We asked a group of AlphaOak consultants one simple question: What is the one thing that genuinely makes your workday easier? The answers ranged from AI automation to a coffee warmer—and revealed something more useful about productivity along the way.
There is a particular irony in asking consultants how they stay productive. Much of our professional lives is spent looking at how other organizations work: where processes break down, where unnecessary steps have accumulated, where information gets lost, where technology creates friction instead of removing it, and where a relatively small change could make an entire system work better. Then we close the client diagram, return to our own desks, and discover 17 browser tabs, four conversations we meant to return to, a meeting starting in three minutes, and a cup of coffee we made sometime around breakfast.
So during a recent AlphaOak Wednesday Connect Hour, we turned the lens inward and asked the team a deceptively simple question: What is your favorite productivity hack—the one thing that genuinely makes your workday easier? It could be a piece of software, a gadget, an AI tool, a shortcut, or simply a slightly strange way of doing something better.
What followed was not a collection of elaborate productivity systems. In fact, that was precisely what made the conversation interesting. The answers ranged from a physical mute button and automated coffee to AI-built memory systems, carefully controlled notifications, morning walks, browser profiles, Markdown files, and a good old-fashioned notebook. Beneath that variety, however, was a surprisingly consistent idea: productivity is often less about getting more work done and more about removing the small pieces of friction that repeatedly get in the way of doing good work.
Make the Important Things Obvious
Michael Haydock started with perhaps the most visually satisfying answer: a GLOWING physical mute button that sits on his desk. When he is muted, the device tells him. When he is live, it tells him that too. Instead of searching for a tiny microphone icon inside whichever collaboration platform happens to be open, he can tap one physical control. It is an almost comically simple solution to a problem that somehow persists despite decades of technological progress: the professional world still spends an astonishing amount of time saying, “You’re on mute.”
The real value of Michael’s setup, however, is not the button itself. It is the design principle behind it. Important information should be visible, and frequent actions should be easy. If you perform something dozens of times every day, even a small amount of unnecessary friction compounds. Michael has essentially taken a recurring digital decision and turned it into muscle memory.
Tony Buffington immediately supplied the business case. He remembered people on a previous project who did not realize they were unmuted while discussing other members of the project team. Michael’s glowing button, Tony observed, could have saved them from “a lot of apologies.” Shortly afterward, multiple members of the team were discussing buying one themselves. Productivity lesson number one nearly became an AlphaOak procurement event.
Sometimes Tomorrow’s Productivity Starts Tonight
Shayan Khodafar’s approach was decidedly less technological. He prepares for the next morning before the current day ends. He checks what is coming, sets an alarm around an early meeting if necessary, and removes whatever small obstacles he can in advance. That includes coffee. His coffee maker sits on a smart plug, and he prepares the beans, filter, and water the night before so the coffee can begin brewing automatically in the morning.
The important part is not the coffee, although waking up to the smell of coffee received enthusiastic support from the group. Shayan’s system is really about moving decisions away from the moments when you are least equipped to make them. Five minutes of preparation the evening before can be much easier to find than five minutes during a morning in which a child needs something, a meeting is approaching, an RFP is competing for attention, and the day has already begun making demands.
Michael described the practice as “grooming your calendar for the next day,” and that may be the more broadly useful habit. Many difficult workdays begin before the work itself becomes difficult. We start by reacting. We discover the first meeting instead of anticipating it. We open email before deciding what actually matters. Other people’s priorities arrive before our own have been established. Shayan’s routine is essentially a small daily preflight check: know what tomorrow looks like before tomorrow arrives.
Decide What Deserves to Interrupt You
Jayson Parker approaches productivity from another direction: controlling digital noise before it controls him. At the beginning of the day, he checks for operating-system, application, and network updates so they do not suddenly appear while he is presenting or concentrating on something else. More importantly, he uses focus settings across his devices so that during the first part of his workday, only notifications he considers important are allowed through.
It is a small configuration change with a larger philosophy behind it. Notifications are not neutral. Every red badge, banner, vibration, Teams message, email alert, software update, and calendar reminder is making a tiny request for the same finite resource: attention. The productivity cost is not merely the few seconds required to look at a notification. It is the mental transition away from the problem that was being solved before it arrived.
Jayson’s solution is not to become faster at processing interruptions. It is to stop treating every interruption as equally entitled to his attention. The notification can wait. The work in front of him may not be able to.
Give AI the Work Humans Predictably Avoid
The conversation became considerably more technical when Bill Busath described the small AI-enabled systems he has been building around his own work. His problem will be familiar to anyone managing multiple projects, meetings, AI conversations, and parallel workstreams: information does not necessarily disappear because it was unimportant. Sometimes it disappears because something else became urgent five minutes later.
For meetings, Bill built a process that reviews Teams recordings and transcripts, identifies important moments, captures relevant screenshots, and preserves them with the meeting record. The distinction is important. A generic meeting summary may tell him what happened, but sometimes he needs to return weeks later and understand precisely what someone was showing on screen when a particular decision was discussed. His system preserves not just the conclusion but some of the original context around it. He is also developing a higher-level way of keeping track of his numerous AI and coding threads so that an idea or task he started several days earlier does not disappear simply because another priority interrupted it.
Bill applies the same thinking outside work. He has built automations that scan email for vehicle-service records and preserve the information by car. Another captures receipts associated with home renovations so they can be retrieved later. These are not glamorous AI use cases, which is precisely why they are interesting. They address the administrative work people know they should do but often do inconsistently because it is repetitive, tedious, and easy to postpone.
There is a practical AI strategy hiding here for organizations as well. Before searching for the most sophisticated thing AI could possibly do, identify the boring, structured, recurring tasks people already dislike doing. If something has to happen repeatedly, follows a recognizable pattern, and routinely falls through the cracks because nobody enjoys maintaining it, it is probably worth investigating as an automation candidate.
AI does not always need to invent the future. Sometimes it just needs to file the receipt.
Structure the Context, Not Just the Prompt
Paul Murrietta offered another increasingly important AI habit. He has been using Markdown files to organize functional designs, instructions, and other information that can then serve as reusable context when working with AI. Instead of reconstructing the same background repeatedly inside individual conversations, the relevant knowledge can be structured and carried with the work.
The broader lesson is becoming increasingly important as organizations adopt AI. We spend enormous energy debating which model is best, but the usefulness of any model is heavily influenced by the quality of the context surrounding the task. Scattered instructions, undocumented assumptions, inconsistent terminology, and fragmented project knowledge do not magically become organized because AI has entered the conversation. The better the underlying context, the more useful the resulting interaction can become.
Paul’s systems instinct extends beyond the office. He also runs a centralized home media server, automates household devices, and has considered creating what amounts to a personal plant-maintenance system for his house—something that could track recurring activities such as pool maintenance and gutter cleaning. At AlphaOak, apparently, you can take the consultant out of EAM, but there is no guarantee you can take EAM out of the consultant.
Not Everything Needs an API
Then Tony brought the conversation firmly back to earth. His productivity tools include a banker’s lamp that makes his keyboard easier to see and an old-fashioned electric cup warmer that keeps his coffee hot when work distracts him long enough to forget that he made it.
There is something refreshingly important about that answer. Technology professionals can occasionally develop a tendency to engineer an impressive solution to a very unimpressive problem. Tony’s approach is the opposite. If the problem is that the keyboard is difficult to see, add a light. If the coffee gets cold, keep the coffee warm.
The objective is not to build the most sophisticated solution. It is to solve the actual problem.
That principle applies surprisingly well beyond desk accessories. In enterprise technology, complexity can acquire an aura of seriousness. A solution involving more components, more integrations, or more technology can appear inherently more transformational. It is worth remembering that elegance frequently looks like subtraction. Sometimes the best architecture really is the equivalent of a $20 coffee warmer.
Paper Has Not Received the End-of-Life Notice
Nevin Gamble offered an equally useful counterpoint to the increasingly digital conversation. He described himself as “an analog guy.” A large notebook sits next to his desk, and he writes things down throughout the day. He knows where the information is, he can return to it easily, and he does not need another application to manage the system that is supposed to help him manage everything else.
In an industry currently fascinated by AI-powered knowledge management, there is something wonderfully stubborn about a notebook continuing to work exactly as advertised. Yet Nevin and Bill are actually solving versions of the same problem. Both need a reliable way to extend human memory. Bill builds technology that captures and resurfaces information across digital workstreams. Nevin puts pen to paper.
Neither method is inherently more productive. The better system is the one that reliably changes what happens when you need the information again.
That is an important point because productivity advice often becomes prescriptive. Use this application. Adopt this framework. Automate this workflow. Create this morning routine. But a system that is theoretically superior and practically abandoned after three weeks is not superior at all. A notebook used every day will outperform an elaborate productivity platform nobody remembers to open.
Protect the Human Operating the System
Sarina Miller shifted the conversation from tools to the person using them. Her most important productivity practice is protecting time at the beginning of the day for herself. She walks, exercises, spends time thinking or meditating, and identifies the few things that matter most before allowing the rest of the day to begin competing for her attention.
Her point was not that everyone needs to adopt the same morning routine. It was that after years of balancing work, family, and other responsibilities, she discovered that starting the day by taking care of herself changed how she approached everything that followed. That may sound less tactical than a notification setting or an automation, but it addresses the resource on which every other productivity system ultimately depends.
Knowledge work is cognitively expensive. Yet productivity conversations frequently treat the human being as the inconvenient variable in the system. We optimize calendars, automate workflows, eliminate clicks, summarize meetings, deploy AI assistants, and configure increasingly sophisticated digital environments while quietly assuming that the person operating all of this machinery has unlimited capacity.
They do not. Sometimes a walk before the first meeting does more for the quality of the next four hours than another application ever could.
The Best Productivity System May Be the One You Build Around Yourself
By the end of the conversation, Shayan pointed out just how wide the spectrum had become. The discussion had moved from making coffee ahead of time to, in his words, becoming “existentially grounded” before tackling the day. He was joking, but he had also identified what made the conversation useful.
There was no universal system.
Michael reduces ambiguity. Shayan removes tomorrow’s friction tonight. Jayson protects attention. Paul structures context. Bill externalizes memory and automates administrative work. Tony fixes simple problems with simple tools. Nevin trusts paper. Sarina protects the person who has to do all of it.
Different techniques, but remarkably similar objectives.
Most of us do not need to become dramatically more productive. We need to identify the handful of small frictions that steal attention repeatedly throughout the week. The meeting we nearly forget. The notification that breaks concentration. The information we know we will never remember. The repetitive task we continually postpone. The cold coffee. The morning that begins in reaction mode before we have decided what matters.
Those problems rarely require a grand productivity transformation. They require noticing what repeatedly gets in the way and being willing to design around it.
That may mean AI. It may mean automation. It may mean better information architecture. It may mean walking outside before opening Teams.
And sometimes it may simply mean buying a very large glowing button that makes absolutely certain you know when you’re on mute.
Judging by the reaction from our consultants, we may need to order those in bulk.