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  1. Asked: November 10, 2025In: Wordpess

    Why are WooCommerce orders paid successfully but not showing in the admin after enabling Redis cache?

    Zayn Siddiqui
    Zayn Siddiqui
    Added an answer on January 10, 2026 at 1:25 pm

    This happens because Redis is serving stale query results, not because the orders are missing. WooCommerce writes order data correctly to the database, but when Redis or Memcached is misconfigured, WordPress reads cached query results instead of fetching fresh rows. That makes it look like orders neRead more

    This happens because Redis is serving stale query results, not because the orders are missing.

    WooCommerce writes order data correctly to the database, but when Redis or Memcached is misconfigured, WordPress reads cached query results instead of fetching fresh rows. That makes it look like orders never existed even though they are safely stored.

    You can confirm this by disabling the object-cache plugin and refreshing the Orders page. If the missing orders suddenly appear, the database is fine and the cache is the problem.

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  2. Asked: March 15, 2025In: Salesforce

    Why do Salesforce tests pass but logic fails in production?

    Lial Thompson
    Lial Thompson
    Added an answer on January 10, 2026 at 7:10 am

    Tests don’t always mirror real data or permissions. Edge cases go untested. Production reveals gaps. Better test realism helps.Takeaway: Passing tests don’t guarantee correctness.

    Tests don’t always mirror real data or permissions. Edge cases go untested.

    Production reveals gaps.

    Better test realism helps.
    Takeaway: Passing tests don’t guarantee correctness.

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  3. Asked: March 11, 2025In: Salesforce

    Why do Lightning Web Components feel slower as data volume increases?

    Pawan Sehrawat
    Best Answer
    Pawan Sehrawat Begginer
    Added an answer on January 10, 2026 at 5:32 am

    The slowdown usually comes from server-side data handling rather than the UI itself. Large SOQL queries, excessive serialization, and returning unnecessary fields all increase response time. On the client side, rendering large data structures or repeatedly re-rendering components also adds overhead.Read more

    The slowdown usually comes from server-side data handling rather than the UI itself. Large SOQL queries, excessive serialization, and returning unnecessary fields all increase response time. On the client side, rendering large data structures or repeatedly re-rendering components also adds overhead.

    Most teams solve this by limiting queried fields, adding pagination, caching results, and ensuring Apex methods are purpose-built for UI consumption.
    Takeaway: LWC performance issues usually start in Apex, not JavaScript.

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  4. Asked: April 9, 2025In: Salesforce

    Why does Apex code hit governor limits even after basic bulkification?

    Harmeet Krishna
    Harmeet Krishna Begginer
    Added an answer on January 10, 2026 at 5:26 am

    Bulkification solves only the most obvious limit issues. Once data volumes grow, limits are often hit due to large heap usage, expensive logic inside loops, trigger recursion, or automation chains triggered by DML. Even a single bulk-safe update can cascade into multiple Flows, triggers, and processRead more

    Bulkification solves only the most obvious limit issues. Once data volumes grow, limits are often hit due to large heap usage, expensive logic inside loops, trigger recursion, or automation chains triggered by DML. Even a single bulk-safe update can cascade into multiple Flows, triggers, and processes.

    The usual fix is to reduce the total work done per transaction—filter records aggressively, avoid unnecessary field queries, and break work into asynchronous jobs when possible.
    Takeaway: Governor limits are about total work, not just where SOQL and DML are placed.

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  5. Asked: April 1, 2025In: Salesforce

    Why do Salesforce Flows become hard to maintain as automation grows?

    Mohan Sharma
    Mohan Sharma Begginer
    Added an answer on January 10, 2026 at 5:18 am

    Flows become hard to maintain because they scale visually, not structurally. Each new requirement adds branches, decisions, and record updates, but there’s no strong modularity like you’d have in Apex. Over time, logic that should be reusable or isolated ends up duplicated across paths, making changRead more

    Flows become hard to maintain because they scale visually, not structurally. Each new requirement adds branches, decisions, and record updates, but there’s no strong modularity like you’d have in Apex. Over time, logic that should be reusable or isolated ends up duplicated across paths, making changes risky.

    Teams usually handle this by splitting responsibilities: keeping Flows focused on orchestration and moving complex logic into Apex, subflows, or reusable components. Clear naming, documentation, and strict ownership rules also help slow down entropy.

    Takeaway: Flows work best when they stay simple and delegate complexity elsewhere.

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  6. Asked: January 2, 2025In: Cybersecurity

    Why does my API leak internal details through error messages?

    Jonny Bones
    Jonny Bones Begginer
    Added an answer on January 6, 2026 at 7:41 am

    Verbose error messages often reveal internal implementation details that attackers can use to understand system behavior. These leaks usually occur when development-mode error handling is accidentally enabled in production. While detailed errors are useful during debugging, they shouldn’t be exposedRead more

    Verbose error messages often reveal internal implementation details that attackers can use to understand system behavior. These leaks usually occur when development-mode error handling is accidentally enabled in production.

    While detailed errors are useful during debugging, they shouldn’t be exposed externally once an application is live. Instead, applications should return generic error messages to clients and log detailed diagnostics internally.

    Balancing usability and security means being intentional about what information is shared and with whom.

    Takeaway: Errors should help developers internally without revealing internals to users.

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  7. Asked: November 11, 2025In: Cybersecurity

    Why does zero-trust architecture still experience breaches?

    Samay Mathur
    Samay Mathur Begginer
    Added an answer on January 6, 2026 at 7:29 am

    Zero trust reduces implicit trust but doesn’t eliminate all attack vectors. If credentials are compromised or authorization policies are overly permissive, attackers can still gain access—just with more friction. Many breaches occur because zero trust is only partially implemented. Identity may be eRead more

    Zero trust reduces implicit trust but doesn’t eliminate all attack vectors. If credentials are compromised or authorization policies are overly permissive, attackers can still gain access—just with more friction.

    Many breaches occur because zero trust is only partially implemented. Identity may be enforced, but monitoring, segmentation, or continuous verification may be weak or inconsistent.

    Zero trust improves resilience, but it doesn’t make systems breach-proof.

    Takeaway: Zero trust lowers risk, it doesn’t eliminate it.

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    Merab added an answer Changes ripple through automation. Hidden dependencies exist. Testing catches regressions.Takeaway:… June 12, 2026 at 6:37 am
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    Theodore Marcus added an answer Salesforce error messages are designed to be generic to avoid… June 11, 2026 at 7:00 am
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  1. Asked: May 11, 2026In: Salesforce

    Why does my Salesforce Flow fail in production but work in sandbox?

    Dimitri Shyplenkov
    Dimitri Shyplenkov Begginer
    Added an answer on May 12, 2026 at 4:58 am

    Production data, permissions, or automation differ from sandbox. Problem Explanation Sandboxes rarely mirror production exactly, leading to runtime differences. Root Cause(s) 1. Missing permissions 2. Different record data 3. Additional automation in prod Step-by-Step Solution 1. Debug Flow in produRead more

    Production data, permissions, or automation differ from sandbox.

    Problem Explanation

    Sandboxes rarely mirror production exactly, leading to runtime differences.

    Root Cause(s)
    1. Missing permissions
    2. Different record data
    3. Additional automation in prod
    Step-by-Step Solution
    1. Debug Flow in production safely
    2. Compare permissions and profiles
    3. Review active automation
    Edge Cases & Variations
    1. Production-only validation rules
    2. Integration users behave differently
    Common Mistakes to Avoid
    1. Testing only in sandbox
    2. Assuming identical environments

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  2. Asked: May 11, 2026In: Salesforce

    Why does my Apex HTTP callout fail with “Callout not allowed from this context”?

    Vaibhav Sharma
    Vaibhav Sharma Begginer
    Added an answer on May 12, 2026 at 4:14 am

    Callouts are not permitted from synchronous trigger execution. Problem Explanation Salesforce restricts HTTP callouts from certain contexts, including standard triggers and some Flow actions. Root Cause(s) 1. Callout inside trigger 2. Callout inside non-async Apex 3. Mixed DML before callout Step-byRead more

    Callouts are not permitted from synchronous trigger execution.

    Problem Explanation

    Salesforce restricts HTTP callouts from certain contexts, including standard triggers and some Flow actions.

    Root Cause(s)
    1. Callout inside trigger
    2. Callout inside non-async Apex
    3. Mixed DML before callout
    Step-by-Step Solution
    1. Move callout logic to @future(callout=true) or Queueable
    2. Invoke async method from trigger
    3. Ensure no DML before callout in same transaction
    Edge Cases & Variations
    1. Platform Events allow callouts asynchronously
    2. Named Credentials simplify auth handling
    Common Mistakes to Avoid
    1. Calling APIs directly from triggers
    2. Ignoring transaction order

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  3. Asked: May 10, 2026In: AI & Machine Learning

    Why does my deployed LLM give inconsistent answers to the same prompt?

    Anjali Singhania
    Anjali Singhania Begginer
    Added an answer on May 11, 2026 at 5:49 pm

    This is usually due to sampling settings rather than model instability. Parameters like temperature, top-k, and top-p introduce randomness. If these aren’t fixed, outputs will vary even for identical inputs. Set deterministic decoding for consistent responses, especially in production. Also verify tRead more

    This is usually due to sampling settings rather than model instability.
    Parameters like temperature, top-k, and top-p introduce randomness. If these aren’t fixed, outputs will vary even for identical inputs. Set deterministic decoding for consistent responses, especially in production. Also verify that prompts don’t include dynamic metadata like timestamps.
    Common mistakes:

    1. Leaving temperature > 0 unintentionally
    2. Mixing deterministic and sampled decoding
    3. Assuming reproducibility by default

    Determinism must be explicitly configured.

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