Draftly: Platform Stabilization, LinkedIn API Fix, Scheduling Logic Repair & Infrastructure Cleanup for an AI-Powered LinkedIn Content Platform
AddWeb Solution was hired to stabilize the entire platform and provide technical remediation for Draftly, an AI-powered content creation and management platform for professionals and entrepreneurs developing their personal brands with content that is consistent and high-quality. In a 15-week engagement, we eliminated unused Git branches, outdated Cloudflare resources, legacy configurations, and obsolete email accounts to deliver a stable, reliable, and maintainable platform, while solving critical functionality problems across LinkedIn comment integration, scheduled post publishing, active user detection, browser extension validation, and subscription verification.
The Business Needs
When an AI-Powered Content Platform’s Own Infrastructure Undermines the Experience It Promises to Deliver
Draftly is created on an alluring guarantee—to help experts, creators, and marketers create a robust LinkedIn profile without the time and effort typically needed for regular content creation, using AI-powered material generation, clever scheduling, performance analytics, and audience interaction features. Functional problems that can’t get posts out the door on time or block users from commenting on posts are not just about making things easier for people; they are a contradiction to the platform’s core offering of reliability and automaticity.
The platform had several outstanding problems, which, when combined, were degrading the user experience, reliability of the platform, and maintainability of the system. Draftly’s extension to LinkedIn prevented users from leaving comments on LinkedIn, which is essential for the platform’s engagement capabilities. The smart scheduling feature, one of the key highlights of the platform, was not always clear on the date and time the posts were being scheduled and was not always reliable or trustworthy. The users could not also edit or delete scheduled posts within the time frame set before the publication of the posts, eliminating one basic function that any scheduling platform should offer.
The inconsistencies in detecting active users and validating browser extensions to verify subscription status created access control weaknesses for the platform, impacting the user experience and the integrity of the subscription system. Technical debt was also piling up at the infrastructure level, with the combined risk of obsolete email accounts, inactive Cloudflare resources, legacy configurations and outdated Git branches adding to the burden of maintaining the platform, where user data and LinkedIn API credentials are processed.
About Our Client: Vibhu Dhariwal engaged AddWeb Solution to take full ownership of Draftly’s platform stabilization, resolving all critical functional issues, repairing the scheduling engine, fixing the LinkedIn API integration, and cleaning up the infrastructure to deliver a reliable, secure, and maintainable platform for professionals and businesses building their LinkedIn presence.
Our Approach
Systematic Diagnosis, Prioritized Remediation, and Infrastructure Cleanup Across a React and Node.js LinkedIn Platform
AddWeb Solution began with a comprehensive audit of the Draftly platform, working through the full codebase, LinkedIn API integration, scheduling logic, browser extension validation system, and infrastructure layer to map every functional issue and technical debt item before any remediation work began. This audit-first approach ensured that all fixes were implemented with a complete understanding of their dependencies and potential knock-on effects across the platform.
The LinkedIn comment integration was identified as the highest-priority user-facing issue, a broken plugin integration preventing users from posting comments through Draftly’s browser extension. This was addressed through a thorough diagnosis of the LinkedIn API connection, browser extension API handling, and the integration layer between them, with the fix validated end-to-end through complete comment posting workflows before sign-off.
The scheduling engine was the most technically complex remediation target. Posts not publishing at configured times indicated issues across multiple layers: scheduling logic, time zone handling, and background processing, each of which needed to be diagnosed, fixed, and tested independently before the full scheduling pipeline was validated. Time zone handling was a particularly nuanced challenge, given that Draftly serves users across multiple regions who schedule content for specific audience time zones that may differ from their own.
Active user detection and browser extension validation were audited and corrected to ensure subscription verification and user access control were functioning accurately, closing the gaps that were allowing inconsistencies in how the platform identified and authenticated active subscribers. Edit and delete functionality for scheduled posts was implemented within the correct time window logic, giving users the content management control they expected from a professional scheduling platform.
The infrastructure cleanup was executed systematically, removing unused Git branches that were cluttering the repository and creating confusion around the active codebase, decommissioning inactive Cloudflare resources, removing legacy configurations that were no longer relevant to the platform’s current architecture, and retiring obsolete email accounts that represented both maintenance overhead and potential security exposure.
The Solution
What It Delivers for Draftly
A LinkedIn Comment Feature That Actually Works
Draftly’s users can now post LinkedIn comments through the platform’s browser extension without errors or failures, restoring a core engagement feature that is fundamental to building authentic LinkedIn presence and community.
Scheduled Posts That Publish When They’re Supposed To
The repaired scheduling engine, time zone handling, and background processing mean users can trust that content scheduled for a specific date and time will publish exactly when configured, making smart scheduling a reliable feature rather than an unreliable one.
Content Management Users Expected From Day One
Edit and Delete Functionality Within the Allowed Pre-publication Window Gives Users Basic but Essential Control over Their Scheduled Content, Correcting a Gap That Was Undermining Confidence in the Platform as a Professional Content Management Tool.
Subscription Verification That Works Correctly
Accurate active user detection and browser extension validation mean subscription access control is functioning as intended, protecting subscription integrity and ensuring users receive the access level their plan entitles them to.
A Codebase That’s Maintainable Going Forward
The removal of unused Git branches, legacy configurations, and obsolete infrastructure means the development team is working with a clean, current codebase—reducing maintenance overhead and making future development faster and less error-prone.
Reduced Security Exposure Across the Infrastructure
Inactive Cloudflare resources and obsolete email accounts removed from the infrastructure eliminate potential attack surfaces, reducing the platform’s security exposure without affecting any active functionality.
A Platform That Delivers on Its Promise
With functional issues resolved and infrastructure cleaned, Draftly now operates as the reliable, stable platform its AI-powered LinkedIn content promise requires, giving professionals and businesses a tool they can depend on to manage their LinkedIn presence consistently.
Key Features & Activities
How It Was Done
Screenshots
Showcasing Draftly’s Stabilized Post Scheduling, LinkedIn Plugin Fix, Browser Extension Validation & Infrastructure Cleanup Delivered in 15 Weeks
Client Testimonial
What Our Client Says
Final Outcome
Delivering a Stable, Reliable, and Maintainable LinkedIn Content Platform in 15 Weeks
Through AddWeb Solution’s comprehensive platform stabilization engagement, Draftly now operates as the reliable, high-performance LinkedIn content platform its AI-powered promise requires. All critical functional issues have been resolved; LinkedIn comments are posted successfully through the browser extension, scheduled content publishes at the configured date and time across all time zones, and users have full edit and delete control over their scheduled posts within the allowed window.
Subscription verification and user access control are now functioning accurately, with active user detection and browser extension validation correctly identifying and authenticating subscribers across all access points. The infrastructure cleanup has delivered a significantly cleaner operational environment, with unused Git branches, inactive Cloudflare resources, legacy configurations, and obsolete email accounts all removed, leaving a codebase and infrastructure that is materially easier to maintain, develop against, and secure going forward.
With a client happiness score of 9/10 and all functional and infrastructure issues resolved, Draftly is positioned to deliver on its core promise, giving professionals, founders, marketers, and businesses a reliable, AI-powered LinkedIn content platform they can trust to manage their personal brand and LinkedIn presence consistently and effectively.
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