Agile Project Management Tools

Earlier this year, I facilitated a workshop for a new ID team. They were sharp. Motivated. Already juggling multiple projects. But when I asked how they were tracking their work… They pulled up a bullet list in a Word doc. 😬 No tasks. No dates. No owners. Just vibes. And I get it—project management often feels like the last thing we want to deal with. But if you’re the one doing the work, you should be the one leading the project. That means creating structure, setting expectations, and making it easy for your SMEs and stakeholders to collaborate with you. So, in this week’s video, I walk you through how I build a Gantt chart-style timeline for a real ID / eLearning project—from kickoff to launch. Inside, you’ll see how I... ✅ Break down the project into phases and detailed tasks ✅ Assign roles and responsibilities ✅ Estimate timelines and build in review cycles ✅ Use dependencies to manage shifting priorities ✅ Keep projects on track (without losing your mind) 🔗 Watch the full step-by-step video + grab the free template here: https://lnkd.in/g8xnQ72A 💬 How do you manage your ID or eLearning projects? I’d love to hear what works for you. Enjoy the rest of your week! 👋 Tim #eLearning #InstructionalDesign #LearningAndDevelopment

If you consider deploying a WFM tool, this is for you: Auto-scheduling and real time adherence capability is only a part of what you need to look at. What really makes the difference is all the mechanisms around the solution and how well does the tool fit into your existing setup. Here also some practical questions: Can you bulk upload employees or are you adding them one by one? Can you integrate with your HR system? Can you integrate with payroll or are you exporting and adjusting data manually? Are there technical limitations that will impact you later on? And if integrations are not possible, can you still design the process in a way that avoids manual work? These are the questions that define whether a WFM tool will actually deliver value. In many cases, the tool itself is not the issue. It’s how it’s implemented, connected, and used across teams. This is where we usually support clients, either to get more out of their current setup or to make better decisions before implementing a new one. If you’re currently evaluating your setup or not getting the expected value from your WFM tool, happy to exchange perspectives. 💜 rightWFM #workforcemanagement

Ever wanted to turn your n8n workflow into a proper API endpoint? You can expose any n8n workflow as an API that other apps can call. Perfect for building integrations without writing backend code. The setup is simpler than you think: → Add a Webhook trigger node to start your workflow → Set the trigger's "Response" property to "Using 'Respond to Webhook' node" → Build your workflow logic in between → Add a "Respond to Webhook" node at the end → Configure it with content-type: application/json → Return your data in JSON format Now your workflow has a URL that accepts requests and sends back responses. Just like a real API. Why this is cool? → No server management headaches → Built-in error handling → Visual workflow editor beats writing code → Integrates with 400+ services out of the box I've used this to create custom APIs for everything from data processing to notification systems. Saves weeks of development time. The Webhook URL becomes your API endpoint. Other apps can GET/POST/PUT data to it and get structured responses back.

Today Glide becomes a whole new beast with the beta release of ⚡ Workflows–eerily powerful automations, perfectly integrated with Glide, continuing in our tradition of elegant tools with understated power. All of our customers pair Glide with a third-party automation tool like Zapier or Make, which are great for connecting your app to a wide array of existing services, but awkward for data-intensive automations that our customers want to achieve for a few reasons: 1. Shared data and compute: previously, customers implemented the same logic in Glide & the automation tool, drastically increasing maintenance cost. Glide Workflows have direct access to the same tables and computations as your apps, so your interfaces and automations remain in lockstep. 2. Zapier and Make are optimized for processing single events, connecting tool A to tool B. Glide Workflows are designed for operations on tables and batch data; for example, it's easy to loop over all Orders, then all Items per Order, and then finally complete a summary step. Looping is absent, primitive, or convoluted in these other tools. 3. No-code computations as steps. Glide Workflows has access to Glide's set of powerful computational primitives, making it simple to run AI, call APIs, manipulate numbers and text, without using any formulas or code. Chain these computations with actions to build simple but powerful workflows. 4. One subscription. Businesses want to consolidate their vendors. Agencies want simpler billing for clients. No-code solutions are often cobbled together with many tools, but we want building in Glide to be simpler than that. Business customers get access to scheduled triggers today, and webhook, email, and integration triggers are coming soon. Looking forward to your feedback!

𝗜 𝗯𝘂𝗶𝗹𝘁 𝗮𝗻 n8n 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝘁𝗵𝗮𝘁 𝗿𝗲𝗽𝗹𝗮𝗰𝗲𝗱 𝗮𝗿𝗼𝘂𝗻𝗱 𝟰𝟳 𝗻𝗼𝗱𝗲𝘀 𝘄𝗶𝘁𝗵 𝗼𝗻𝗹𝘆 𝟮 𝗻𝗼𝗱𝗲𝘀. When it comes to n8n, we normally see those extremely comprehensive workflows that can overwhelm even the most avid users of the product, especially if they are the kind of workflows people want to just duplicate and use. It's no surprise that n8n builders obsess over flexing the most complex workflow, even if it may deliver the simplest of solutions. If you're building a solution, the solution needs to deliver and not seem overkill for anyone. Imagine explaining a 100-node n8n workflow to your customer? You'll probably end up writing instructions for people who need to understand the workflow and how to use it, sometimes even that doesn't help. 𝗦𝗼 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝘁𝗵𝗮𝘁 𝗰𝗿𝗼𝘀𝘀𝗲𝗱 𝗺𝘆 𝗺𝗶𝗻𝗱 𝘄𝗮𝘀: 𝗛𝗼𝘄 𝗰𝗮𝗻 𝗜 𝗺𝗮𝗸𝗲 𝗺𝘆 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝘀𝗶𝗺𝗽𝗹𝗲? Because 𝗵𝗲𝗿𝗲'𝘀 𝘄𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝘀 𝘄𝗵𝗲𝗻 𝘆𝗼𝘂 𝘀𝗰𝗮𝗹𝗲 𝗻𝟴𝗻 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀: 🔴 You're managing 30+ credentials across tools 🔴 Every API behaves differently (different auth, different limits, different errors) 🔴 Your custom logic is scattered across dozens of nodes 🔴 One broken credential kills the entire flow However, this isn't an n8n problem; it's an integration problem. I solved this by taking advantage of Model Context Protocol (MCP), particularly using MCP Gateways, so my workflow can work with any app or service without any complexity. 🛠️ 𝗪𝗵𝗮𝘁 𝗜 𝘂𝘀𝗲𝗱 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗯𝘂𝗶𝗹𝗱: - An input node. - An LLM of my choosing with provided instructions. - Fastn's UCL gateway and connected it to around 10-20 services/apps. Through this, 𝗜 𝘄𝗮𝘀 𝗮𝗯𝗹𝗲 𝘁𝗼 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁 𝘁𝗵𝗲 𝗳𝗼𝗹𝗹𝗼𝘄𝗶𝗻𝗴: ✅ Have my workflow act as a product owner. ✅ Have my workflow take designs from Figma and create, publish, and entire the project. ✅ Update teams and members about changes, updates, issues, and more. All from one command, two nodes, and a singular MCP gateway. If you're interested in replicating this process, 𝗜 𝗵𝗮𝘃𝗲 𝗿𝗲𝗰𝗼𝗿𝗱𝗲𝗱 𝘁𝗵𝗲 𝗲𝗻𝘁𝗶𝗿𝗲 𝘁𝘂𝘁𝗼𝗿𝗶𝗮𝗹 𝗶𝗻 𝗮 𝗯𝗹𝗼𝗴, 𝘄𝗵𝗶𝗰𝗵 𝘄𝗶𝗹𝗹 𝗿𝗼𝘂𝗴𝗵𝗹𝘆 𝘁𝗮𝗸𝗲 𝘆𝗼𝘂 𝟮-𝟯 𝗺𝗶𝗻𝘂𝘁𝗲𝘀. 𝗟𝗶𝗻𝗸 𝘁𝗼 𝘁𝗵𝗲 𝗯𝗹𝗼𝗴 𝗶𝗻 𝘁𝗵𝗲 𝗰𝗼𝗺𝗺𝗲𝗻𝘁𝘀.

🚀 Introducing JavAI Workflow 🦜🔂☕: Build programmatically custom agentic workflows, AI Agents, RAG systems for java I'm excited to introduce my new open-source project to the Java Community 🙅♂️🫡 JavAI workflow is a #Java library to build, package, integrate, orchestrate and monitor #agentic #AI systems for java developers 💡 Principles: Java-based, Stateful, Flexible, AI ecosystem integration, publish as API, Observability, Scalable. v.0.2.0 Features: - Graph code: Supports creation of Nodes, Conditional Nodes, Edges, and workflows as a graph. Build custom workflows with multiple transitions between nodes such as one-way, round trip and recursive. - Run workflow: jAI workflow supports sync and stream runs - Integration: #LangChain4j integration, enabling you build workflows using all the features that LangChain4j offers. This integration provides a comprehensive toolset for building advanced AI applications to integrate with multiple LLM providers and models. - Visualization: Generates workflow images using #Graphviz lib 🗺️ Future Features: - 🐙 Module supports from core lib. - ⚒️ Build module as MCP server. - ▶️ Publish workflow as API (SSE and REST) - 🐬 Dockerize, kubernetes and cloud deployments (Helm charts, docker) - 📈 OpenTelemetry integration (metrics and traces) - 🌐 Web-based playground to add, test, run and debug jAI workflows endpoints. This is the feature more expected for java communities Learn how to use it in your java project below 👇 🔗 github repo: https://lnkd.in/esMTnsMw 👨💻 examples repo: https://lnkd.in/e7qisqDV #AI #LangChain #java #agents #system #opensource #workflow #orchestrator #rag #gpt

When an Account owner changes in Salesforce, business users often expect all related records (Contacts, Cases, Opportunities, Orders, Invoices, etc.) to follow the new owner. But this is not standard behaviour for custom objects, and even some standard ones too. There are common ways to approach this — multiple Flows, object-specific triggers, or scheduled jobs. Each works, but they tend to be either hard to maintain, fragmented, or not real-time. I wanted a design that was scalable, maintainable, and declarative where possible. Here’s what I built: 1 - A record-triggered Flow, which detects the Account ownership change. 2 - The Flow invokes a single Apex method that performs the ownership cascade. 3 - A Custom Metadata Type defines which objects are included, and which lookup field ties them to the Account. - The Apex dynamically queries and updates the related records in a bulk-safe way. This approach isn’t the only valid one. You could use separate triggers on each child object, or even solve access concerns with Territory Management or sharing rules. But in this case, explicit ownership needed to change, and I wanted to avoid scattering logic across multiple places. What makes this design valuable is how it balances trade-offs: • Configurable: adding or removing objects is a metadata update, not a code change. • Bulk-safe: it can handle a single update or a large batch without hitting limits. • Separation of concerns: Flow handles orchestration, Apex handles logic. • Hybrid approach: declarative where possible, programmatic where necessary. Lesson learned: the best Salesforce solutions often come from combining declarative tools with programmatic techniques, rather than forcing one approach. By using metadata to control Apex behaviour and letting Flow handle orchestration, you get something that is scalable, flexible, and still admin-friendly. #Salesforce #SalesforceArchitect #SalesforceFlow #Apex #CustomMetadata #SolutionArchitecture #Automation #ClicksNotCode #LowCode #ProCode #SalesforceConsultant #SystemDesign

I just solved a workflow problem that was eating hours of my time every week - and I want to share how I did it. Like many content creators, I was manually converting my Beehive newsletter drafts into markdown for my website. Copy, paste, reformat, fix images, adjust embeds... you know the drill. It was tedious and error-prone. So I built a custom MCP (Model Context Protocol) server in Java that: • Connects directly to Beehive's API • Pulls draft content automatically • Converts HTML to my specific markdown format • Handles images, YouTube embeds, and Twitter posts • Creates files in the right directory structure The best part? I can just tell Claude: "Grab the latest draft and create the markdown file for my website" - and it handles everything. This isn't just another toy tutorial. It's a real solution to a real problem that saves me hours every week. The MCP server gives Claude the exact tools it needs to automate complex workflows that would be painful to script manually. I've even set up GitHub Actions to build native images for Mac, Windows, and Linux - so you don't need Java installed to use it. The source code is available on GitHub if you want to see how it works or build something similar for your own workflow. What manual tasks in your workflow could benefit from this kind of automation? Sometimes the best solutions come from scratching your own itch. Watch the full demo: https://lnkd.in/e-M2fMZy ##MCP #Java

When managing complex workflows, orchestrating tasks effectively is essential. Apache Airflow is a powerful tool that can help automate and manage these workflows, ensuring tasks run on time and in the correct sequence. Benefits of Using Apache Airflow ● Scalability: Handles complex workflows, suitable for both startups and large enterprises. ● Flexibility: Write workflows in Python, allowing for custom logic and easy integration with other systems. ● Monitoring & Alerts: Track the status of your workflows in real time and get notified of issues. ● Extensibility: Airflow's wide range of built-in operators, along with custom operators, enables it to connect to almost any system or tool in your tech stack. Real-Life Example: Managing E-commerce Data Pipelines Imagine you’re managing a large e-commerce platform where daily tasks include multiple tasks like Collecting sales data, Processing and cleaning them. Loading the data into data warehouse. Running analytics etc. With Apache Airflow, you can create a Directed Acyclic Graph (DAG) to define the order and dependencies of these tasks. For example, Airflow will ensure the data processing starts only after data collection is complete, and analytics only runs after data loading is successful. This automation saves time, reduces errors, and ensures your team always has the latest information. #DataEngineering #Databricks #WhatsTheData

✅ USE CASE: Automated Proposal Delivery Using Make ➕ Salesforce ➕ Google Workspace 🧩 Business Need: A client needed to automatically send personalized business proposals to every new lead they received through Google Forms (stored in Google Sheets). The proposals had to be generated dynamically based on existing Salesforce data and delivered through Gmail as part of their sales workflow. They were already managing customer records in Salesforce, but they didn’t want their sales team spending time checking, copying, pasting, and emailing manually. ⚙️ Solution: We designed a simple and fast automation flow using Make, that integrates natively with Google Workspace and Salesforce. 🔁 End-to-end process: Lead Entry via Google Sheets: New leads are collected through a Google Form and saved into a spreadsheet. Check if Lead Exists in Salesforce: Make searches Salesforce using the lead’s email address to see if it already exists. Routing: ✅ If the lead exists: → We fetch all lead details from Salesforce → Auto-generate a business proposal using a Google Docs template → Create a Gmail draft with the proposal link and a personalized message ❌ If the lead does not exist: → We create a new Lead record in Salesforce → Update the Google Sheet to reflect that the lead has been inserted 💡 Although this could be built using native Salesforce Flows or Apex, it would take more time and involve more complex setup and testing. We chose Make because: It has native connectors for Gmail, Google Docs, Sheets, and Salesforce. It allows us to build and test fast. It’s ideal for prototypes, MVPs, or teams that want to move quickly without developer resources. 🔎 What we considered during implementation: ✅ Error handling: We know Salesforce can fail silently if required fields are missing. We made sure to build conditional checks and fallback steps (e.g. logging status in Google Sheets). ✅ API limits and quotas: Google Sheets has daily limits on write operations. We added row limits and included logic to avoid overload (e.g., processing only unprocessed leads marked as Processed = FALSE). ✅ Data validation: Each field passed to Salesforce or Gmail is validated and formatted to reduce rejection or formatting issues. 🎯 Impact: Business proposals are generated and sent in seconds, not hours. No more copy-pasting or manual entry. Sales team focuses on real conversations, not admin work. The process is scalable, trackable, and easily editable. 📣 This is just one of many ways to combine Make + Salesforce + Google Workspace to automate real business problems. #Salesforce #Automation #Make #CRM #GoogleSheets #LeadManagement #WorkflowAutomation #Gmail #Proposals #Productivity