The Familiar Frustration
Every engineer has faced it: you’re in the middle of drafting a report and think, “I’m sure we’ve solved this before, but where?”
The answer usually exists. It’s in a Phase I ESA from years ago, or a Geotech report on similar soil conditions. But finding it means combing through endless folders, hoping you stumble on the right file or realizing the person who knew the answer retired last year.
This is knowledge drain. It wastes time, erodes consistency, and keeps teams from building on the expertise they’ve already earned.
Why Knowledge Drain Hurts So Much
Engineering knowledge is highly specialized, anchored in site conditions, client requirements, and regulatory justifications that generic sources can’t capture. Losing that is losing a competitive asset.
- When senior staff retire, their insights go with them, leaving younger engineers to guess at how past problems were solved.
- When reports live in scattered folders, even the best language or methods may as well not exist.
- When every project feels like a blank slate, consistency across reports vanishes. One author writes it one way, another writes it differently, and clients notice.
Over time, this erodes efficiency, quality, and confidence.
Where AI Steps In
Artificial intelligence, applied thoughtfully, can help turn this around. Instead of treating old reports as static documents, AI can make them searchable, reusable, and even interactive.
In my own work at Quire, I’ve seen this play out through our development of Lazarus, a tool that transforms legacy reports into what feels like a living library. It works by:
- Smart search and chat: Engineers can ask questions (“show me all reports with clay soil and high-water tables”) and get direct, context-aware results.
- Content reuse: Proven sections, methods, or tables from prior reports can be dropped directly into new ones, saving hours of rework.
- Intelligent quality control: AI cross-checks narratives against tables, scopes, and standards, flagging inconsistencies before reports reach a client.
- Writing enhancement: Draft language can be refined for tone, clarity, or technical rigor, as well as aligned with a firm’s past deliverables.
The effect isn’t abstract. Firms using approaches like this have reported:
- Up to 70% reduction in time to final deliverable
- 50% increase in first-pass approvals
- As much as 98% less time spent searching for information
It’s like having every engineer who ever worked at the firm available on call, ready to share what they knew, in seconds.
What This Means for Younger Engineers
For engineers early in their careers, knowledge drain can feel like being dropped into the deep end. You’re expected to produce client-ready reports but often lack the context of how similar problems were handled before. AI changes that dynamic.
- Onboarding becomes faster: New hires gain access to “guru-level” insights from day one.
- Mentorship scales: Instead of waiting for a busy senior engineer to explain past work, younger staff can tap into the firm’s history instantly.
- Confidence grows: Engineers don’t just guess. They can back up decisions with precedents drawn from their own firm’s work.
This isn’t about replacing human mentorship, but about making sure experience doesn’t evaporate when people leave.
The Bigger Shift Ahead
What firms really need isn’t just better organization. It’s a mindset shift. Knowledge can no longer be treated as a byproduct of projects. It has to be seen as a strategic asset, on the same level as client relationships or technical expertise.
That shift means:
- Reframing archives as living resources: Reports shouldn’t sit idle in folders; they should actively shape how new work is done.
- Elevating knowledge to leadership discussions: Decisions about staffing, quality control, and client service are stronger when informed by the firm’s own history.
- Viewing AI as an enabler, not a shortcut: The point isn’t to replace engineers, but to free them from repetitive work so they can apply judgment where it matters most.
By reframing knowledge as a strategy, firms can turn years of hard-earned experience into a renewable resource. One that fosters innovation, guides teams through change, and builds client trust that lasts.
The Takeaway
Preserving institutional knowledge isn’t about legacy or efficiency alone. It’s about empowering engineers. The hours you save by not reinventing solutions are hours you can spend on innovation, deeper analysis, and professional growth.
AI, when applied in the right context, can unlock the collective intelligence inside every firm. It turns archives into assets, reports into resources, and missed opportunities into competitive advantage.
At its best, AI ensures that yesterday’s hard-earned lessons remain accessible, so no one has to solve the same problem twice.
About the Author: Chris Connell
Chris Connell, a seasoned executive with over 25 years of enterprise software and SaaS leadership, brings a wealth of expertise to his role at Quire, which he joined in April 2023.
Prior to Quire, Chris served as the president of iSolved Network at iSolved, a leader in the HCM software market. Over the course of three years, Chris spearheaded a period of remarkable growth, doubling revenue, achieving consistent 40% year-over-year growth in bookings, and expanding the platform’s user base to over 2 million employees.
Before iSolved, Chris held the CEO position at Trax Technologies, a global leader in Transportation Spend Management. Leading a team of over 500 employees across North America, Central America, Europe, and Asia, he oversaw $12 billion in annual transaction volume. In 2015, Chris orchestrated the successful merger of Trax and Veraction, and he was subsequently appointed CEO of the combined entity, overseeing the integration and launch of a best-in-class Total Transportation Spend Management platform. This followed his successful tenure as CEO of Veraction from 2012 through 2015, another market leading Transportation Spend Management company.
Prior to Trax, Chris served as president of AssetNation, a global online equipment marketplace, from April 2010 to May 2012. During his tenure, AssetNation experienced substantial growth, establishing itself as a leading online marketplace for industrial assets with annual commerce exceeding $100 million and a user base of over 100 million buyers. Following the acquisition of AssetNation by Ritchie Bros (RBA) in 2012, Chris assumed the role of president of Ritchie Bros EquipmentOne, where he led the integration and relaunch of the AssetNation marketplace as RB E1 for Ritchie Brothers, the largest global marketplace for industrial assets in the world.
Chris has also held key commercial leadership positions at Co-Exprise (now iValua) in the direct material procurement space, SEEC, an award-winning service-oriented architecture software company serving the financial services industry, and as VP of Global Account Management at Ariba/FreeMarkets (now SAP Ariba). At Ariba/FreeMarkets, Chris played a pivotal role in the company’s successful transition from on-premises to SaaS solutions, driving growth across the company’s manufacturing, CPG, and high-tech sectors.
Chris was an officer in the United States Marine Corps, holds a Master of Science degree from Boston University, and earned his Bachelor of Arts in Political Science from the Citadel.
