_statem:start_link(?MODULE, [], []).

start_link(Options) ->
    gen_statem:start_link(?MODULE, Options, []).

initiate_self_reflection(Pid) ->
    gen_statem:call(Pid, initiate_self_reflection).

assess_performance(Pid) ->
    gen_statem:call(Pid, assess_performance).

evaluate_decisions(Pid) ->
    gen_statem:call(Pid, evaluate_decisions).

analyze_learning_progress(Pid) ->
    gen_statem:call(Pid, analyze_learning_progress).

reflect_on_goals(Pid) ->
    gen_statem:call(Pid, reflect_on_goals).

examine_biases(Pid) ->
    gen_statem:call(Pid, examine_biases).

update_self_model(Pid, Updates) ->
    gen_statem:call(Pid, {update_self_model, Updates}).

get_self_assessment(Pid) ->
    gen_statem:call(Pid, get_self_assessment).

trigger_metacognition(Pid) ->
    gen_statem:call(Pid, trigger_metacognition).

init(Options) ->
    Data = #self_reflection_data{
        session_id = make_ref(),
        continuous_mode = proplists:get_value(continuous, Options, false),
        reflection_interval = proplists:get_value(interval, Options, 10000),
        start_time = erlang:timestamp(),
        cognitive_profile = initialize_cognitive_profile(),
        reflection_triggers = initialize_reflection_triggers(Options),
        reflection_statistics = #{
            reflection_sessions => 0,
            insights_generated => 0,
            biases_detected => 0,
            decisions_evaluated => 0,
            learning_episodes_analyzed => 0,
            self_model_updates => 0,
            metacognitive_events => 0
        }
    },
    {ok, idle, Data}.

callback_mode() -> [state_functions, state_enter].

idle(enter, _OldState, Data) ->
    case Data#self_reflection_data.continuous_mode of
        true ->
            {keep_state, Data, [{state_timeout, Data#self_reflection_data.reflection_interval, continuous_reflection}]};
        false ->
            {keep_state, Data}
    end;
idle({call, From}, initiate_self_reflection, Data) ->
    ReflectionData = begin_reflection_session(Data),
    {next_state, self_assessment, ReflectionData, [{reply, From, ok}]};
idle({call, From}, assess_performance, Data) ->
    {next_state, self_assessment, Data, [{reply, From, ok}, {state_timeout, 0, performance_focus}]};
idle({call, From}, examine_biases, Data) ->
    {next_state, bias_examination, Data, [{reply, From, ok}]};
idle({call, From}, trigger_metacognition, Data) ->
    {next_state, metacognitive_analysis, Data, [{reply, From, ok}]};
idle(state_timeout, continuous_reflection, Data) ->
    {next_state, self_assessment, begin_reflection_session(Data)};
idle(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data).

self_assessment(enter, _OldState, Data) ->
    AssessmentData = conduct_comprehensive_self_assessment(Data),
    UpdatedStats = increment_stat(reflection_sessions, Data#self_reflection_data.reflection_statistics),
    {next_state, metacognitive_analysis, AssessmentData#self_reflection_data{reflection_statistics = UpdatedStats}};
self_assessment(state_timeout, performance_focus, Data) ->
    PerformanceData = focus_on_performance_assessment(Data),
    {next_state, decision_evaluation, PerformanceData};
self_assessment(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data).

metacognitive_analysis(enter, _OldState, Data) ->
    MetacognitiveData = perform_metacognitive_analysis(Data),
    UpdatedStats = increment_stat(metacognitive_events, Data#self_reflection_data.reflection_statistics),
    {next_state, bias_examination, MetacognitiveData#self_reflection_data{reflection_statistics = UpdatedStats}};
metacognitive_analysis(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data).

bias_examination(enter, _OldState, Data) ->
    BiasData = examine_cognitive_biases(Data),
    case detect_significant_biases(BiasData) of
        {biases_found, BiasInsights} ->
            InsightData = record_bias_insights(BiasInsights, BiasData),
            UpdatedStats = increment_stat(biases_detected, InsightData#self_reflection_data.reflection_statistics),
            {next_state, decision_evaluation, InsightData#self_reflection_data{reflection_statistics = UpdatedStats}};
        no_significant_biases ->
            {next_state, decision_evaluation, BiasData}
    end;
bias_examination(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data).

decision_evaluation(enter, _OldState, Data) ->
    DecisionData = evaluate_recent_decisions(Data),
    case analyze_decision_quality(DecisionData) of
        {insights_available, DecisionInsights} ->
            InsightData = integrate_decision_insights(DecisionInsights, DecisionData),
            UpdatedStats = increment_stat(decisions_evaluated, InsightData#self_reflection_data.reflection_statistics),
            {next_state, learning_reflection, InsightData#self_reflection_data{reflection_statistics = UpdatedStats}};
        no_significant_insights ->
            {next_state, learning_reflection, DecisionData}
    end;
decision_evaluation(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data).

learning_reflection(enter, _OldState, Data) ->
    LearningData = analyze_learning_progress_and_patterns(Data),
    case identify_learning_insights(LearningData) of
        {learning_insights, Insights} ->
            InsightData = integrate_learning_insights(Insights, LearningData),
            UpdatedStats = increment_stat(learning_episodes_analyzed, InsightData#self_reflection_data.reflection_statistics),
            {next_state, goal_alignment, InsightData#self_reflection_data{reflection_statistics = UpdatedStats}};
        no_learning_insights ->
            {next_state, goal_alignment, LearningData}
    end;
learning_reflection(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data).

goal_alignment(enter, _OldState, Data) ->
    GoalData = assess_goal_alignment_and_evolution(Data),
    case evaluate_goal_coherence(GoalData) of
        {alignment_issues, Issues} ->
            UpdatedData = address_goal_misalignment(Issues, GoalData),
            {next_state, self_model_update, UpdatedData};
        goals_aligned ->
            {next_state, self_model_update, GoalData}
    end;
goal_alignment(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data).

self_model_update(enter, _OldState, Data) ->
    ModelData = update_self_model_based_on_insights(Data),
    case significant_model_changes(ModelData) of
        true ->
            UpdatedStats = increment_stat(self_model_updates, ModelData#self_reflection_data.reflection_statistics),
            {next_state, insight_integration, ModelData#self_reflection_data{reflection_statistics = UpdatedStats}};
        false ->
            {next_state, insight_integration, ModelData}
    end;
self_model_update(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data).

insight_integration(enter, _OldState, Data) ->
    IntegrationData = integrate_all_insights(Data),
    PlanData = formulate_self_improvement_plan(IntegrationData),
    UpdatedStats = increment_stat(insights_generated, PlanData#self_reflection_data.reflection_statistics),
    {next_state, wisdom_synthesis, PlanData#self_reflection_data{reflection_statistics = UpdatedStats}};
insight_integration(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data).

wisdom_synthesis(enter, _OldState, Data) ->
    WisdomData = synthesize_wisdom_from_reflection(Data),
    FinalData = complete_reflection_cycle(WisdomData),
    
    case Data#self_reflection_data.continuous_mode of
        true ->
            {next_state, idle, FinalData};
        false ->
            {keep_state, FinalData}
    end;
wisdom_synthesis({call, From}, get_self_assessment, Data) ->
    Assessment = compile_self_assessment_report(Data),
    {keep_state, Data, [{reply, From, {ok, Assessment}}]};
wisdom_synthesis(EventType, Event, Data) ->
    handle_common_events(EventType, Event, Data).

terminate(_Reason, _State, _Data) ->
    ok.

code_change(_Vsn, State, Data, _Extra) ->
    {ok, State, Data}.

begin_reflection_session(Data) ->
    Data#self_reflection_data{
        session_id = make_ref(),
        current_insights = [],
        start_time = erlang:timestamp()
    }.

conduct_comprehensive_self_assessment(Data) ->
    Profile = Data#self_reflection_data.cognitive_profile,
    
    StrengthsAssessment = assess_cognitive_strengths(Profile, Data),
    WeaknessesAssessment = identify_cognitive_weaknesses(Profile, Data),
    MetacognitiveAssessment = evaluate_metacognitive_awareness(Profile, Data),
    AdaptabilityAssessment = assess_adaptability(Profile, Data),
    
    UpdatedProfile = Profile#cognitive_profile{
        strengths = StrengthsAssessment,
        weaknesses = WeaknessesAssessment,
        metacognitive_awareness = MetacognitiveAssessment,
        adaptability_score = AdaptabilityAssessment
    },
    
    Data#self_reflection_data{cognitive_profile = UpdatedProfile}.

focus_on_performance_assessment(Data) ->
    PerformanceMetrics = collect_performance_data(Data),
    PerformanceAnalysis = analyze_performance_trends(PerformanceMetrics),
    PerformanceInsights = generate_performance_insights(PerformanceAnalysis),
    
    Data#self_reflection_data{
        performance_metrics = PerformanceMetrics,
        current_insights = PerformanceInsights ++ Data#self_reflection_data.current_insights
    }.

perform_metacognitive_analysis(Data) ->
    MetacognitiveState = Data#self_reflection_data.metacognitive_state,
    
    AwarenessAnalysis = analyze_self_awareness_levels(MetacognitiveState, Data),
    ConfidenceAnalysis = evaluate_confidence_calibration(MetacognitiveState, Data),
    ReflectionDepthAnalysis = assess_reflection_depth_effectiveness(MetacognitiveState, Data),
    CognitiveLoadAnalysis = analyze_cognitive_load_patterns(MetacognitiveState, Data),
    
    UpdatedMetacognitiveState = #{
        awareness_level => AwarenessAnalysis,
        confidence_level => ConfidenceAnalysis,
        reflection_depth => ReflectionDepthAnalysis,
        cognitive_load => CognitiveLoadAnalysis
    },
    
    Data#self_reflection_data{metacognitive_state = UpdatedMetacognitiveState}.

examine_cognitive_biases(Data) ->
    Profile = Data#self_reflection_data.cognitive_profile,
    DecisionHistory = Data#self_reflection_data.decision_history,
    
    ConfirmationBias = detect_confirmation_bias(DecisionHistory),
    AnchoringBias = detect_anchoring_bias(DecisionHistory),
    AvailabilityBias = detect_availability_bias(DecisionHistory),
    OverconfidenceBias = detect_overconfidence_bias(Profile, DecisionHistory),
    
    DetectedBiases = [B || B <- [ConfirmationBias, AnchoringBias, AvailabilityBias, OverconfidenceBias], B =/= none],
    
    UpdatedProfile = Profile#cognitive_profile{bias_tendencies = DetectedBiases},
    Data#self_reflection_data{cognitive_profile = UpdatedProfile}.

detect_significant_biases(Data) ->
    Biases = Data#self_reflection_data.cognitive_profile#cognitive_profile.bias_tendencies,
    case length(Biases) of
        0 -> no_significant_biases;
        Count when Count > 0 ->
            BiasInsights = [create_bias_insight(Bias) || Bias <- Biases],
            {biases_found, BiasInsights}
    end.

evaluate_recent_decisions(Data) ->
    DecisionHistory = Data#self_reflection_data.decision_history,
    RecentDecisions = lists:sublist(DecisionHistory, 10),
    
    DecisionAnalysis = [analyze_single_decision(Decision, Data) || Decision <- RecentDecisions],
    QualityMetrics = calculate_decision_quality_metrics(DecisionAnalysis),
    
    Data#self_reflection_data{
        performance_metrics = maps:merge(Data#self_reflection_data.performance_metrics, QualityMetrics)
    }.

analyze_decision_quality(Data) ->
    QualityMetrics = maps:get(decision_quality, Data#self_reflection_data.performance_metrics, 0.0),
    case QualityMetrics > 0.7 of
        true -> no_significant_insights;
        false ->
            DecisionInsights = generate_decision_improvement_insights(Data),
            {insights_available, DecisionInsights}
    end.

analyze_learning_progress_and_patterns(Data) ->
    LearningEpisodes = Data#self_reflection_data.learning_episodes,
    
    LearningVelocity = calculate_learning_velocity(LearningEpisodes),
    LearningEfficiency = assess_learning_efficiency(LearningEpisodes),
    KnowledgeRetention = evaluate_knowledge_retention(LearningEpisodes),
    TransferLearning = assess_transfer_learning_capability(LearningEpisodes),
    
    LearningMetrics = #{
        velocity => LearningVelocity,
        efficiency => LearningEfficiency,
        retention => KnowledgeRetention,
        transfer => TransferLearning
    },
    
    Data#self_reflection_data{
        performance_metrics = maps:merge(Data#self_reflection_data.performance_metrics, LearningMetrics)
    }.

identify_learning_insights(Data) ->
    LearningMetrics = maps:get(velocity, Data#self_reflection_data.performance_metrics, 0.0),
    case LearningMetrics < 0.6 of
        true ->
            LearningInsights = generate_learning_improvement_insights(Data),
            {learning_insights, LearningInsights};
        false ->
            no_learning_insights
    end.

assess_goal_alignment_and_evolution(Data) ->
    GoalEvolution = Data#self_reflection_data.goal_evolution,
    SelfModel = Data#self_reflection_data.self_model,
    
    GoalCoherence = assess_internal_goal_coherence(GoalEvolution),
    ValueAlignment = evaluate_goal_value_alignment(GoalEvolution, SelfModel),
    CapabilityAlignment = assess_goal_capability_alignment(GoalEvolution, SelfModel),
    
    Data#self_reflection_data{
        performance_metrics = maps:merge(Data#self_reflection_data.performance_metrics, #{
            goal_coherence => GoalCoherence,
            value_alignment => ValueAlignment,
            capability_alignment => CapabilityAlignment
        })
    }.

evaluate_goal_coherence(Data) ->
    Coherence = maps:get(goal_coherence, Data#self_reflection_data.performance_metrics, 1.0),
    case Coherence < 0.7 of
        true ->
            Issues = identify_goal_coherence_issues(Data),
            {alignment_issues, Issues};
        false ->
            goals_aligned
    end.

update_self_model_based_on_insights(Data) ->
    Insights = Data#self_reflection_data.current_insights,
    SelfModel = Data#self_reflection_data.self_model,
    
    UpdatedModel = apply_insights_to_self_model(Insights, SelfModel),
    Data#self_reflection_data{self_model = UpdatedModel}.

significant_model_changes(Data) ->
    length(Data#self_reflection_data.current_insights) > 3.

integrate_all_insights(Data) ->
    Insights = Data#self_reflection_data.current_insights,
    IntegratedInsights = synthesize_insights(Insights),
    ValidatedInsights = validate_insight_consistency(IntegratedInsights),
    
    Data#self_reflection_data{current_insights = ValidatedInsights}.

formulate_self_improvement_plan(Data) ->
    Insights = Data#self_reflection_data.current_insights,
    CurrentPlan = Data#self_reflection_data.self_improvement_plan,
    
    NewActionItems = generate_action_items_from_insights(Insights),
    UpdatedPlan = integrate_new_action_items(NewActionItems, CurrentPlan),
    PrioritizedPlan = prioritize_improvement_actions(UpdatedPlan),
    
    Data#self_reflection_data{self_improvement_plan = PrioritizedPlan}.

synthesize_wisdom_from_reflection(Data) ->
    Insights = Data#self_reflection_data.current_insights,
    WisdomAccumulation = Data#self_reflection_data.wisdom_accumulation,
    
    NewLessons = extract_lessons_learned(Insights),
    NewPrinciples = derive_principles(Insights),
    NewMentalModels = update_mental_models(Insights, WisdomAccumulation),
    NewHeuristics = develop_heuristics(Insights),
    
    UpdatedWisdom = #{
        lessons_learned => NewLessons ++ maps:get(lessons_learned, WisdomAccumulation, []),
        principles_discovered => NewPrinciples ++ maps:get(principles_discovered, WisdomAccumulation, []),
        mental_models => NewMentalModels,
        heuristics => NewHeuristics ++ maps:get(heuristics, WisdomAccumulation, []),
        patterns => update_wisdom_patterns(Insights, WisdomAccumulation)
    },
    
    Data#self_reflection_data{wisdom_accumulation = UpdatedWisdom}.

complete_reflection_cycle(Data) ->
    Profile = Data#self_reflection_data.cognitive_profile,
    HistoricalProfiles = [Profile | Data#self_reflection_data.historical_profiles],
    
    Data#self_reflection_data{
        historical_profiles = lists:sublist(HistoricalProfiles, 20),
        current_insights = []
    }.

compile_self_assessment_report(Data) ->
    #{
        session_id => Data#self_reflection_data.session_id,
        timestamp => erlang:timestamp(),
        cognitive_profile => Data#self_reflection_data.cognitive_profile,
        metacognitive_state => Data#self_reflection_data.metacognitive_state,
        self_model => Data#self_reflection_data.self_model,
        current_insights => Data#self_reflection_data.current_insights,
        performance_metrics => Data#self_reflection_data.performance_metrics,
        wisdom_accumulation => Data#self_reflection_data.wisdom_accumulation,
        self_improvement_plan => Data#self_reflection_data.self_improvement_plan,
        reflection_statistics => Data#self_reflection_data.reflection_statistics
    }.

record_bias_insights(BiasInsights, Data) ->
    Data#self_reflection_data{
        current_insights = BiasInsights ++ Data#self_reflection_data.current_insights
    }.

integrate_decision_insights(DecisionInsights, Data) ->
    Data#self_reflection_data{
        current_insights = DecisionInsights ++ Data#self_reflection_data.current_insights
    }.

integrate_learning_insights(LearningInsights, Data) ->
    Data#self_reflection_data{
        current_insights = LearningInsights ++ Data#self_reflection_data.current_insights
    }.

address_goal_misalignment(Issues, Data) ->
    MisalignmentInsights = [create_goal_misalignment_insight(Issue) || Issue <- Issues],
    Data#self_reflection_data{
        current_insights = MisalignmentInsights ++ Data#self_reflection_data.current_insights
    }.

increment_stat(Stat, Stats) ->
    maps:update_with(Stat, fun(X) -> X + 1 end, 1, Stats).

handle_common_events({call, From}, get_self_assessment, Data) ->
    Assessment = compile_self_assessment_report(Data),
    {keep_state, Data, [{reply, From, {ok, Assessment}}]};
handle_common_events({call, From}, {update_self_model, Updates}, Data) ->
    UpdatedModel = maps:merge(Data#self_reflection_data.self_model, Updates),
    {keep_state, Data#self_reflection_data{self_model = UpdatedModel}, [{reply, From, ok}]};
handle_common_events({call, From}, evaluate_decisions, Data) ->
    {next_state, decision_evaluation, Data, [{reply, From, ok}]};
handle_common_events({call, From}, analyze_learning_progress, Data) ->
    {next_state, learning_reflection, Data, [{reply, From, ok}]};
handle_common_events({call, From}, reflect_on_goals, Data) ->
    {next_state, goal_alignment, Data, [{reply, From, ok}]};
handle_common_events(_EventType, _Event, _Data) ->
    {keep_state_and_data, [postpone]}.

initialize_cognitive_profile() ->
    #cognitive_profile{
        metacognitive_awareness = 0.5,
        self_efficacy = 0.5,
        adaptability_score = 0.5,
        emotional_intelligence = 0.5,
        critical_thinking = 0.5
    }.

initialize_reflection_triggers(Options) ->
    #{
        performance_threshold => proplists:get_value(performance_threshold, Options, 0.7),
        decision_complexity => proplists:get_value(decision_complexity, Options, medium),
        learning_plateau => proplists:get_value(learning_plateau, Options, true),
        goal_misalignment => proplists:get_value(goal_misalignment, Options, true),
        bias_detection => proplists:get_value(bias_detection, Options, true)
    }.

assess_cognitive_strengths(_Profile, _Data) -> [].
identify_cognitive_weaknesses(_Profile, _Data) -> [].
evaluate_metacognitive_awareness(_Profile, _Data) -> 0.5.
assess_adaptability(_Profile, _Data) -> 0.5.
collect_performance_data(_Data) -> #{}.
analyze_performance_trends(_Metrics) -> #{}.
generate_performance_insights(_Analysis) -> [].
analyze_self_awareness_levels(_State, _Data) -> 0.5.
evaluate_confidence_calibration(_State, _Data) -> 0.5.
assess_reflection_depth_effectiveness(_State, _Data) -> shallow.
analyze_cognitive_load_patterns(_State, _Data) -> low.
detect_confirmation_bias(_History) -> none.
detect_anchoring_bias(_History) -> none.
detect_availability_bias(_History) -> none.
detect_overconfidence_bias(_Profile, _History) -> none.
create_bias_insight(Bias) -> #reflection_insight{type = bias, content = Bias}.
analyze_single_decision(_Decision, _Data) -> #{}.
calculate_decision_quality_metrics(_Analysis) -> #{decision_quality => 0.8}.
generate_decision_improvement_insights(_Data) -> [].
calculate_learning_velocity(_Episodes) -> 0.7.
assess_learning_efficiency(_Episodes) -> 0.7.
evaluate_knowledge_retention(_Episodes) -> 0.8.
assess_transfer_learning_capability(_Episodes) -> 0.6.
generate_learning_improvement_insights(_Data) -> [].
assess_internal_goal_coherence(_Evolution) -> 0.8.
evaluate_goal_value_alignment(_Evolution, _Model) -> 0.8.
assess_goal_capability_alignment(_Evolution, _Model) -> 0.8.
identify_goal_coherence_issues(_Data) -> [].
apply_insights_to_self_model(_Insights, Model) -> Model.
synthesize_insights(Insights) -> Insights.
validate_insight_consistency(Insights) -> Insights.
generate_action_items_from_insights(_Insights) -> [].
integrate_new_action_items(New, Current) -> New ++ Current.
prioritize_improvement_actions(Plan) -> Plan.
extract_lessons_learned(_Insights) -> [].
derive_principles(_Insights) -> [].
update_mental_models(_Insights, Wisdom) -> maps:get(mental_models, Wisdom, []).
develop_heuristics(_Insights) -> [].
update_wisdom_patterns(_Insights, Wisdom) -> maps:get(patterns, Wisdom, []).
create_goal_misalignment_insight(Issue) -> #reflection_insight{type = goal_misalignment, content = Issue}.